Fireside Product Management

TLDR: It was Claude :-)When I set out to compare ChatGPT, Claude, Gemini, Grok, and ChatPRD for writing Product Requirement Documents, I figured they'd all be roughly equivalent. Maybe some subtle variations in tone or structure, but nothing earth-shattering. They're all built on similar transformer architectures, trained on massive datasets, and marketed as capable of handling complex business writing.What I discovered over 45 minutes of hands-on testing revealed not just which tools are better for PRD creation, but why they're better, and more importantly, how you should actually be using AI to accelerate your product work without sacrificing quality or strategic thinking.If you're an early or mid-career PM in Silicon Valley, this matters to you. Because here's the uncomfortable truth: your peers are already using AI to write PRDs, analyze features, and generate documentation. The question isn't whether to use these tools. The question is whether you're using the right ones most effectively.So let me walk you through exactly what I did, what I learned, and what you should do differently.The Setup: A Real-World Test CaseHere's how I structured the experiment. As I said at the beginning of my recording, “We are back in the Fireside PM podcast and I did that review of the ChatGPT browser and people seemed to like it and then I asked, uh, in a poll, I think it was a LinkedIn poll maybe, what should my next PM product review be? And, people asked for ChatPRD.”So I had my marching orders from the audience. But I wanted to make this more comprehensive than just testing ChatPRD in isolation. I opened up five tabs: ChatGPT, Claude, Gemini, Grok, and ChatPRD.For the test case, I chose something realistic and relevant: an AI-powered tutor for high school students. Think KhanAmigo or similar edtech platforms. This gave me a concrete product scenario that's complex enough to stress-test these tools but straightforward enough that I could iterate quickly.But here's the critical part that too many PMs get wrong when they start using AI for product work: I didn't just throw a single sentence at these tools and expect magic.The “Back of the Napkin” Approach: Why You Still Need to Think“I presume everybody agrees that you should have some formulated thinking before you dump it into the chatbot for your PRD,” I noted early in my experiment. “I suppose in the future maybe you could just do, like, a one-sentence prompt and come out with the perfect PRD because it would just know everything about you and your company in the context, but for now we're gonna do this more, a little old-school AI approach where we're gonna do some original human thinking.”This is crucial. I see so many PMs, especially those newer to the field, treat AI like a magic oracle. They type in “Write me a PRD for a social feature” and then wonder why the output is generic, unfocused, and useless.Your job as a PM isn't to become obsolete. It's to become more effective. And that means doing the strategic thinking work that AI cannot do for you.So I started in Google Docs with what I call a “back of the napkin” PRD structure. Here's what I included:Why: The strategic rationale. In this case: “Want to complement our existing edtech business with a personalized AI tutor, uh, want to maintain position industry, and grow through innovation. on mission for learners.”Target User: Who are we building for? “High school students interested in improving their grades and fundamentals. Fundamental knowledge topics. Specifically science and math. Students who are not in the top ten percent, nor in the bottom ten percent.”This is key—I got specific. Not just “students,” but students in the middle 80%. Not just “any subject,” but science and math. This specificity is what separates useful AI output from garbage.Problem to Solve: What's broken? “Students want better grades. Students are impatient. Students currently use AI just for finding the answers and less to, uh, understand concepts and practice using them.”Key Elements: The feature set and approach.Success Metrics: How we'd measure success.Now, was this a perfectly polished PRD outline? Hell no. As you can see from my transcript, I was literally thinking out loud, making typos, restructuring on the fly. But that's exactly the point. I put in maybe 10-15 minutes of human strategic thinking. That's all it took to create a foundation that would dramatically improve what came out of the AI tools.Round One: Generating the Full PRDWith my back-of-the-napkin outline ready, I copied it into each tool with a simple prompt asking them to expand it into a more complete PRD.ChatGPT: The Reliable GeneralistChatGPT gave me something that was... fine. Competent. Professional. But also deeply uninspiring.The document it produced checked all the boxes. It had the sections you'd expect. The writing was clear. But when I read it, I couldn't shake the feeling that I was reading something that could have been written for literally any product in any company. It felt like “an average of everything out there,” as I noted in my evaluation.Here's what ChatGPT did well: It understood the basic structure of a PRD. It generated appropriate sections. The grammar and formatting were clean. If you needed to hand something in by EOD and had literally no time for refinement, ChatGPT would save you from complete embarrassment.But here's what it lacked: Depth. Nuance. Strategic thinking that felt connected to real product decisions. When it described the target user, it used phrases that could apply to any edtech product. When it outlined success metrics, they were the obvious ones (engagement, retention, test scores) without any interesting thinking about leading indicators or proxy metrics.The problem with generic output isn't that it's wrong, it's that it's invisible. When you're trying to get buy-in from leadership or alignment from engineering, you need your PRD to feel specific, considered, and connected to your company's actual strategy. ChatGPT's output felt like it was written by someone who'd read a lot of PRDs but never actually shipped a product.One specific example: When I asked for success metrics, ChatGPT gave me “Student engagement rate, Time spent on platform, Test score improvement.” These aren't wrong, but they're lazy. They don't show any thinking about what specifically matters for an AI tutor versus any other educational product. Compare that to Claude's output, which got more specific about things like “concept mastery rate” and “question-to-understanding ratio.”Actionable Insight: Use ChatGPT when you need fast, serviceable documentation that doesn't need to be exceptional. Think: internal updates, status reports, routine communications. Don't rely on it for strategic documents where differentiation matters. If you do use ChatGPT for important documents, treat its output as a starting point that needs significant human refinement to add strategic depth and company-specific context.Gemini: Better Than ExpectedGoogle's Gemini actually impressed me more than I anticipated. The structure was solid, and it had a nice balance of detail without being overwhelming.What Gemini got right: The writing had a nice flow to it. The document felt organized and logical. It did a better job than ChatGPT at providing specific examples and thinking through edge cases. For instance, when describing the target user, it went beyond demographics to consider behavioral characteristics and motivations.Gemini also showed some interesting strategic thinking. It considered competitive positioning more thoughtfully than ChatGPT and proposed some differentiation angles that weren't in my original outline. Good AI tools should add insight, not just regurgitate your input with better formatting.But here's where it fell short: the visual elements. When I asked for mockups, Gemini produced images that looked more like stock photos than actual product designs. They weren't terrible, but they weren't compelling either. They had that AI-generated sheen that makes it obvious they came from an image model rather than a designer's brain.For a PRD that you're going to use internally with a team that already understands the context, Gemini's output would work well. The text quality is strong enough, and if you're in the Google ecosystem (Docs, Sheets, Meet, etc.), the integration is seamless. You can paste Gemini's output directly into Google Docs and continue iterating there.But if you need to create something compelling enough to win over skeptics or secure budget, Gemini falls just short. It's good, but not great. It's the solid B+ student: reliably competent but rarely exceptional.Actionable Insight: Gemini is a strong choice if you're working in the Google ecosystem and need good integration with Docs, Sheets, and other Google Workspace tools. The quality is sufficient for most internal documentation needs. It's particularly good if you're working with cross-functional partners who are already in Google Workspace. You can share and collaborate on AI-generated drafts without friction. But don't expect visual mockups that will wow anyone, and plan to add your own strategic polish for high-stakes documents.Grok: Not Ready for Prime TimeLet's just say my expectations were low, and Grok still managed to underdeliver. The PRD felt thin, generic, and lacked the depth you need for real product work.“I don't have high expectations for grok, unfortunately,” I said before testing it. Spoiler alert: my low expectations were validated.Actionable Insight: Skip Grok for product documentation work right now. Maybe it'll improve, but as of my testing, it's simply not competitive with the other options. It felt like 1-2 years behind the others.ChatPRD: The Specialized ToolNow this was interesting. ChatPRD is purpose-built for PRDs, using foundational models underneath but with specific tuning and structure for product documentation.The result? The structure was logical, the depth was appropriate, and it included elements that showed understanding of what actually matters in a PRD. As I reflected: “Cause this one feels like, A human wrote this PRD.”The interface guides you through the process more deliberately than just dumping text into a general chat interface. It asks clarifying questions. It structures the output more thoughtfully.Actionable Insight: If you're a technical lead without a dedicated PM, or you're a PM who wants a more structured approach to using AI for PRDs, ChatPRD is worth the specialized focus. It's particularly good when you need something that feels authentic enough to share with stakeholders without heavy editing.Claude: The Clear WinnerBut the standout performer, and I'm ranking these, was Claude.“I think we know that for now, I'm gonna say Claude did the best job,” I concluded after all the testing. Claude produced the most comprehensive, thoughtful, and strategically sound PRD. But what really set it apart were the concept mocks.When I asked each tool to generate visual mockups of the product, Claude produced HTML prototypes that, while not fully functional, looked genuinely compelling. They had thoughtful UI design, clear information architecture, and felt like something that could actually guide development.“They were, like, closer to, like, what a Lovable would produce or something like that,” I noted, referring to the quality of low-fidelity prototypes that good designers create.The text quality was also superior: more nuanced, better structured, and with more strategic depth. It felt like Claude understood not just what a PRD should contain, but why it should contain those elements.Actionable Insight: For any PRD that matters, meaning anything you'll share with leadership, use to get buy-in, or guide actual product development, you might as well start with Claude. The quality difference is significant enough that it's worth using Claude even if you primarily use another tool for other tasks.Final Rankings: The Definitive HierarchyAfter testing all five tools on multiple dimensions: initial PRD generation, visual mockups, and even crafting a pitch paragraph for a skeptical VP of Engineering, here's my final ranking:* Claude - Best overall quality, most compelling mockups, strongest strategic thinking* ChatPRD - Best for structured PRD creation, feels most “human”* Gemini - Solid all-around performance, good Google integration* ChatGPT - Reliable but generic, lacks differentiation* Grok - Not competitive for this use case“I'd probably say Claude, then chat PRD, then Gemini, then chat GPT, and then Grock,” I concluded.The Deeper Lesson: Garbage In, Garbage Out (Still Applies)But here's what matters more than which tool wins: the realization that hit me partway through this experiment.“I think it really does come down to, like, you know, the quality of the prompt,” I observed. “So if our prompt were a little more detailed, all that were more thought-through, then I'm sure the output would have been better. But as you can see we didn't really put in brain trust prompting here. Just a little bit of, kind of hand-wavy prompting, but a little better than just one or two sentences.”And we still got pretty good results.This is the meta-insight that should change how you approach AI tools in your product work: The quality of your input determines the quality of your output, but the baseline quality of the tool determines the ceiling of what's possible.No amount of great prompting will make Grok produce Claude-level output. But even mediocre prompting with Claude will beat great prompting with lesser tools.So the dual strategy is:* Use the best tool available (currently Claude for PRDs)* Invest in improving your prompting skills ideally with as much original and insightful human, company aware, and context aware thinking as possible.Real-World Workflows: How to Actually Use This in Your Day-to-Day PM WorkTheory is great. Here's how to incorporate these insights into your actual product management workflows.The Weekly Sprint Planning WorkflowEvery PM I know spends hours each week preparing for sprint planning. You need to refine user stories, clarify acceptance criteria, anticipate engineering questions, and align with design and data science. AI can compress this work significantly.Here's an example workflow:Monday morning (30 minutes):* Review upcoming priorities and open your rough notes/outline in Google Docs* Open Claude and paste your outline with this prompt:“I'm preparing for sprint planning. Based on these priorities [paste notes], generate detailed user stories with acceptance criteria. Format each as: User story, Business context, Technical considerations, Acceptance criteria, Dependencies, Open questions.”Monday afternoon (20 minutes):* Review Claude's output critically* Identify gaps, unclear requirements, or missing context* Follow up with targeted prompts:“The user story about authentication is too vague. Break it down into separate stories for: social login, email/password, session management, and password reset. For each, specify security requirements and edge cases.”Tuesday morning (15 minutes):* Generate mockups for any UI-heavy stories:“Create an HTML mockup for the login flow showing: landing page, social login options, email/password form, error states, and success redirect.”* Even if the HTML doesn't work perfectly, it gives your designers a starting pointBefore sprint planning (10 minutes):* Ask Claude to anticipate engineering questions:“Review these user stories as if you're a senior engineer. What questions would you ask? What concerns would you raise about technical feasibility, dependencies, or edge cases?”* This preparation makes you look thoughtful and helps the meeting run smoothlyTotal time investment: ~75 minutes. Typical time saved: 3-4 hours compared to doing this manually.The Stakeholder Alignment WorkflowGetting alignment from multiple stakeholders (product leadership, engineering, design, data science, legal, marketing) is one of the hardest parts of PM work. AI can help you think through different stakeholder perspectives and craft compelling communications for each.Here's how:Step 1: Map your stakeholders (10 minutes)Create a quick table in a doc:Stakeholder | Primary Concern | Decision Criteria | Likely Objections VP Product | Strategic fit, ROI | Company OKRs, market opportunity | Resource allocation vs other priorities VP Eng | Technical risk, capacity | Engineering capacity, tech debt | Complexity, unclear requirements Design Lead | User experience | User research, design principles | Timeline doesn't allow proper design process Legal | Compliance, risk | Regulatory requirements | Data privacy, user consent flowsStep 2: Generate stakeholder-specific communications (20 minutes)For each key stakeholder, ask Claude:“I need to pitch this product idea to [Stakeholder]. Based on this PRD, create a 1-page brief addressing their primary concern of [concern from your table]. Open with the specific value for them, address their likely objection of [objection], and close with a clear ask. Tone should be [professional/technical/strategic] based on their role.”Then you'll have customized one-pagers for your pre-meetings with each stakeholder, dramatically increasing your alignment rate.Step 3: Synthesize feedback (15 minutes)After gathering stakeholder input, ask Claude to help you synthesize:“I got the following feedback from stakeholders: [paste feedback]. Identify: (1) Common themes, (2) Conflicting requirements, (3) Legitimate concerns vs organizational politics, (4) Recommended compromises that might satisfy multiple parties.”This pattern-matching across stakeholder feedback is something AI does really well and saves you hours of mental processing.The Quarterly Planning WorkflowQuarterly or annual planning is where product strategy gets real. You need to synthesize market trends, customer feedback, technical capabilities, and business objectives into a coherent roadmap. AI can accelerate this dramatically.Six weeks before planning:* Start collecting input (customer interviews, market research, competitive analysis, engineering feedback)* Don't wait until the last minuteFour weeks before planning:Dump everything into Claude with this structure:“I'm creating our Q2 roadmap. Context:* Business objectives: [paste from leadership]* Customer feedback themes: [paste synthesis]* Technical capabilities/constraints: [paste from engineering]* Competitive landscape: [paste analysis]* Current product gaps: [paste from your analysis]Generate 5 strategic themes that could anchor our Q2 roadmap. For each theme:* Strategic rationale (how it connects to business objectives)* Key initiatives (2-3 major features/projects)* Success metrics* Resource requirements (rough estimate)* Risks and mitigations* Customer segments addressed”This gives you a strategic framework to react to rather than starting from a blank page.Three weeks before planning:Iterate on the most promising themes:“Deep dive on Theme 3. Generate:* Detailed initiative breakdown* Dependencies on platform/infrastructure* Phasing options (MVP vs full build)* Go-to-market considerations* Data requirements* Open questions requiring research”Two weeks before planning:Pressure-test your thinking:“Play devil's advocate on this roadmap. What are the strongest arguments against each initiative? What am I likely missing? What failure modes should I plan for?”This adversarial prompting forces you to strengthen weak points before your leadership reviews it.One week before planning:Generate your presentation:“Create an executive presentation for this roadmap. Structure: (1) Market context and strategic imperative, (2) Q2 themes and initiatives, (3) Expected outcomes and metrics, (4) Resource requirements, (5) Key risks and mitigations, (6) Success criteria for decision. Make it compelling but data-driven. Tone: confident but not overselling.”Then add your company-specific context, visual brand, and personal voice.The Customer Research WorkflowAI can't replace talking to customers, but it can help you prepare better questions, analyze feedback more systematically, and identify patterns faster.Before customer interviews:“I'm interviewing customers about [topic]. Generate:* 10 open-ended questions that avoid leading the witness* 5 follow-up questions for each main question* Common cognitive biases I should watch for* A framework for categorizing responses”This prep work helps you conduct better interviews.After interviews:“I conducted 15 customer interviews. Here are the key quotes: [paste anonymized quotes]. Identify:* Recurring themes and patterns* Surprising insights that contradict our assumptions* Segments with different needs* Implied needs customers didn't articulate directly* Recommended next steps for validation”AI is excellent at pattern-matching across qualitative data at scale.The Crisis Management WorkflowSomething broke. The site is down. Data was lost. A feature shipped with a critical bug. You need to move fast.Immediate response (5 minutes):“Critical incident. Details: [brief description]. Generate:* Incident classification (Sev 1-4)* Immediate stakeholders to notify* Draft customer communication (honest, apologetic, specific about what happened and what we're doing)* Draft internal communication for leadership* Key questions to ask engineering during investigation”Having these drafted in 5 minutes lets you focus on coordination and decision-making rather than wordsmithing.Post-incident (30 minutes):“Write a post-mortem based on this incident timeline: [paste timeline]. Include:* What happened (technical details)* Root cause analysis* Impact quantification (users affected, revenue impact, time to resolution)* What went well in our response* What could have been better* Specific action items with owners and deadlines* Process changes to prevent recurrence Tone: Blameless, focused on learning and improvement.”This gives you a strong first draft to refine with your team.Common Pitfalls: What Not to Do with AI in Product ManagementNow let's talk about the mistakes I see PMs making with AI tools. Pitfall #1: Treating AI Output as FinalThe biggest mistake is copy-pasting AI output directly into your PRD, roadmap presentation, or stakeholder email without critical review.The result? Documents that are grammatically perfect but strategically shallow. Presentations that sound impressive but don't hold up under questioning. Emails that are professionally worded but miss the subtext of organizational politics.The fix: Always ask yourself:* Does this reflect my actual strategic thinking, or generic best practices?* Would my CEO/engineering lead/biggest customer find this compelling and specific?* Are there company-specific details, customer insights, or technical constraints that only I know?* Does this sound like me, or like a robot?Add those elements. That's where your value as a PM comes through.Pitfall #2: Using AI as a Crutch Instead of a ToolSome PMs use AI because they don't want to think deeply about the product. They're looking for AI to do the hard work of strategy, prioritization, and trade-off analysis.This never works. AI can help you think more systematically, but it can't replace thinking.If you find yourself using AI to avoid wrestling with hard questions (”Should we build X or Y?” “What's our actual competitive advantage?” “Why would customers switch from the incumbent?”), you're using it wrong.The fix: Use AI to explore options, not to make decisions. Generate three alternatives, pressure-test each one, then use your judgment to decide. The AI can help you think through implications, but you're still the one choosing.Pitfall #3: Not IteratingGetting mediocre AI output and just accepting it is a waste of the technology's potential.The PMs who get exceptional results from AI are the ones who iterate. They generate an initial response, identify what's weak or missing, and ask follow-up questions. They might go through 5-10 iterations on a key section of a PRD.Each iteration is quick (30 seconds to type a follow-up prompt, 30 seconds to read the response), but the cumulative effect is dramatically better output.The fix: Budget time for iteration. Don't try to generate a complete, polished PRD in one prompt. Instead, generate a rough draft, then spend 30 minutes iterating on specific sections that matter most.Pitfall #4: Ignoring the Political and Human ContextAI tools have no understanding of organizational politics, interpersonal relationships, or the specific humans you're working with.They don't know that your VP of Engineering is burned out and skeptical of any new initiatives. They don't know that your CEO has a personal obsession with a specific competitor. They don't know that your lead designer is sensitive about not being included early enough in the process.If you use AI-generated communications without layering in this human context, you'll create perfectly worded documents that land badly because they miss the subtext.The fix: After generating AI content, explicitly ask yourself: “What human context am I missing? What relationships do I need to consider? What political dynamics are in play?” Then modify the AI output accordingly.Pitfall #5: Over-Relying on a Single ToolDifferent AI tools have different strengths. Claude is great for strategic depth, ChatPRD is great for structure, Gemini integrates well with Google Workspace.If you only ever use one tool, you're missing opportunities to leverage different strengths for different tasks.The fix: Keep 2-3 tools in your toolkit. Use Claude for important PRDs and strategic documents. Use Gemini for quick internal documentation that needs to integrate with Google Docs. Use ChatPRD when you want more guided structure. Match the tool to the task.Pitfall #6: Not Fact-Checking AI OutputAI tools hallucinate. They make up statistics, misrepresent competitors, and confidently state things that aren't true. If you include those hallucinations in a PRD that goes to leadership, you look incompetent.The fix: Fact-check everything, especially:* Statistics and market data* Competitive feature claims* Technical capabilities and limitations* Regulatory and compliance requirementsIf the AI cites a number or makes a factual claim, verify it independently before including it in your document.The Meta-Skill: Prompt Engineering for PMsLet's zoom out and talk about the underlying skill that makes all of this work: prompt engineering.This is a real skill. The difference between a mediocre prompt and a great prompt can be 10x difference in output quality. And unlike coding or design, where there's a steep learning curve, prompt engineering is something you can get good at quickly.Principle 1: Provide Context Before InstructionsBad prompt:“Write a PRD for an AI tutor”Good prompt:“I'm a PM at an edtech company with 2M users, primarily high school students. We're exploring an AI tutor feature to complement our existing video content library and practice problems. Our main competitors are Khan Academy and Course Hero. Our differentiation is personalized learning paths based on student performance data.Write a PRD for an AI tutor feature targeting students in the middle 80% academically who struggle with science and math.”The second prompt gives Claude the context it needs to generate something specific and strategic rather than generic.Principle 2: Specify Format and ConstraintsBad prompt:“Generate success metrics”Good prompt:“Generate 5-7 success metrics for this feature. Include a mix of:* Leading indicators (early signals of success)* Lagging indicators (definitive success measures)* User behavior metrics* Business impact metricsFor each metric, specify: name, definition, target value, measurement method, and why it matters.”The structure you provide shapes the structure you get back.Principle 3: Ask for Multiple OptionsBad prompt:“What should our Q2 priorities be?”Good prompt:“Generate 3 different strategic approaches for Q2:* Option A: Focus on user acquisition* Option B: Focus on engagement and retention* Option C: Focus on monetizationFor each option, detail: key initiatives, expected outcomes, resource requirements, risks, and recommendation for or against.”Asking for multiple options forces the AI (and forces you) to think through trade-offs systematically.Principle 4: Specify Audience and ToneBad prompt:“Summarize this PRD”Good prompt:“Create a 1-paragraph summary of this PRD for our skeptical VP of Engineering. Tone: Technical, concise, addresses engineering concerns upfront. Focus on: technical architecture, resource requirements, risks, and expected engineering effort. Avoid marketing language.”The audience and tone specification ensures the output will actually work for your intended use.Principle 5: Use Iterative RefinementDon't try to get perfect output in one prompt. Instead:First prompt: Generate rough draft Second prompt: “This is too generic. Add specific examples from [our company context].” Third prompt: “The technical section is weak. Expand with architecture details and dependencies.” Fourth prompt: “Good. Now make it 30% more concise while keeping the key details.”Each iteration improves the output incrementally.Let me break down the prompting approach that worked in this experiment, because this is immediately actionable for your work tomorrow.Strategy 1: The Structured Outline ApproachDon't go from zero to full PRD in one prompt. Instead:* Start with strategic thinking - Spend 10-15 minutes outlining why you're building this, who it's for, and what problem it solves* Get specific - Don't say “users,” say “high school students in the middle 80% of academic performance”* Include constraints - Budget, timeline, technical limitations, competitive landscape* Dump your outline into the AI - Now ask it to expand into a full PRD* Iterate section by section - Don't try to perfect everything at onceThis is exactly what I did in my experiment, and even with my somewhat sloppy outline, the results were dramatically better than they would have been with a single-sentence prompt.Strategy 2: The Comparative Analysis PatternOne technique I used that worked particularly well: asking each tool to do the same specific task and comparing results.For example, I asked all five tools: “Please compose a one paragraph exact summary I can share over DM with a highly influential VP of engineering who is generally a skeptic but super smart.”This forced each tool to synthesize the entire PRD into a compelling pitch while accounting for a specific, challenging audience. The variation in quality was revealing—and it gave me multiple options to choose from or blend together.Actionable tip: When you need something critical (a pitch, an executive summary, a key decision framework), generate it with 2-3 different AI tools and take the best elements from each. This “ensemble approach” often produces better results than any single tool.Strategy 3: The Iterative Refinement LoopDon't treat the AI output as final. Use it as a first draft that you then refine through conversation with the AI.After getting the initial PRD, I could have asked follow-up questions like:* “What's missing from this PRD?”* “How would you strengthen the success metrics section?”* “Generate 3 alternative approaches to the core feature set”Each iteration improves the output and, more importantly, forces me to think more deeply about the product.What This Means for Your CareerIf you're an early or mid-career PM reading this, you might be thinking: “Great, so AI can write PRDs now. Am I becoming obsolete?”Absolutely not. But your role is evolving, and understanding that evolution is critical.The PMs who will thrive in the AI era are those who:* Excel at strategic thinking - AI can generate options, but you need to know which options align with company strategy, customer needs, and technical feasibility* Master the art of prompting - This is a genuine skill that separates mediocre AI users from exceptional ones* Know when to use AI and when not to - Some aspects of product work benefit enormously from AI. Others (user interviews, stakeholder negotiation, cross-functional relationship building) require human judgment and empathy* Can evaluate AI output critically - You need to spot the hallucinations, the generic fluff, and the strategic misalignments that AI inevitably producesThink of AI tools as incredibly capable interns. They can produce impressive work quickly, but they need direction, oversight, and strategic guidance. Your job is to provide that guidance while leveraging their speed and breadth.The Real-World Application: What to Do Monday MorningLet's get tactical. Here's exactly how to apply these insights to your actual product work:For Your Next PRD:* Block 30 minutes for strategic thinking - Write your back-of-the-napkin outline in Google Docs or your tool of choice* Open Claude (or ChatPRD if you want more structure)* Copy your outline with this prompt:“I'm a product manager at [company] working on [product area]. I need to create a comprehensive PRD based on this outline. Please expand this into a complete PRD with the following sections: [list your preferred sections]. Make it detailed enough for engineering to start breaking down into user stories, but concise enough for leadership to read in 15 minutes. [Paste your outline]”* Review the output critically - Look for generic statements, missing details, or strategic misalignments* Iterate on specific sections:“The success metrics section is too vague. Please provide 3-5 specific, measurable KPIs with target values and explanation of why these metrics matter.”* Generate supporting materials:“Create a visual mockup of the core user flow showing the key interaction points.”* Synthesize the best elements - Don't just copy-paste the AI output. Use it as raw material that you shape into your final documentFor Stakeholder Communication:When you need to pitch something to leadership or engineering:* Generate 3 versions of your pitch using different tools (Claude, ChatPRD, and one other)* Compare them for:* Clarity and conciseness* Strategic framing* Compelling value proposition* Addressing likely objections* Blend the best elements into your final version* Add your personal voice - This is crucial. AI output often lacks personality and specific company context. Add that yourself.For Feature Prioritization:AI tools can help you think through trade-offs more systematically:“I'm deciding between three features for our next release: [Feature A], [Feature B], and [Feature C]. For each feature, analyze: (1) Estimated engineering effort, (2) Expected user impact, (3) Strategic alignment with making our platform the go-to solution for [your market], (4) Risk factors. Then recommend a prioritization with rationale.”This doesn't replace your judgment, but it forces you to think through each dimension systematically and often surfaces considerations you hadn't thought of.The Uncomfortable Truth About AI and Product ManagementLet me be direct about something that makes many PMs uncomfortable: AI will make some PM skills less valuable while making others more valuable.Less valuable:* Writing boilerplate documentation* Creating standard frameworks and templates* Generating routine status updates* Synthesizing information from existing sourcesMore valuable:* Strategic product vision and roadmapping* Deep customer empathy and insight generation* Cross-functional leadership and influence* Critical evaluation of options and trade-offs* Creative problem-solving for novel situationsIf your PM role primarily involves the first category of tasks, you should be concerned. But if you're focused on the second category while leveraging AI for the first, you're going to be exponentially more effective than your peers who resist these tools.The PMs I see succeeding aren't those who can write the best PRD manually. They're those who can write the best PRD with AI assistance in one-tenth the time, then use the saved time to talk to more customers, think more deeply about strategy, and build stronger cross-functional relationships.Advanced Techniques: Beyond Basic PRD GenerationOnce you've mastered the basics, here are some advanced applications I've found valuable:Competitive Analysis at Scale“Research our top 5 competitors in [market]. For each one, analyze: their core value proposition, key features, pricing strategy, target customer, and likely product roadmap based on recent releases and job postings. Create a comparison matrix showing where we have advantages and gaps.”Then use web search tools in Claude or Perplexity to fact-check and expand the analysis.Scenario Planning“We're considering three strategic directions for our product: [Direction A], [Direction B], [Direction C]. For each direction, map out: likely customer adoption curve, required technical investments, competitive positioning in 12 months, and potential pivots if the hypothesis proves wrong. Then identify the highest-risk assumptions we should test first for each direction.”This kind of structured scenario thinking is exactly what AI excels at—generating multiple well-reasoned perspectives quickly.User Story GenerationAfter your PRD is solid:“Based on this PRD, generate a complete set of user stories following the format ‘As a [user type], I want to [action] so that [benefit].' Include acceptance criteria for each story. Organize them into epics by functional area.”This can save your engineering team hours of grooming meetings.The Tools Will Keep Evolving. Your Process Shouldn'tHere's something important to remember: by the time you read this, the specific rankings might have shifted. Maybe ChatGPT-5 has leapfrogged Claude. Maybe a new specialized tool has emerged.But the core principles won't change:* Do strategic thinking before touching AI* Use the best tool available for your specific task* Iterate and refine rather than accepting first outputs* Blend AI capabilities with human judgment* Focus your time on the uniquely human aspects of product managementThe specific tools matter less than your process for using them effectively.A Final Experiment: The Skeptical VP TestI want to share one more insight from my testing that I think is particularly relevant for early and mid-career PMs.Toward the end of my experiment, I gave each tool this prompt: “Please compose a one paragraph exact summary I can share over DM with a highly influential VP of engineering who is generally a skeptic but super smart.”This is such a realistic scenario. How many times have you needed to pitch an idea to a skeptical technical leader via Slack or email? Someone who's brilliant, who's seen a thousand product ideas fail, and who can spot b******t from a mile away?The quality variation in the responses was fascinating. ChatGPT gave me something that felt generic and safe. Gemini was better but still a bit too enthusiastic. Grok was... well, Grok.But Claude and ChatPRD both produced messages that felt authentic, technically credible, and appropriately confident without being overselling. They acknowledged the engineering challenges while framing the opportunity compellingly.The lesson: When the stakes are high and the audience is sophisticated, the quality of your AI tool matters even more. That skeptical VP can tell the difference between a carefully crafted message and AI-generated fluff. So can your CEO. So can your biggest customers.Use the best tools available, but more importantly, always add your own strategic thinking and authentic voice on top.Questions to Consider: A Framework for Your Own ExperimentsAs I wrapped up my Loom, I posed some questions to the audience that I'll pose to you:“Let me know in the comments, if you do your PRDs using AI differently, do you start with back of the envelope? Do you say, oh no, I just start with one sentence, and then I let the chatbot refine it with me? Or do you go way more detailed and then use the chatbot to kind of pressure test it?”These aren't rhetorical questions. Your answer reveals your approach to AI-augmented product work, and different approaches work for different people and contexts.For early-career PMs: I'd recommend starting with more detailed outlines. The discipline of thinking through your product strategy before touching AI will make you a stronger PM. You can always compress that process later as you get more experienced.For mid-career PMs: Experiment with different approaches for different types of documents. Maybe you do detailed outlines for major feature PRDs but use more iterative AI-assisted refinement for smaller features or updates. Find what optimizes your personal productivity while maintaining quality.For senior PMs and product leaders: Consider how AI changes what you should expect from your PM team. Should you be reviewing more AI-generated first drafts and spending more time on strategic guidance? Should you be training your team on effective AI usage? These are leadership questions worth grappling with.The Path Forward: Continuous ExperimentationMy experiment with these five AI tools took 45 minutes. But I'm not done experimenting.The field of AI-assisted product management is evolving rapidly. New tools launch monthly. Existing tools get smarter weekly. Prompting techniques that work today might be obsolete in three months.Your job, if you want to stay at the forefront of product management, is to continuously experiment. Try new tools. Share what works with your peers. Build a personal knowledge base of effective prompts and workflows. And be generous with what you learn. The PM community gets stronger when we share insights rather than hoarding them.That's why I created this Loom and why I'm writing this post. Not because I have all the answers, but because I'm figuring it out in real-time and want to share the journey.A Personal Note on Coaching and ConsultingIf this kind of practical advice resonates with you, I'm happy to work with you directly.Through my pm coaching practice, I offer 1:1 executive, career, and product coaching for PMs and product leaders. We can dig into your specific challenges: whether that's leveling up your AI workflows, navigating a career transition, or developing your strategic product thinking.I also work with companies (usually startups or incubation teams) on product strategy, helping teams figure out PMF for new explorations and improving their product management function.The format is flexible. Some clients want ongoing coaching, others prefer project-based consulting, and some just want a strategic sounding board for a specific decision. Whatever works for you.Reach out through tomleungcoaching.com if you're interested in working together.OK. Enough pontificating. Let's ship greatness. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

Every few years, the world of product management goes through a phase shift. When I started at Microsoft in the early 2000s, we shipped Office in boxes. Product cycles were long, engineering was expensive, and user research moved at the speed of snail mail. Fast forward a decade and the cloud era reset the speed at which we build, measure, and learn. Then mobile reshaped everything we thought we knew about attention, engagement, and distribution.Now we are standing at the edge of another shift. Not a small shift, but a tectonic one. Artificial intelligence is rewriting the rules of product creation, product discovery, product expectations, and product careers.To help make sense of this moment, I hosted a panel of world class product leaders on the Fireside PM podcast:• Rami Abu-Zahra, Amazon product leader across Kindle, Books, and Prime Video• Todd Beaupre, Product Director at YouTube leading Home and Recommendations• Joe Corkery, CEO and cofounder of Jaide Health • Tom Leung (me), Partner at Palo Alto Foundry• Lauren Nagel, VP Product at Mezmo• David Nydegger, Chief Product Officer at OvivaThese are leaders running massive consumer platforms, high stakes health tech, and fast moving developer tools. The conversation was rich, honest, and filled with specific examples. This post summarizes the discussion, adds my own reflections, and offers a practical guide for early and mid career PMs who want to stay relevant in a world where AI is redefining what great product management looks like.Table of Contents* What AI Cannot Do and Why PM Judgment Still Matters* The New AI Literacy: What PMs Must Know by 2026* Why Building AI Products Speeds Up Some Cycles and Slows Down Others* Whether the PM, Eng, UX Trifecta Still Stands* The Biggest Risks AI Introduces Into Product Development* Actionable Advice for Early and Mid Career PMs* My Takeaways and What Really Matters Going Forward* Closing Thoughts and Coaching Practice1. What AI Cannot Do and Why PM Judgment Still MattersWe opened the panel with a foundational question. As AI becomes more capable every quarter, what is left for humans to do. Where do PMs still add irreplaceable value. It is the question every PM secretly wonders.Todd put it simply: “At the end of the day, you have to make some judgment calls. We are not going to turn that over anytime soon.”This theme came up again and again. AI is phenomenal at synthesizing, drafting, exploring, and narrowing. But it does not have conviction. It does not have lived experience. It does not feel user pain. It does not carry responsibility.Joe from Jaide Health captured it perfectly when he said: “AI cannot feel the pain your users have. It can help meet their goals, but it will not get you that deep understanding.”There is still no replacement for sitting with a frustrated healthcare customer who cannot get their clinical data into your system, or a creator on YouTube who feels the algorithm is punishing their art, or a devops engineer staring at an RCA output that feels 20 percent off.Every PM knows this feeling: the moment when all signals point one way, but your gut tells you the data is incomplete or misleading. This is the craft that AI does not have.Why judgment becomes even more important in an AI worldDavid, who runs product at a regulated health company, said something incredibly important: “Knowing what great looks like becomes more essential, not less. The PM's that thrive in AI are the ones with great product sense.”This is counterintuitive for many. But when the operational work becomes automated, the differentiation shifts toward taste, intuition, sequencing, and prioritization.Lauren asked the million dollar question. “How are we going to train junior PMs if AI is doing the legwork. Who teaches them how to think.”This is a profound point. If AI closes the gap between junior and senior PMs in execution tasks, the difference will emerge almost entirely in judgment. Knowing how to probe user problems. Knowing when a feature is good enough. Knowing which tradeoffs matter. Knowing which flaw is fatal and which is cosmetic.AI is incredible at writing a PRD. AI is terrible at knowing whether the PRD is any good.Which means the future PM becomes more strategic, more intuitive, more customer obsessed, and more willing to make thoughtful bets under uncertainty.2. The New AI Literacy: What PMs Must Know by 2026I asked the panel what AI literacy actually means for PMs. Not the hype. Not the buzzwords. The real work.Instead of giving gimmicky answers, the discussion converged on a clear set of skills that PMs must master.Skill 1: Understanding context engineeringDavid laid this out clearly: “Knowing what LMS are good at and what they are not good at, and knowing how to give them the right context, has become a foundational PM skill.”Most PMs think prompt engineering is about clever phrasing. In reality, the future is about context engineering. Feeding models the right data. Choosing the right constraints. Deciding what to ignore. Curating inputs that shape outputs in reliable ways.Context engineering is to AI product development what Figma was to collaborative design. If you cannot do it, you are not going to be effective.Skill 2: Evals, evals, evalsRami said something that resonated with the entire panel: “Last year was all about prompts. This year is all about evals.”He is right.• How do you build a golden dataset.• How do you evaluate accuracy.• How do you detect drift.• How do you measure hallucination rates.• How do you combine UX evals with model evals.• How do you decide what good looks like.• How do you define safe versus unsafe boundaries.AI evaluation is now a core PM responsibility. Not exclusively. But PMs must understand what engineers are testing for, what failure modes exist, and how to design test sets that reflect the real world.Lauren said her PMs write evals side by side with engineering. That is where the world is going.Skill 3: Knowing when to trust AI output and when to override itTodd noted: “It is one thing to get an answer that sounds good. It is another thing to know if it is actually good.”This is the heart of the role. AI can produce strategic recommendations that look polished, structured, and wise. But the real question is whether they are grounded in reality, aligned with your constraints, and consistent with your product vision.A PM without the ability to tell real insight from confident nonsense will be replaced by someone who can.Skill 4: Understanding the physics of model changesThis one surprised many people, but it was a recurring point.Rami noted: “When you upgrade a model, the outputs can be totally different. The evals start failing. The experience shifts.”PMs must understand:• Models get deprecated• Models drift• Model updates can break well tuned prompts• API pricing has real COGS implications• Latency varies• Context windows vary• Some tasks need agents, some need RAG, some need a small finetuned modelThis is product work now. The PM of 2026 must know these constraints as well as a PM of the cloud era understood database limits or API rate limits.Skill 5: How to construct AI powered prototypes in hours, not weeksIt now takes one afternoon to build something meaningful. Zero code required. Prompt, test, refine. Whether you use Replit, Cursor, Vercel, or sandboxed agents, the speed is shocking.But this makes taste and problem selection even more important. The future PM must be able to quickly validate whether a concept is worth building beyond the demo stage.3. Why Building AI Products Speeds Up Some Cycles and Slows Down OthersThis part of the conversation was fascinating because people expected AI to accelerate everything. The panel had a very different view.Fast: Prototyping and concept validationLauren described how her teams can build working versions of an AI powered Root Cause Analysis feature in days, test it with customers, and get directional feedback immediately.“You can think bigger because the cost of trying things is much lower,” she said.For founders, early PMs, and anyone validating hypotheses, this is liberating. You can test ten ideas in a week. That used to take a quarter.Slow: Productionizing AI featuresThe surprising part is that shipping the V1 of an AI feature is slower than most expect.Joe noted: “You can get prototypes instantly. But turning that into a real product that works reliably is still hard.”Why. Because:• You need evals.• You need monitoring.• You need guardrails.• You need safety reviews.• You need deterministic parts of the workflow.• You need to manage COGS.• You need to design fallbacks.• You need to handle unpredictable inputs.• You need to think about hallucination risk.• You need new UI surfaces for non deterministic outputs.Lauren said bluntly: “Vibe coding is fast. Moving that vibe code to production is still a four month process.”This should be printed on a poster in every AI startup office.Very Slow: Iterating on AI powered featuresAnother counterintuitive point. Many teams ship a great V1 but struggle to improve it significantly afterward.David said their nutrition AI feature launched well but: “We struggled really hard to make it better. Each iteration was easy to try but difficult to improve in a meaningful way.”Why is iteration so difficult.Because model improvements may not translate directly into UX improvements. Users need consistency. Drift creates churn. Small changes in context or prompts can cause large changes in behavior.Teams are learning a hard truth: AI powered features do not behave like typical deterministic product flows. They require new iteration muscles that most orgs do not yet have.4. The PM, Eng, UX Trifecta in the AI EraI asked whether the classic PM, Eng, UX triad is still the right model. The audience was expecting disagreement. The panel was surprisingly aligned.The trifecta is not going anywhereRami put it simply: “We still need experts in all three domains to raise the bar.”Joe added: “AI makes it possible for PMs to do more technical work. But it does not replace engineering. Same for design.”AI blurs the edges of the roles, but it does not collapse them. In fact, each role becomes more valuable because the work becomes more abstract.• PMs focus on judgment, sequencing, evaluation, and customer centric problem framing• Engineers focus on agents, systems, architecture, guardrails, latency, and reliability• Designers focus on dynamic UX, non deterministic UX patterns, and new affordances for AI outputsWhat does changeAI makes the PM-Eng relationship more intense. The backbone of AI features is a combination of model orchestration, evaluation, prompting, and context curation. PMs must be tighter than ever with engineering to design these systems.David noted that his teams focus more on individual talents. Some PMs are great at context engineering. Some designers excel at polishing AI generated layouts. Some engineers are brilliant at prompt chaining. AI reveals strengths quickly.The trifecta remains. The skill distribution within it evolves.5. The Biggest Risks AI Introduces Into Product DevelopmentWhen we asked what scares PMs most about AI, the conversation became blunt and honest. Risk 1: Loss of user trustLauren warned: “If people keep shipping low quality AI features, user trust in AI erodes. And then your good AI product suffers from the skepticism.”This is very real. Many early AI features across industries are low quality, gimmicky, or unreliable. Users quickly learn to distrust these experiences.Which means PMs must resist the pressure to ship before the feature is ready.Risk 2: Skill atrophyTodd shared a story that hit home for many PMs. “Junior folks just want to plug in the prompt and take whatever the AI gives them. That is a recipe for having no job later.”PMs who outsource their thinking to AI will lose their judgment. Judgment cannot be regained easily.This is the silent career killer.Risk 3: Safety hazards in sensitive domainsDavid was direct: “If we have one unsafe output, we have to shut the feature off. We cannot afford even small mistakes.”In healthcare, finance, education, and legal industries, the tolerance for error is near zero. AI must be monitored relentlessly. Human in the loop systems are mandatory. The cycles are slower but the stakes are higher.Risk 4: The high bar for AI compared to humansJoe said something I have thought about for years: “AI is held to a much higher standard than human decision making. Humans make mistakes constantly, but we forgive them. AI makes one mistake and it is unacceptable.”This slows adoption in certain industries and creates unrealistic expectations.Risk 5: Model deprecation and instabilityRami described a real problem AI PMs face: “Models get deprecated faster than they get replaced. The next model is not always GA. Outputs change. Prompts break.”This creates product instability that PMs must anticipate and design around.Risk 6: Differentiation becomes hardI shared this perspective because I see so many early stage startups struggle with it.If your whole product is a wrapper around an LLM, competitors will copy you in a week. The real differentiation will not come from using AI. It will come from how deeply you understand the customer, how you integrate AI with proprietary data, and how you create durable workflows.6. Actionable Advice for Early and Mid Career PMsThis was one of my favorite parts of the panel because the advice was humble, practical, and immediately useful.A. Develop deep user empathy. This will become your biggest differentiator.Lauren said it clearly: “Maintain your empathy. Understand the pain your user really has.”AI makes execution cheap. It makes insight valuable.If you can articulate user pain precisely.If you can differentiate surface friction from underlying need.If you can see around corners.If you can prototype solutions and test them in hours.If you can connect dots between what AI can do and what users need.You will thrive.Tactical steps:• Sit in on customer support calls every week.• Watch 10 user sessions for every feature you own.• Talk to customers until patterns emerge.• Ask “why” five times in every conversation.• Maintain a user pain log and update it constantly.B. Become great at context engineeringThis will matter as much as SQL mattered ten years ago.Action steps:• Practice writing prompts with structured context blocks.• Build a library of prompts that work for your product.• Study how adding, removing, or reordering context changes output.• Learn RAG patterns.• Learn when structured data beats embeddings.• Learn when smaller local models outperform big ones.C. Learn eval frameworksThis is non negotiable.You need to know:• Precision vs recall tradeoffs• How to build golden datasets• How to design scenario based evals for UX• How to test for hallucination• How to monitor drift• How to set quality thresholds• How to build dashboards that reflect real world input distributionsYou do not need to write the code.You do need to define the eval strategy.D. Strengthen your product senseYou cannot outsource product taste.Todd said it best: “Imagine asking AI to generate 20 percent growth for you. It will not tell you what great looks like.”To strengthen your product sense:• Review the best products weekly.• Take screenshots of great UX patterns.• Map user flows from apps you admire.• Break products down into primitives.• Ask yourself why a product decision works.• Predict what great would look like before you design it.The PMs who thrive will be the ones who can recognize magic when they see it.E. Stay curiousRami's closing advice was simple and perfect: “Stay curious. Keep learning. It never gets old.”AI changes monthly. The PM who is excited by new ideas will outperform the PM who clings to old patterns.Practical habits:• Read one AI research paper summary each week.• Follow evaluation and model updates from major vendors.• Build at least one small AI prototype a month.• Join AI PM communities.• Teach juniors what you learn. Nothing accelerates mastery faster.F. Embrace velocity and side projectsTodd said that some of his biggest career breakthroughs came from solving problems on the side.This is more true now than ever.If you have an idea, you can build an MVP over a weekend. If it solves a real problem, someone will notice.G. Stay close to engineeringNot because you need to code, but because AI features require tighter PM engineering collaboration.Learn enough to be dangerous:• How embeddings work• How vector stores behave• What latency tradeoffs exist• How agents chain tasks• How model versioning works• How context limits shape UX• Why some prompts blow up API costsIf you can speak this language, you will earn trust and accelerate cycles.H. Understand the business deeplyJoe's advice was timeless: “Know who pays you and how much they pay. Solve real problems and know the business model.”PMs who understand unit economics, COGS, pricing, and funnel dynamics will stand out.7. Tom's Takeaways and What Really Matters Going ForwardI ended the recording by sharing what I personally believe after moderating this discussion and working closely with a variety of AI teams over the past 2 years.Judgment becomes the most valuable PM skillAs AI gets better at analysis, synthesis, and execution, your value shifts to:• Choosing the right problem• Sequencing decisions• Making 55 45 calls• Understanding user pain• Making tradeoffs• Deciding when good is good enough• Defining success• Communicating vision• Influencing the orgAgents can write specs.LLMs can produce strategies.But only humans can choose the right one and commit.Learning speed becomes a competitive advantageI said this on the panel and I believe it more every month.Because of AI, you now have:• Infinite coaches• Infinite mentors• Infinite experts• Infinite documentation• Infinite learning loopsA PM who learns slowly will not survive the next decade. Curiosity, empathy, and velocity will separate great from goodMany panelists said versions of this. The common pattern was:• Understand users deeply• Combine multiple tools creatively• Move quickly• Learn constantlyThe future rewards generalists with taste, speed, and emotional intelligence.Differentiation requires going beyond wrapper appsThis is one of my biggest concerns for early stage founders. If your entire product is a wrapper around a model, you are vulnerable.Durable value will come from:• Proprietary data• Proprietary workflows• Deep domain insight• Organizational trust• Distribution advantage• Safety and reliability• Integration with existing systemsAI is a component, not a moat.8. Closing ThoughtsHosting this panel made me more optimistic about the future of product management. Not because AI will not change the job. It already has. But because the fundamental craft remains alive.Product management has always been about understanding people, making decisions with incomplete information, telling compelling stories, and guiding teams through ambiguity and being right often.AI accelerates the craft. It amplifies the best PMs and exposes the weak ones. It rewards curiosity, empathy, velocity, and judgment.If you want tailored support on your PM career, leadership journey, or executive path, I offer 1 on 1 career, executive, and product coaching at tomleungcoaching.com.OK team. Let's ship greatness. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

The Interview That Sparked This EssayJoe Corkery and I worked together at Google years ago, and he has since gone on to build a venture-backed company tackling a real and systemic problem in healthcare communication. This essay is my attempt to synthesize that conversation. It is written for early and mid career PMs in Silicon Valley who want to get sharper at product judgment, market discovery, customer validation, and knowing the difference between encouragement and signal. If you feel like you have ever shipped something, presented it to customers, and then heard polite nodding instead of movement and urgency, this is for you.Joe's Unusual Career ArcJoe's background is not typical for a founder. He is a software engineer. And a physician. And someone who has led business development in the pharmaceutical industry. That multidisciplinary profile allowed him to see something that many insiders miss: healthcare is full of problems that everyone acknowledges, yet very few organizations are structurally capable of solving.When Joe joined Google Cloud in 2014, he helped start the healthcare and life sciences product org. Yet the timing was difficult. As he put it:“The world wasn't ready or Google wasn't ready to do healthcare.” So instead of building healthcare products right away, he spent two years working on security, compliance, and privacy. That detour will matter later, because it set the foundation for everything he is now doing at Jaide.Years later, he left Google to build a healthcare company focused initially on guided healthcare search, particularly for women's health. The idea resonated emotionally. Every customer interview validated the need. Investors said it was important. Healthcare organizations nodded enthusiastically.And yet, there was no traction.This created a familiar and emotionally challenging founder dilemma:* When everyone is encouraging you* But no one will pay you or adopt early* How do you know if you are early, unlucky, or wrong?This is the question at the heart of product strategy.False Positives: Why Encouragement Is Not FeedbackIf you have worked as a PM or founder for more than a few weeks, you have encountered positive feedback that turned out to be meaningless. People love your idea. Executives praise your clarity. Customers tell you they would definitely use it. Friends offer supportive high-fives.But then nothing moves.As Joe put it:“Everyone wanted to be supportive. But that makes it hard to know whether you're actually on the right path.” This is not because people are dishonest. It is because people are kind, polite, and socially conditioned to encourage enthusiasm. In Silicon Valley especially, we celebrate ambition. We praise risk-taking. We cheer for the founder-in-the-garage mythology. If someone tells you that your idea is flawed, they fear they are crushing your passion.So even when we explicitly ask for brutal honesty, people soften their answers.This is the false positive trap.And if you misread encouragement as traction, you can waste months or even years.The Small Framing Change That Changes EverythingJoe eventually realized that the problem was not the idea itself. The problem was how he was asking for feedback.When you present your idea as the idea, people naturally react supportively:* “That's really interesting.”* “I could see that being useful.”* “This is definitely needed.”But when you instead present two competing ideas and ask someone to help you choose, you change the psychology of the conversation entirely.Joe explained it this way:“When we said, ‘We are building this. What do you think?' people wanted to be encouraging. But when we asked, ‘We are choosing between these two products. Which one should we build?' it gave them permission to actually critique.” This shift is subtle, but powerful. Suddenly:* People contrast.* Their reasoning surfaces.* Their hesitation becomes visible.* Their priorities emerge with clarity.By asking someone to choose between two ideas, you activate their decision-making brain instead of their supportive brain.It is no different from usability testing. If you show someone a screen and ask what they think, they are polite. If you give them a task and ask them to complete it, their actual friction appears immediately.In product discovery, friction is truth.How This Applies to PMs, Not Just FoundersYou may be thinking: this is interesting for entrepreneurs, but I work inside a company. I have stakeholders, OKRs, a roadmap, and a backlog that already feels too full.This technique is actually more relevant for PMs inside companies than for founders.Inside organizations, political encouragement is even more pervasive:* Leaders say they want innovation, but are risk averse.* Cross-functional partners smile in meetings, but quietly maintain objections.* Engineers nod when you present the roadmap, but may not believe in it.* Customers say they like your idea, but do not prioritize adoption.One of the most powerful tools you can use as a PM is explicitly framing your product decisions as explicit choices, rather than proposals seeking validation. For example:Instead of saying:“We are planning to build a new onboarding flow. Here is the design. Thoughts?”Say:“We are deciding between optimizing retention or acquisition next quarter. If we choose retention, the main lever is onboarding friction. Here are two possible approaches. Which outcome matters more to the business right now?”In the second framing:* The business goal is visible.* The tradeoff is unavoidable.* The decision owner is clear.* The conversation becomes real.This is how PMs build credibility and influence: not through slides or persuasion, but through framing decisions clearly.Jaide's Pivot: From Health Search to AI TranslationThe result of Joe's reframed feedback approach was unambiguous.Across dozens of conversations with healthcare executives and hospital leaders, one pattern emerged consistently:Translation was the urgent, budget-backed, economically meaningful problem.As Joe put it, after talking to more than 40 healthcare decision-makers:“Every single person told us to build the translation product. Not mostly. Not many. Every single one.” This kind of clarity is rare in product strategy. When you get it, you do not ignore it. You move.Jaide Health shifted its core focus to solving a very real, very measurable, and very painful problem in healthcare: the language gap affecting millions of patients.More than 25 million patients in the United States do not speak English well enough to communicate with clinicians. This leads to measurable harm:* Longer hospital stays* Increased readmission rates* Higher medical error rates* Lower comprehension of discharge instructionsThe status quo for translation relies on human interpreters who are expensive, limited, slow to schedule, and often unavailable after hours or in rare languages. Many clinicians, due to lack of resources, simply use Google Translate privately on their phones. They know this is not secure or compliant, but they feel like they have no better option.So Jaide built a platform that integrates compliance, healthcare-specific terminology, workflow embedding, custom glossaries, discharge summaries, and real-time accessibility.This is not simply “healthcare plus GPT”. It is targeted, workflow-integrated, risk-aware operational excellence.Product managers should study this pattern closely.The winning strategy was not inventing a new problem. It was solving a painful problem that everyone already agreed mattered.The Core PM Lesson: Focus on Problems With Urgent Budgets Behind ThemA question I often ask PMs I coach:Who loses sleep if this problem is not solved?If the answer is:* “Not sure”* “Eventually the business will feel it”* “It would improve the experience”* “It could move a KPI if adoption increases”Then you do not have a real problem yet.Real product opportunities have:* A user who is blocked from achieving something meaningful* A measurable cost or consequence of inaction* An internal champion with authority to push change* An adjacent workflow that your product can attach to immediately* A budget owner who is willing to pay now, not laterHealthcare translation checks every box. That is why Joe now has institutional adoption and a business with meaningful traction behind it.Why PMs Struggle With This in PracticeIf the lesson seems obvious, why do so many PMs fall into the encouragement trap?The reason is emotional more than analytical.It is uncomfortable to confront the possibility that your idea, feature, roadmap, strategy, or deck is not compelling enough yet. It is easier to seek validation than truth.In my first startup, we kept our product in closed beta for months longer than we should have. We told ourselves we were refining the UX, improving onboarding, solidifying architecture. The real reason, which I only admitted years later, was that I was afraid the product was not good enough. I delayed reality to protect my ego.In product work, speed of invalidation is as important as speed of iteration.If something is not working, you need to know as quickly as possible. The faster you learn, the more shots you get. The best PMs do not fall in love with their solutions. They fall in love with the moments of clarity that allow them to change direction quickly.Actionable Advice for Early and Mid Career PMsBelow are specific behaviors and habits you can put into practice immediately.1. Always test product concepts as choices, not presentationsInstead of asking:“What do you think of this idea?”Ask:“We are deciding between these two approaches. Which one is more important for you right now and why?”This forces prioritization, not politeness.2. Never ship a feature without observing real usage inside the workflowA feature that exists but is not used does not exist.Sit next to users. Watch screen behavior. Listen to their muttering. Ask where they hesitate. And most importantly, observe what they do after they close your product.That is where the real friction lives.3. Always ask: What is the cost of not solving this?If there is no real cost of inaction, the feature will not drive adoption.Impact must be felt, not imagined.4. Look for users with strong emotional urgency, not polite agreementWhen someone says:“This would be helpful.”That is death.When someone says:“I need this and I need it now.”That is life.Find urgency. Design around urgency. Ignore politeness.5. Know the business model of your customer better than they doThis is where many PMs plateau.If you want to be taken seriously by executives, you must understand:* How your customer makes money* What costs they must manage* Which levers influence financial outcomesWhen PMs learn to speak in revenue, cost, and risk instead of features, priorities, and backlog, their influence changes instantly.The Broader Strategic Question: What Happens When Foundational Models Improve?During our conversation, I asked Joe whether the rapid improvement of GPT-like translation will eventually make specialized healthcare translation unnecessary.His answer was pragmatic:“Our goal is to ride the wave. The best technology alone does not win. The integrated solution that solves the real problem wins.” This is another crucial product lesson:* Foundational models are table stakes.* Differentiation comes from workflow integration, specialization, compliance, and trust.* Adoption is driven by reducing operational friction.In other words:In AI-first product strategy, the model is the engine. The workflow is the vehicle. The customer problem is the road.The Future of Product Work: Judgment Over OutputThe world is changing. Tools are accelerating. Capabilities are compounding. But the core skill of product leadership remains the same:Can you tell the difference between signal and noise, urgency and politeness, truth and encouragement?That is judgment.Product management will increasingly become less about writing PRDs or pushing execution and more about identifying the real problem worth solving, framing tradeoffs clearly, and navigating ambiguity with confidence and clarity.The PMs who will thrive in the coming decade are those who learn how to ask better questions.ClosingThis conversation with Joe reminded me that most of the time, product failure is not the result of a bad idea. It is the result of insufficient clarity. The clarity does not come from thinking harder. It comes from testing real choices, with real users, in real workflows, and asking questions that force truth rather than encouragement.If this resonates and you want help sharpening your product judgment, improving your influence with executives, developing clarity in your roadmap, or navigating career transitions, I work 1:1 with a small number of PMs, founders, and product executives.You can learn more at tomleungcoaching.com.OK. Enough pontificating. Let's ship greatness. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

I didn't plan to make a video today. I'd just wrapped a client call, remembered that OpenAI had released Atlas, and decided to record a quick unboxing for my Fireside PM community.I'd heard mixed things—some people raving about it, others underwhelmed—but I made a deliberate choice not to read any reviews beforehand. I wanted to go in blind, the way an actual user would.Within 30 minutes, I had my verdict: Atlas earns a C+.It's ambitious, it's fast, and it hints at a radical new way to experience the web. But it also stumbles in ways that remind you just how fragile early AI products can be—especially when ambition outpaces usability.This post isn't a teardown or a fan letter. It's a field report from someone who's built and shipped dozens of products, from scrappy startups to billion-user platforms. My goal here is simple: unpack what Atlas gets wrong, acknowledge what it gets right, and pull out lessons every PM and product team can use.The Unboxing ExperienceWhen I first launched Atlas, I got the usual macOS security warning. I'm not docking points for that—this is an MVP, and once it hits the Mac App Store, those prompts will fade into the background.There was an onboarding window outlining the main features, but I barely glanced at it. I was eager to jump in and see the product in action. That's not a unique flaw—it's how most real users behave. We skip the instructions and go straight to testing the limits.That's why the best onboarding happens in motion, not before use. There were some suggested prompts which I ignored but I would've loved contextual fly-outs or light tooltips appearing as I explored past the first 30 seconds of my experience:* “Try asking Atlas to summarize this page.”* “Highlight text to discuss it.”* “Atlas can compare this to other sources—want to see how?”Small, progressive cues like these are what turn exploration into mastery.The initial onboarding screen wasn't wrong—it was just misplaced. It taught before I cared. And that's a universal PM lesson: meet users where their curiosity is, not where your product tour is.When Atlas StumbledAtlas's biggest issue isn't accuracy or latency—it's identity.It doesn't yet know what it wants to be. On one hand, it acts like a browser with ChatGPT built in. On the other, it markets itself as an intelligent agent that can browse for you. Right now, it does neither convincingly.When I tried simple commands like “Summarize this page” or “Open the next link and tell me what it says,” the experience broke down. Sometimes it responded correctly; other times, it ignored the context entirely.The deeper issue isn't technical—it's architectural. Atlas hasn't yet resolved the question of who's driving. Is the user steering and Atlas assisting, or is Atlas steering and the user supervising?That uncertainty creates friction. It's like co-piloting with someone who keeps grabbing the wheel mid-turn.Then there's the missing piece that could make Atlas truly special: action loops.The UI makes it feel like Atlas should be able to take action—click, save, organize—but it rarely does. You can ask it to summarize, but you can't yet say “add this to my notes” or “book this flight.” Those are the natural next steps in the agentic journey, and until they arrive, Atlas feels like a chat interface masquerading as a browser.This isn't a criticism of the vision—it's a question of sequencing. The team is building for the agentic future before the product earns the right to claim that mantle. Until it can act, Atlas is mostly a neat wrapper around ChatGPT that doesn't justify replacing Chrome, Safari, or Edge.Where Atlas ShinesDespite the friction, there were moments where I saw real promise.When Atlas got it right, it was magical. I'd open a 3,000-word article, ask for a summary, and seconds later have a coherent, tone-aware digest. Having that capability integrated directly into the browsing experience—no copy-paste, no tab-switching—is an elegant idea.You can tell the team understands restraint. The UI is clean and minimal, the chat panel is thoughtfully integrated, and the speed is impressive. It feels engineered by people who care about quality.The challenge is that all of this could, in theory, exist as a plugin. The browser leap feels premature. Building a full browser is one of the hardest product decisions a company can make—it's expensive, high-friction, and carries a huge switching cost for users.The most generous interpretation is that OpenAI went full browser to enable agentic workflows—where Atlas doesn't just summarize, but acts on behalf of the user. That would justify the architecture. But until that capability arrives, the browser feels like infrastructure waiting for a reason to exist.Atlas today is a scaffolding for the future, not a product for the present.Lessons for Product ManagersEven so, Atlas offers a rich set of takeaways for PMs building ambitious products.1. Don't Confuse Vision with MVPYou earn the right to ship big ideas by nailing the small ones. Atlas's long-term vision is compelling, but the MVP doesn't yet prove why it needed to exist. Start with one unforgettable use case before scaling breadth.2. Earn Every Switch CostChanging browsers is one of the highest-friction user behaviors in software. Unless your product delivers something 10x better, start as an extension, not a replacement.3. Design for Real Behavior, Not Ideal BehaviorMost users skip onboarding. Expect it. Plan for it. Guide them in context instead of relying on their patience.4. Choose a Metaphor and CommitAtlas tries to be both browser and assistant. Pick one. If you're an assistant, drive. If you're a browser, stay out of the way. Users shouldn't have to guess who's in control.5. Autonomy Without Agency Frustrates UsersIt's worse for an AI to understand what you want but refuse to act than to not understand at all. Until Atlas can take meaningful action, it's not an agent—it's a spectator.6. Sequence Ambition Behind ValueThe product is building for a world that doesn't exist yet. Ambition is great, but the order of operations matters. Earn adoption today while building for tomorrow.Advice for the Atlas TeamIf I were advising the Atlas PM and design teams directly, I'd focus on five things:* Clarify the core identity. Decide if you're an AI browser with ChatGPT or a ChatGPT agent that uses a browser. Everything else flows from that choice.* Earn the right to replace Chrome. Give users one undeniably magical use case that justifies the switch—research synthesis, comparison mode, or task execution.* Fix the metaphor collision. Make it obvious who's in control: human or AI. Even a “manual vs. autopilot” toggle would add clarity.* Build action loops. Move from summarization to completion. The browser of the future won't just explain—it will execute.* Sequence ambition. Agentic work is the destination, but the current version needs to win users on everyday value first.None of this is out of reach. The bones are good. What's missing is coherence.Closing ReflectionAtlas is a fascinating case study in what happens when world-class technology meets premature positioning. It's not bad—it's unfinished.A C+ isn't an insult. It's a reminder that potential and product-market fit are two different things. Atlas is the kind of product that might, in a few releases, feel indispensable. But right now, it's a prototype wearing the clothes of a platform.For every PM watching this unfold, the lesson is universal: don't get seduced by your own roadmap. Ambition must be earned, one user journey at a time.That's how trust is built—and in AI, trust is everything.If you or your team are wrestling with similar challenges—whether it's clarifying your product vision, sequencing your roadmap, or improving PM leadership—I offer both 1:1 executive and career coaching at tomleungcoaching.com and expert product management consulting and fractional CPO services through my firm, Palo Alto Foundry.OK. Enough pontificating. Let's ship greatness. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

IntroductionOne of the great joys of hosting my Fireside PM podcast is the opportunity to reconnect with people I've known for years and go deep into the mechanics of business building. Recently, I sat down with Jason Stoffer, partner at Maveron Capital, a venture firm with a laser focus on consumer companies. Jason and I go way back to my Seattle days, so this was both a reunion and an education. Our conversation turned into a masterclass on scaling consumer businesses, the art of finding moats, and the brutal realities of marketplaces.But beyond the case studies, what stood out were the actionable insights PMs can apply right now. If you're an early or mid-career product manager in Silicon Valley, there are playbooks here you can borrow—not in theory, but in practice.Jason summed up his approach to analyzing companies like this: “So many founders can get caught in the moment that sometimes it's best when we're looking at a new investment to talk about if things go right, what can happen. What would an S-1 or public filing look like? What would the company look like at a big M&A event? And then you work backwards.” That mindset—begin with the end in mind—is as powerful for a product manager shipping features as it is for a VC evaluating billion-dollar bets.In this post, I'll share:* The key lessons from Jason's breakdown of Quince and StubHub* How these lessons apply directly to your PM career* Tactical moves you can make to future-proof your trajectory* Reflections on what surprised me most in this conversationAnd along the way, I'll highlight specific frameworks and examples you can put into action this week.Part 1: Quince and the Power of Supply Chain InnovationWhen Jason first explained Quince's model, I'll admit I was skeptical. On its face, it sounds like yet another DTC apparel play. Sell cheap cashmere sweaters online? Compete with incumbents like Theory and Away? It didn't sound differentiated.Jason disagreed. “Most people know Shein, and Shein was kind of working direct with factories. Quince's innovation was asking, what do factories in Asia have during certain times of the year? They have excess capacity. Those are the same factories who are making a Theory shirt or an Away bag. Quince went to those factories and said, hey, make product for us, you hold the inventory, we'll guarantee we'll sell it.”That's not a design tweak—it's a supply chain disruption. Costco built an empire on this principle. TJX did the same. Walmart before them. If you can structurally rewire how goods get to consumers, you've got the foundation for a massive business.Lesson for PMs: Sometimes the real innovation isn't visible in the interface. It's hidden in the plumbing. As PMs, we often obsess over UI polish, onboarding flows, or feature prioritization. But step back and ask: what's the equivalent of supply chain disruption in your domain? It might be a new data pipeline, a pricing model, or even a workflow that cuts out three layers of manual steps for your users. Those invisible shifts can unlock outsized value.Jason gave the example of Quince's $50 cashmere sweater. “Anyone in retail knows that if you're selling at a 12% gross margin and it's apparel with returns, you're making no money on that. What is it? It's an alternative method of customer acquisition. You hook them with the sweater and sell them everything else.” In other words, they turned a P&L liability into a marketing hack.Actionable move for PMs: Identify your “$50 sweater.” What's the feature you can offer that might look unprofitable or inconvenient in isolation, but serves as an on-ramp to deeper engagement? Maybe it's a generous free tier in SaaS, or an intentionally unscalable white-glove onboarding process. Don't dismiss those just because they don't scale on day one.Part 2: Moats, Marketing, and Hero SKUsJason emphasized that great retailers pair supply chain execution with marketing innovation. Costco has rotisserie chickens and $2 hot dogs. Quince has $50 cashmere sweaters. These “hero SKUs” create shareable moments and lasting brand associations.“You're pairing supply chain innovation with marketing innovation, and it's super effective,” Jason explained.Lesson for PMs: Don't just think about your feature set—think about your hero feature. What's the one thing that makes users say, “You have to try this product”? Too often, PM roadmaps are a laundry list of incremental improvements. Instead, design at least one feature that can carry your brand in conversations, tweets, and TikToks. Think about Figma's multiplayer cursors or Slack's playful onboarding. These are features that double as marketing.Part 3: StubHub and the Economics of TrustAfter Quince, Jason shifted to a very different case study: StubHub. Here, the lesson wasn't about supply chain but about moats built on trust, liquidity, and cash flow mechanics.“Customers will pay for certainty even if they hate you,” Jason said. Think about that. StubHub's fees are infamous. Buyers grumble, sellers grumble. And yet, if you need a Taylor Swift ticket and want to be sure it's legit, you go to StubHub. That reliability is the moat.Lesson for PMs: Trust is an underrated product feature. In consumer software, this might mean uptime and reliability. In enterprise SaaS, it might mean compliance and security certifications. In AI, it could mean interpretability and guardrails. Don't underestimate how much people will endure friction if they can be sure you'll deliver.Jason also pointed out StubHub's cash flow hack: “StubHub gets money from buyers up front and then pays the sellers later. That's a beautiful business model. If you create a cash flow cycle where you're getting the money first and delivering later, you raise a lot less equity and get diluted less.”This is a reminder that product decisions can have financial implications. As PMs, you may not directly set billing cycles, but you can influence monetization models, free trial design, or even refund policies—all of which affect working capital.Actionable move for PMs: Partner with finance. Ask them: what product levers could improve cash conversion cycles? Could prepayment discounts, annual billing, or usage-based pricing reduce working capital strain? Thinking beyond the feature spec makes you more valuable to your company—and accelerates your own career.Part 4: Five Takeaways from StubHub Jason listed five lessons from StubHub:* Trust is a moat – Even if users complain, reliability keeps them loyal.* Liquidity is a moat – Scale compounds, especially in marketplaces.* Cash flow mechanics matter – Payment terms can determine survival.* Tooling locks in supply – Seller-facing tools create stickiness.* Scale itself compounds – Once you're ahead, momentum carries you.Part 5: What Surprised Me MostAs I listened back to this conversation, two surprises stood out.First, the sheer size of value retail. Jason noted that TJX is worth $157 billion. Burlington, $22 billion. Costco, $418 billion. These aren't sexy tech names, but they are empires. It made me rethink my assumptions about what “boring” industries can teach us.Second, Jason's humility about being wrong. “Reddit might be one,” he admitted when I asked about his biggest misses. “I had no idea that LLMs would use their data in a way that would make it incredibly important. I was dead wrong. I said sit on the sidelines.” That candor is refreshing—and a reminder that even seasoned investors get it wrong. The key is to keep learning.Lesson for PMs: Admit your misses. Write them down. Share them. Don't hide them. Your credibility grows when you own your blind spots and show how you've adjusted.Closing ThoughtsTalking with Jason felt like being back in business school—but with sharper edges. These aren't abstract frameworks. They're battle-tested strategies from companies that scaled to billions. As PMs, our job isn't just to ship features. It's to build businesses. That requires thinking about supply chains, trust, cash flow, and marketing moats.If you found this helpful and want to go deeper, check out Jason's Substack, Ringing the Bell, where he publishes his case studies. And if you want to level up your own career trajectory, I offer 1:1 executive, career, and product coaching at tomleungcoaching.com.Shape the Future of PMAnd if you haven't yet, I'd love your input on my Future of Product Management survey. It only takes about 5 minutes, and by filling it out you'll get early access to the results plus an invitation to a live readout with a panel of top product leaders. The survey explores how AI, team structures, and skill sets are reshaping the PM role for 2026 and beyond.OK. Let's ship greatness. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

When I sit down with product leaders who've spent decades shaping how Silicon Valley builds products, I'm always struck by how their career arcs echo the very lessons they now teach. Michael Margolis is no exception.Michael started his career as an anthropologist, stumbled into educational software in the late 90s, helped scale Gmail during its formative years, and eventually became one of the first design researchers at Google Ventures (GV). For fifteen years, he sat at the intersection of startups and product discovery, helping founders learn faster, save years of wasted effort, and—sometimes—kill their darlings before they drained all the fuel.In our conversation, Michael didn't just share war stories. He laid out a concrete, repeatable framework for product teams—whether you're a PM at a FAANG company or a fresh hire at a Series A startup—on how to cut through noise, get to the truth, and accelerate learning cycles.This post is my attempt to capture those lessons. If you're an early to mid-career PM in Silicon Valley trying to sharpen your craft, this is for you.From Anthropology to Gmail: The Value of Unorthodox BeginningsMichael's path to Google wasn't a linear “go to Stanford CS, join a startup, IPO” narrative. Instead, he started in anthropology and educational software, producing floppy-disk learning titles at The Learning Company and Electronic Arts. That detour turned out to be foundational.“Studying anthropology was my introduction to usability and ethnography,” Michael told me. “It gave me a lens to look at people's behaviors not just as data points but as cultural patterns.”For PMs, the lesson is clear: don't discount the odd chapters of your own career. That sales job, that nonprofit internship, or that side hustle in teaching can become your secret weapon later. Michael carried those anthropology muscles into Gmail, where understanding human behavior at scale was just as critical as writing code.Actionable Advice for PMs:* Audit your own “non-linear” career experiences. What hidden skills—interviewing, pattern-recognition, narrative-building—could you bring into product work?* When hiring, don't filter only for straight-line resumes. The best PMs often bring unexpected perspectives.The Google Years: Scaling Research at Hyper-speedMichael joined Gmail in 2006, when it was still young but maturing fast. He quickly noticed how different the rhythm was compared to the slow, expensive ethnographic studies he had done for consulting clients like Walmart.com.“At Walmart,” he explained, “I had to compress these big, long expensive projects into something faster. Gmail demanded that same speed, but at enormous scale.”At Google, the prime “clients” for his research were often designers. The questions he answered were things like: How do we attract Outlook users? How do we make the interface intuitive enough for mass adoption?This difference matters for PMs: in big companies, research questions often start downstream—how to refine, polish, or optimize. In startups, questions live upstream: What should we build at all? Knowing where you sit in that spectrum changes the kind of research (and product bets) you should prioritize.Jumping to Google Ventures: Bringing UXR Into VCIn 2010, Michael made a bold move: leaving the mothership to become one of the very first design researchers embedded inside a venture capital firm. GV was trying to differentiate itself by not just writing checks but also offering operational help—design, hiring, PR.“I got lucky,” he recalled. “GV had already hired Braden Kowitz as their design partner, and Braden said, ‘I need a researcher.' That was my break.”Working with founders was a shock. They didn't act like Google PMs. “It was like they were playing by a different set of rules. They'd say, ‘Here's where we're going. You can help me, or get out of my way.'”That forced Michael to reinvent how he showed value. Instead of writing reports that might sit unread, he had to deliver insights in real-time, in ways founders couldn't ignore.The Watch Party Method: Stop Writing ReportsHere's where the gold nuggets come in. Michael realized traditional reports weren't cutting it. Instead, he invented what he calls “watch parties.”“I don't do the research study unless the whole team watches,” he said. “I compress it into a day—five interviews with bullseye customers, the whole team in a virtual backroom. By the end, they've seen it all, they're debriefing themselves, and alignment happens automatically. I haven't written a report in years.”Think about that. No 30-page decks. No long hand-offs. Just visceral, shared observation.Actionable Advice for PMs:* Next time you run a user test, insist that at least your core team attends live. Skip the sanitized recap slides.* At the end of a session, have the team summarize their top three takeaways. When they say it, it sticks.Bullseye Customers: Getting Uncomfortably SpecificOne of Michael's most powerful contributions is the bullseye customer exercise.“A bullseye customer,” he explained, “is the very specific subset of your target market who is most likely to adopt your product first. The key is to define not just inclusion criteria but also exclusion criteria.”Founders (and PMs) often resist narrowing. They want to believe their TAM is huge. But Michael's method forces rigor. He described grilling teams until they admit things like: Actually, if this person doesn't work from home, they probably won't care. Or if they've never paid for a premium tool, they won't convert.Example: Imagine you're building a new coffee subscription. Your bullseye might be: Remote tech workers in San Francisco, ages 25-35, who already spend $50+ per month on specialty coffee, and who like experimenting with new roasters. If your product doesn't delight them, it won't magically resonate with “all coffee drinkers.”Actionable Advice for PMs:* Write down both inclusion and exclusion criteria for your bullseye.* Add triggers: life events that make adoption more likely (e.g., new job, new diagnosis, move to a new city).* Recruit five people who fit it exactly. If they're lukewarm, rethink your product.Why Five Interviews Is EnoughMichael swears by the number five.“After three interviews, you're not sure if it's a pattern,” he said. “By five, you hit data saturation. Everyone sees the signal. Any more and the team is begging you to stop so they can make changes.”For PMs under pressure, this is liberating. You don't need 100 customer calls. You need five of the right customers, observed by the right team members, in a compressed timeframe.Multiple Prototypes: Don't Ask Customers to ImagineAnother Margolis rule: never show just one prototype.“If you show one, the team gets too attached, and the customer can only react. With three, I can say: compare and contrast. What do you love? What do you hate? I collect the Lego pieces and assemble the next iteration.”Sometimes those prototypes aren't even original mockups—they're competitor landing pages. As Michael joked: “Have you tested your competitor's prototypes? No? Then you've left something out.”Actionable Advice for PMs:* When exploring value props, mock up three different landing pages. Don't ask “Which do you prefer?” Instead ask: “Which elements matter most, and why?”* Treat mild praise as a “no.” Only visceral excitement counts as signal.Founders, Stubbornness, and the Henry Ford TrapI pressed Michael on what happens when founders dismiss customer feedback by invoking Henry Ford's famous line about “faster horses.”He smiled. “The beauty of bullseye customers is it forces accountability. If you told me these people are your dream users, and they shrug, then you can't hand-wave it away. Either change your customer definition or your product.”This is a crucial lesson for PMs who work with visionary leaders. Conviction is necessary, but unchecked conviction can sink a product. Anchoring on bullseye customers creates a shared contract that keeps both egos and hypotheses grounded.Bright Spots > Exit InterviewsWhen teams ask him to interview churned customers, Michael often refuses.“There are a bazillion reasons people don't use something,” he said. “It's inefficient. Instead, I go find the bright spots—the power users who love it. I want to know why they're on fire, and then go find more people like them.”This “bright spot” focus helps PMs avoid premature pivots. Instead of chasing every no, double down on the yeses until you understand the common thread.Case Study: Refrigerated Medications and ZiplineTo illustrate, Michael shared a project with Zipline, the drone-delivery company. They wanted to deliver specialty medications. The core question: was speed or timing more important?Through interviews, the bright spot insight emerged: refrigeration was the killer constraint. Patients didn't care about “fastest possible” delivery in the abstract. They cared about not leaving refrigerated drugs on their porch.That nuance completely changed the product and infrastructure design.For PMs, the takeaway is that sometimes the decisive factor isn't the flashy benefit you advertise (“we're the fastest!”) but a practical detail you only uncover through careful listening.AI and the Future of ResearchWe couldn't avoid the AI question. Has it changed his process?“I worry about how AI is creating distance between teams and customers,” Michael admitted. “If my bot talks to your bot and spits out a report, you miss the nuance. The power of research is in the stories, the details, the visceral reactions.”That said, he does use AI for quick prototype copywriting and summaries. But he insists on live team observation for the real work.For PMs, the advice is to use AI as an accelerant, not a replacement. Let it write the rough draft of your landing page copy, but don't outsource customer empathy to a transcript.What PMs Should Do Differently TomorrowLet's distill Michael's 15 years of wisdom into actionable steps you can implement this week:* Define your bullseye. Write down exact inclusion, exclusion, and trigger criteria.* Recruit five. Stop at five, but make them exact matches.* Run a watch party. Get your designer, engineer, and PM peers in the virtual backroom. No observers, no insights.* Prototype in threes. Landing pages are cheap. Competitor screenshots are free.* Look for visceral reactions. Anything less than “Wait, can I get this now?” is a polite no.* Study the bright spots. Find your power users and figure out what makes them glow.* Compress cycles. The whole exercise—recruit, test, learn—should take days, not months.Quotes Worth RememberingTo make these lessons stick, here are five quotes from Michael that every PM should tape to their desk:* “I don't do the research unless the whole team watches.”* “A bullseye customer is the very specific subset of your target market most likely to adopt first.”* “After five interviews, you hit data saturation. Everyone sees the pattern.”* “If you show one prototype, the team gets too attached. With three, you collect the Lego pieces.”* “Mild encouragement is a polite no. Only visceral excitement counts as yes.”My Takeaways as a Coach and PMTalking to Michael reinforced something I've seen in my own career: product failure often comes not from bad execution, but from weak learning cycles. Teams don't test the right people, don't synthesize together, and don't act quickly on what they learn.Michael's methods aren't magic—they're discipline. They compress time, sharpen focus, and force alignment. Whether you're building the next Gmail or the next startup idea in a Palo Alto garage, these principles apply.If you're an early to mid-career PM, start by practicing on a small scale. Don't wait for your manager to bless a massive UXR budget. Run a five-person watch party with your next prototype. You'll be surprised at how quickly the fog lifts.ClosingIf this resonated and you're looking for deeper guidance, I also work 1:1 with PMs and executives on career, product, and leadership challenges. You can learn more at tomleungcoaching.com.And if you haven't yet, I'd love your input on my Future of Product Management survey. It only takes about 5 minutes, and by filling it out you'll get early access to the results plus an invitation to a live readout with a panel of top product leaders. The survey explores how AI, team structures, and skill sets are reshaping the PM role for 2026 and beyond. Let's ship greatness. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

From Chaos to Clarity: How AI is Rewriting the Playbook for Product ManagersLessons from my conversation with ex-Google PM Assaf Reifer on building tools that tame the noise, sharpen priorities, and give PMs back their most valuable resource: focus.When I think back on my time at Google, one of the highlights was building and scaling teams with incredibly talented product managers. Some of those PMs went on to lead big initiatives across YouTube, Google Health, and other parts of the company. A few branched out and became founders.One of them is Assaf Reifer, a former PM on my team at YouTube in Zurich. We first met over breakfast through what I think was a LinkedIn networking experiment. He had been at Bain, was exploring his next move, and we happened to be hiring. The match worked out beautifully. He ended up becoming one of the top performers on the team and played a key role in building YouTube Analytics and the transition from the old Creator Studio into what creators now use daily.Recently, I had the chance to catch up with Assaf on my Fireside PM podcast. He's been experimenting with new projects, one of which could change how PMs everywhere manage the daily chaos of inputs, competing priorities, and distractions. What follows is a long, deep dive into our conversation, plus my take on what early-to-mid career PMs in Silicon Valley can learn from it.The Setup: Why Now Is a Historic Moment for BuildersAssaf started by reflecting on what it feels like to be a builder in 2025. He's been a software engineer, a consultant, and a PM. But he emphasized that the past two years feel different, historic even.I remarked:“In the last two years with advancements in AI, a lot of the knowledge necessary to build something end to end is really bridged by some of these technologies. It empowers people to realize ideas and experiments that previously required 10 people and millions of dollars.”Think about that for a second. Not long ago, building a SaaS product that could ingest Zoom transcripts, Slack threads, and Jira tickets, then triage them into a priority list for a PM would have required a team of engineers, designers, and product folks. Now a single founder can stitch that together with off-the-shelf AI models, APIs, and some creativity.For early-career PMs, the actionable insight is clear: don't wait for permission to build. Even if you're not an engineer, AI has lowered the barrier to entry so much that you can tinker, prototype, and validate ideas faster than ever. Open ChatGPT or Gemini, describe what you want to build, and let the system guide you through the concepts you don't understand.Assaf encourages this approach:“The best way to start is open ChatGPT or Gemini, tell it what you want to build, and ask it how. It will respond with 30 terms you don't understand, and you just go one by one. You ask it to explain each concept, and gradually you close the gap very quickly.”That's the 2025 version of “learning to code.” You don't need to become a full-stack engineer. But you do need to become fluent in exploring, iterating, and leveraging AI as a co-pilot.The Problem: PMs as Air Traffic ControllersAfter talking about the broader builder landscape, we turned to the problem space Assaf is attacking. We discussed product managers as “air traffic controllers,” juggling multiple channels of information, each with different levels of urgency.“Being a PM is all about prioritizing. You're interacting with sales, engineering, customers, peers, executives. You have OKRs on one hand, and then Jira tickets or a customer threatening to churn on the other. Until recently, the best PMs just kept it all in their heads or in spreadsheets.”Sound familiar? If you're a PM, you've probably woken up to a wall of Slack notifications, 10 unread emails from sales, and a Jira dashboard full of tickets. Then, by 10am, you're in a meeting where a senior leader asks, “What do you think about this issue that came up this morning?” And you're embarrassed because you didn't even know it existed.I've been there. And I bet you have too.The core challenge: noise vs. signal. PMs succeed not because they read every message but because they know which ones matter. That judgment call has historically been a mix of intuition, experience, and luck.The Solution: Issue Center (PM Studio?)Assaf's project, tentatively called “Issue Center,” is a SaaS tool that ingests all the inputs PMs already swim in: Slack, Jira, Zoom transcript, and applies AI-powered rules to surface the truly critical items.The workflow looks like this:* Integration: Connect the tool to your company's communication stack. (His design partner is running Microsoft 365/Teams, but it could work with Slack and Google too.)* Rule Setup: Create rules that define what matters to you. For example, “API degradation impacting users” is critical. Or “customer mentions a competitor as better” is high.* AI Assistance: The system uses AI to evaluate whether inputs match your rules. It flags the items, explains why, and links you back to the source.* Prioritized Dashboard: Instead of drowning in messages, you wake up to a curated list of critical, high, and medium issues to tackle first.Assaf demoed it live, showing how rules surfaced relevant Jira tickets, Slack threads, and transcripts. At one point, he laughed at his own naming convention:“Clearly I'm not a marketer. It's called Issue Center for now, but we can call it PM Studio if that makes it sound cooler.”I told him PM Studio had a nice ring to it.The important thing wasn't the branding, though—it was the shift from reactive scrambling to proactive clarity.Actionable Takeaway #1: Define Your Own Rules of SignalHere's where PMs can learn something even before using a tool like this. Ask yourself: What are the true signals in my work?* Is it when a customer threatens to leave?* When an API is degrading?* When an executive brings up a competitor?Whatever they are, write them down. These are your “rules.” Even if you don't have AI filtering your inputs yet, the discipline of defining rules forces you to separate noise from signal.Assaf admitted that rule-writing is an art:“The rule description is very important, because that's what the system uses to match. If it's too narrow, it won't pick up. If it's too broad, you'll get noise. That's why I want to make onboarding easier with quick-start templates for common rules.”This mirrors how you should think about your own prioritization framework. If you're too vague (“respond to all customer requests”), you'll drown. If you're too narrow (“only focus on API latency under 200ms”), you might miss the forest for the trees.The Bigger Picture: Managers of PMsAssaf also highlighted another layer of value, helping PM leads manage their teams.“If you're a PM lead and you have a team, you want visibility into what critical topics your PMs care about, what jeopardizes OKRs, and where they need support. This tool can give you that bird's-eye view.”This is huge. One of the hardest parts of managing PMs is knowing what's actually keeping them busy. Are they firefighting customer issues? Negotiating with engineering? Or chasing shiny objects?For managers, the actionable advice is: ask your PMs to share their “critical issue list” with you weekly. Even if you don't have Assaf's tool yet, that discipline will create alignment and uncover mis-prioritizations.The Privacy Angle: Building TrustWe also talked about the obvious concern: privacy. If your tool is reading Slack messages, Zoom calls, and Jira tickets, where does that data go?Assaf has thought about this deeply:“This is architected as a single-tenant SaaS. It's installed in your company's own cloud tenant. Nothing leaves the org. Even when we use AI, it runs through your enterprise API key, which isn't used for training.”For PMs evaluating AI tools, this is a reminder: always ask how data is handled. At many companies, legal and IT will shut down even the coolest tool if privacy isn't bulletproof. If you're the PM championing adoption, anticipate those concerns and come prepared with answers.Actionable Takeaway #2: Trust Is a FeatureIn 2025, building trust is not just about having the right feature set. It's about handling privacy, security, and reliability as first-class features.If you're building a product, or even advocating for one inside your company, bake trust into your pitch. Show that you've thought about data handling, failure modes, and user control.Beyond Explicit Rules: The Future of Inferred PrioritiesOne of the fun parts of our conversation was brainstorming future features. I suggested that beyond explicit rules, the system could infer priorities by watching behavior:* If you always jump into competitor-related Slack threads, the system could propose a rule.* If you consistently respond faster to certain stakeholders, it could bump their inputs up in priority.Assaf agreed this was interesting but also flagged the risks:“Whenever you do something that isn't explicitly set by the user and you get it wrong, you risk losing trust. You don't want noise creeping into the critical bucket.”That's a broader lesson for PMs: don't get seduced by complexity if it undermines trust. Sometimes a simple, transparent system is better than a magical one that feels unpredictable.The Side Project: An AI Teddy BearWe spent most of our time on PM Studio, but Assaf also showed me something else: a prototype for an AI-powered plush toy that serves as a conversational buddy for kids.The idea is part educational, part entertaining. Think Teddy Ruxpin meets ChatGPT, but with parental controls and guardrails.He tested it with his own kids, and at one point, a child said he wanted to “eat the squirrel” in a story. The system responded, “That's not a very nice thing. Let's try something kinder.”That made me laugh—and also highlighted the importance of building safe AI for children.As a parent myself, I told Assaf:“If this thing could help kids develop critical thinking and curiosity before they jump into ChatGPT, I'd pay money for it. We don't formally teach critical thinking to children, but a well-designed toy could do it through fun experiences.”While this project is still early, it connects to a broader theme: AI is reshaping not just how we work, but how we learn, parent, and play.Actionable Takeaway #3: Think About Second-Order EffectsFor PMs, the teddy bear might seem irrelevant. But the lesson is this: when you build with AI, think about the second-order effects.* How does this change how people learn, not just how they work?* How does it shape what they trust, not just what they use?* How does it influence long-term skills, not just short-term productivity?If you only optimize for immediate outcomes, you miss the deeper impact your product could have.Practical Advice for PMs in Silicon ValleyLet's bring this back to you, the early-to-mid career PM navigating the chaos of Silicon Valley. Here are five actionable insights from my conversation with Assaf:* Define Your Critical Rules. Don't wait for a tool. Write down the signals that truly matter in your role and use them to triage your own work.* Build Trust Through Clarity. Whether you're building products or pitching ideas internally, make privacy, reliability, and transparency part of your value prop.* Use AI as a Learning Co-Pilot. Open ChatGPT or Gemini and let it teach you the concepts behind the systems you want to build. Don't be afraid of looking dumb, ask it to explain everything.* Share Priorities with Your Manager. If you manage PMs, ask for their top three critical issues weekly. If you're managed, proactively share them. It will align expectations and reduce surprises.* Anticipate Second-Order Effects. Don't just think about what your product does today. Think about how it changes behavior, skills, and trust over time.Why This Matters: The Cambrian Explosion of BuildersWe closed our conversation reflecting on the bigger picture. I remarked:“You wonder if the next hundred billion dollars of market value will come not from 10 decacorns, but from a thousand smaller companies run by 5–10 people. That's good for customers. It's good for competition. And it's possible because of AI.”This is a turning point in product management. The PMs who thrive in the next decade will be those who can harness AI, not just as users, but as builders, integrators, and thinkers.Final ThoughtsCatching up with Assaf reminded me of why I love product management. At its best, it's about solving messy problems, shaping the future, and helping people focus on what matters most.As you navigate your own PM career, I encourage you to experiment with AI, define your rules of signal, and always keep trust at the core of what you build.And if you want more personalized support, I run a 1:1 executive, career, and product coaching practice at tomleungcoaching.com. If you want to try Assaf's Issue Center tool as a design partner, feel free to contact him or hit him up on X. OK. Enough pontificating. Let's get back to work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

Product Managers spend their days drowning in docs, tickets, user feedback, and endless Slack threads. What if AI could cut through the noise, flag what's urgent, resolve the routine, and let you focus on strategy? On this week's Fireside Product Management, I sit down with former Google PM and Bain consultant Assaf Riefer to discuss the product he's building to do exactly that—an AI copilot for PMs. If you've ever wished you had an associate PM working 24/7 at your side, this one's for you.

When Jess Gilmartin talks, I listen. If you've been in Silicon Valley long enough, you might have heard of Jess. She's been a full-time CMO, a founder, a startup whisperer, and most recently, one of the sharpest advisors to CEOs I know when it comes to hiring marketing leadership that actually works.In our recent Fireside PM conversation, we went deep on the do's and don'ts of hiring a CMO. While many of my listeners and readers are early- to mid-career product managers, this interview is packed with insight relevant not just to founders and CEOs but to any PM who will eventually be part of a hiring panel, collaborating with marketing peers, or considering their own path to executive leadership.Why Your Company Even Needs a CMOLet's start with first principles. As Jess puts it:“The CMO is the steward of the brand. And brand isn't just your website or ads—it's every interaction a customer has with your company. That includes your support team, your social media presence, your onboarding experience, and yes, your product.”The reason this matters for PMs is simple: we often underestimate the scope and gravity of the brand experience. We build features. We define roadmaps. But we rarely think of the emotional resonance of what we're building.“Part of the job is ensuring consistency and excellence across all these touchpoints,” Jess said. "That also means having the spine to flag when something the product team is doing will degrade that experience."Translation? If you think marketing's job is to "wrap" your product after the work is done, you're missing the point.What Great CMOs Actually Do (Hint: It's Not Just Marketing)One of the biggest wake-up calls for me was hearing Jess talk about the real job of a modern CMO:“When I was a CMO, I had senior leaders under me running product marketing, growth, and comms. I spent most of my time on executive alignment, crisis communications, and internal messaging. I was rarely in the weeds.”That division of labor is a signal. The difference between a head of marketing and a CMO isn't just title inflation—it's scope. A CMO thinks in systems. They think in multi-stakeholder alignment. And above all, they should be one of the CEO's most strategic advisors.Jess broke it down this way:“The biggest mistake founders make is hiring too senior or too junior a marketer for where they are. If you're still pre-product-market-fit, don't hire a head of marketing. You need to be doing that work yourself.”As someone who has worked with a lot of pre-PMF startups, I couldn't agree more. And yet, time and time again, I see companies try to paper over early churn or stagnant growth with splashy campaigns and SEO spend.It doesn't work.Product Managers: Here's What You Keep Getting WrongThere was one part of our conversation where my PM blood pressure rose just a bit. I asked Jess what she does when she's in a cross-functional meeting and the product team is proudly showcasing something... that isn't actually great for the user experience.She smiled:“I try not to have strong opinions on product. That's not my job. But I deeply understand the customer experience. And when I see something that isn't going to land, I raise a fuss. Not all the time—you have to pick your battles—but marketing sees across silos. We're often the ones that spot inconsistencies in the end-to-end experience.”PMs, listen carefully to that last part.We often live in silos—focused on our vertical, our feature, our sprint velocity. Meanwhile, marketing is scanning horizontally, sensing what happens when someone tries to connect the dots. That perspective is invaluable. And if you're lucky enough to work with a CMO or a senior PMM who raises their hand about UX inconsistencies or cross-functional misalignments, treat that as signal, not noise.The Dirty Truth About CMO TenureReady for the most sobering stat of the interview?“Most CMOs last two years,” Jess said flatly.Why? Expectations are sky-high. CEOs want the creativity of Nike, the analytics of Facebook, the virality of TikTok, and the demand gen of HubSpot—all in one human. Oh, and don't forget crisis PR, event strategy, and internal morale-boosting Slack posts.That level of sprawl is untenable.“Marketing is the only function where we expect a single person to be excellent at creative, numbers, product thinking, storytelling, operations, hiring, and analytics,” she said. “It's unrealistic.”So what happens? You hire a CMO for one phase, they nail it, and then two years later the business needs something else. That's not a failure. That's reality.Founders and PM leaders should take note: you're not hiring a CMO to last forever. You're hiring them to solve today's problem exceptionally well.Demand Gen vs. Messaging vs. PMM: Pick Your PoisonThis next insight is gold for any hiring manager:“When hiring a marketing leader, figure out what your biggest problem is. Is it lack of pipeline, weak differentiation, or lack of strategic product alignment? You won't find someone world-class at all three.”Jess described three typical archetypes:* Demand Gen-focused leaders – Performance-oriented, data-driven, often strong in growth loops and paid acquisition but weaker on storytelling or product narrative.* Brand and Messaging experts – They come up through storytelling, design, and content. These are the campaign artists and identity shapers.* PMM-style CMOs – Strong in positioning, go-to-market, launch orchestration, and cross-functional strategy. They see the product and customer journey clearly but may lack deep growth or brand skills.That might be the most important hiring advice in this entire conversation. Every CMO candidate comes from somewhere. What they did before will influence what they do next. The key is aligning that background with your immediate business challenge.If you already have a rockstar PMM but no repeatable pipeline, hire a demand gen-oriented CMO. If you've got leads but they don't convert or your brand is invisible, find a storytelling operator.And if you're a PM moving up the ranks? This is how you should evaluate your marketing counterparts. Don't just ask "are they good?" Ask: are they good at the thing we need most right now?Hiring CMOs: Skip the Case Study, Do the PlanWhen Jess advises founders on hiring a CMO, she doesn't run them through generic behavioral interviews or vague culture fit chats. She makes them present a real plan.“I give them a budget. I give them our current strategy. I ask: 'Show me how you'd spend it and what your plan would be to hit our goals.'”The best candidates, she said, are:* Articulate – They speak clearly, persuasively, and inspire confidence.* Specific – They don't just say "we'll run paid ads" or "we'll increase brand awareness." They tell you how, why, and in what sequence.* Bold – They bring creative energy. One candidate impressed Jess with cheeky, bold challenger messaging that she herself wouldn't have dreamed up.That kind of spark matters. Especially for a role that's supposed to shape how the world feels about your company.Founders: Don't Get Dazzled by LogosPerhaps the spiciest take in the conversation came when I asked Jess about resume signals:“Do not get dazzled by former companies. That senior PMM from Salesforce may not have ever hired a team, built a pipeline, or touched brand messaging.”This hit close to home. As a former Google exec, I know all too well how much people over-index on logos. Jess prefers candidates who have been in the trenches—startup veterans, operators who've hired across functions, people with range.The ultimate test? Jess asks: Did they just run the playbook, or do they know how to build one?Actionable Advice for PMsSo, what should early- and mid-career product managers take from this?* Learn to speak marketing. Understand the difference between PMM, brand, growth, and demand gen. This makes you a better cross-functional partner.* Invite your PMM early. Don't treat them as a launch afterthought. Bring them into ideation, prioritization, and roadmap planning.* Observe how marketing fights. Good CMOs don't just object; they escalate. They build coalitions. Watch how they influence.* Test CMO fit with real-world scenarios. Ask candidates to brainstorm a real strategic decision or messaging conflict. See how they think.* Beware the shiny logo. Ask CMO candidates what they personally owned, who they hired, and what they changed. If you hear too much passive voice, dig deeper.A Final WordIf you're a founder or exec looking to hire your first CMO, I strongly suggest you watch the full interview. And if you're a PM, use this as a lens to reflect on your own career. How well do you understand your marketing counterparts? How would you describe your company's brand? Learn more about Jess here.If you'd like help with your own product leadership journey, I offer 1:1 coaching at tomleungcoaching.com. OK. Enough pontificating. Let's get back to work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

We're back with a Startup Spotlight episode on the Fireside PM podcast. It's not every day you get to speak with someone who's straddled the worlds of architecture, gaming, AI, and robotics—and managed to turn those disparate threads into a startup tackling one of the most important problems in our robotic future.Steven Ren, the co-founder and CEO of Palatial, joined me from Lower Manhattan to share the winding journey of his company—from Cornell's architecture school to optimizing simulations for robot training at scale. We went deep on the technology, market evolution, and product insights he's picked up along the way—and there are dozens of takeaways here for early and mid-career PMs, especially those building infrastructure, devtools, or working in AI-adjacent spaces.From Watercolors to Headsets: The Early SeedsSteven didn't grow up dreaming of building tools for humanoid robot training. He actually wanted to be an architect—and studied architecture at Cornell. His turning point came in a multidisciplinary studio class led by Don Greenberg, a legend in computer graphics.“He was always trying to get architects to work together with the CS people… and that really opened my eyes to what immersive tech and real-time rendering could do for communicating spaces.”This interdisciplinary exposure planted the idea that real-time, explorable 3D environments could fundamentally improve how people visualize, design, and collaborate around spaces—both physical and digital.He got a taste of this while at Tesla, working on Giga factory expansion. The rapid pace of construction caused costly design coordination issues, and Steven built a prototype that stitched disparate CAD formats into a fly-through simulation using Unreal Engine.“I put together a pipeline that optimized and converted all the CAD designs into an Unreal Engine level—basically a big game—so they could fly around and see how everything fit together.”It helped prevent expensive errors and even became a tool for internal storytelling. That experience solidified his conviction: digital twins weren't just cool—they were valuable. He knew he wanted to build a company that scaled that capability.Pivot 1: From Architecture to OptimizationThe initial Palatial concept was ambitious: a cloud platform where architects could upload CAD files and get back interactive, game-like visualizations that clients could explore in the browser.Sounds great—until you realize how unpredictable CAD file structures can be.“Every software is different, and everyone uses the software differently. You have to make foundational translations between how engineers organize a scene and how game engines expect it.”Instead of a tidy black box, they were faced with a combinatorial nightmare of input variability. Worse, customers didn't want a finished result—they wanted control over how their designs were rendered and experienced.So they pivoted. The new insight: the universal pain point was optimization. Making the scenes look and perform well across platforms.Enter: Palatial as a plugin for Unreal Engine. The new tool became something like “CCleaner for your 3D scene,” scanning for inefficiencies and letting users apply best-practice fixes with a few clicks. Lighting, texture mapping, model merging—all simplified and standardized.“Even if you don't understand what's going on, the idea is that you can arrive at a much more optimized project… and sometimes better-looking too.”If you're a PM shipping developer tools or plugins, take note: this pivot exemplifies how deep user testing can uncover the narrow wedge feature that wins adoption—before expanding.The Aha Moment: Simulations, Not ShowcasesDespite the optimization plugin gaining traction, Steven and the team began to spot a different kind of demand: robotics companies were building millions of virtual environments for training and testing.“You need like hundreds of thousands of environments to teach the robot all the different variations of the world it could come across.”Today, many of those teams manually build 3D scenes—or worse, ask ML engineers to fumble their way through creative tasks. It's expensive, inconsistent, and distracts from core innovation. Steven saw a gap Palatial was well-suited to fill.So they pivoted again.Now, Palatial is focused on powering massive-scale, high-fidelity simulation environments—starting with objects and scenes that train robots to physically manipulate the real world.PM Takeaway #1: Don't Fear the Pivot—Engineer for ItMost PMs are taught to avoid scope creep, but what Palatial did is different. They bet on a market's inevitable evolution (robotics), built a wedge feature (optimization), and used that to find the real platform opportunity (simulation infrastructure).Steven put it plainly:“It's been a winding journey. We thought we'd serve architects, then realized robot developers had the same need—but at far greater scale.”This is a playbook for product leaders:* Find a general pain point across verticals (in Palatial's case: messy 3D pipelines)* Build a useful component (e.g., optimization plugin)* Watch for the industry that experiences that pain at 10x scale (robotics vs. architecture)PM Takeaway #2: Build for Openness, Not Lock-InAnother strategic decision: rather than offering a fully walled-off end-to-end platform, Palatial focused on modularity.“We're going to offer this as an API so teams can build generation into their existing pipeline… and just use that piece.”In a world where AI stacks are increasingly bespoke, trying to own everything can backfire. By being composable, Palatial makes itself easier to adopt—especially for developers already invested in internal tooling.Whether you're in devtools, AI, or infra, this is a good reminder: great platforms start by being great plugins.PM Takeaway #3: Product-Market Fit Might Be a Who, Not a WhatPalatial didn't change their core tech—they changed the user.Same backend pipeline. Same rendering engine. But by shifting from architects (low frequency, high customization) to robotics engineers (high frequency, high fidelity), they unlocked a recurring, sticky use case.“We realized this isn't about showcasing a single building. It's about training robots through thousands of virtual environments—and those environments need to look and behave like the real world.”This kind of vertical shift is especially relevant in today's AI world, where many companies sit atop general capabilities. The biggest opportunities often come from narrowing the audience, not the scope.PM Takeaway #4: Speed is the New MoatIn one of my favorite moments, I asked Steven how he thinks about competitive defensibility.His answer:“There's no such thing as a technological moat anymore. The moat is speed—having a nimble team that can iterate fast and adapt.”We've heard echoes of this across the startup world, but it hits especially hard in AI and frontier tech. If you're leading a PM team, ask yourself: are you shipping faster than your competitors can copy you?And if not, why not?PM Takeaway #5: Accuracy Will Be the Differentiator in the Robot EraOne thing Steven emphasized again and again was realism. In order for simulation-trained robots to be effective, their environments must behave like the real world. That means physical properties, lighting conditions, and object metadata all matter.“There's no point in generating data if it doesn't match reality. You can generate as much crappy data as you want—it's like oversweetened candy. You don't want it.”In other words: in the age of synthetic data and generative tools, quality—not just quantity—will win.As a PM, that might mean:* Prioritizing fidelity over speed when the stakes are high* Partnering with domain experts to tune your models* Making room for manual curation and validation—even if it slows you downPM Takeaway #6: Be Willing to Outgrow Your Initial MarketSteven was candid about the limits of their original architecture play:“It was kind of a one-and-done thing. There's a bigger market where you need many environments, all the time.”This highlights something I often tell coaching clients: your first ICP (ideal customer profile) is often just a foothold. Pay attention when your usage data, pricing power, or support requests point to higher-value customers in adjacent markets.Where Palatial Is HeadedToday, Palatial is in the middle of rolling out their MVP for simulation-ready 3D asset generation. These aren't just pretty models—they contain metadata about mass, bounce, physics, and more, making them usable for training and validation.They're also building the tooling to generate full environments from those assets and optimize them for scale.Eventually, Steven sees a future where the robots themselves are capturing and syncing environments in real-time:“Eventually this will be onboard the robots. As they walk around, they'll translate what they see into a digital twin—and train on that in the background.”That vision is a long way off. But Palatial is betting that when we get there, infrastructure like theirs will be indispensable.Final ThoughtsIf you're an early or mid-career PM, a few questions to reflect on:* What new verticals are quietly developing the same problems my team is already solving?* Is there a simpler, standalone piece of my product that could become a wedge?* Am I over-investing in platform scope vs. developer modularity?* Is my team fast enough to stay ahead in a post-moat world?If you want to stay close to the frontlines of robotics infrastructure—or you just want to learn from a founder iterating in public—follow Steven Ren and check out palatialxr.com.And if your own company is navigating complex product strategy decisions or early-stage growth hurdles, I offer one-on-one coaching at tomleungcoaching.com, and product consulting and startup advisory services at paloaltofoundry.com.OK, enough pontificating. Back to work, team. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

Twenty-five years ago, Tim DeSieno and I were two outsiders on the tropical island of Singapore, me trying to build a startup, him fresh out of a restructuring law practice. We reconnected recently on the Fireside PM podcast, and what followed was one of the most illuminating conversations I've had this year.Tim's career arc is anything but conventional: from decades in global debt restructuring to litigation finance investor, and now advisor to an AI legal startup. The conversation, which started as a reunion, turned into a firehose of insight—for lawyers, founders, and especially product managers trying to anticipate where disruption lands next.This post distills that hour-long conversation into key lessons for early- and mid-career product managers. Whether you're wrangling roadmaps at a Series A startup or driving platform strategy at a late-stage unicorn, you'll find practical frameworks, surprising analogies, and a peek into the wild intersection of law and AI.1. Litigation Funding Is What Early VC Investing Looks Like in a Non-Tech Industry"We would look at 100 cases, take three seriously, and maybe fund one."Tim described litigation finance as a "venture capital" approach to legal claims. Funders underwrite the legal equivalent of startups: high-risk, high-reward lawsuits with uncertain outcomes. The investment model is classic VC—non-recourse funding in exchange for a percentage of winnings—but applied to torts, sovereign disputes, and commercial litigation.This is a also a class in triage. As PMs, we're sometimes guilty of over-indexing on tech, TAM or user demand without enough scrutiny of distribution or defensibility. In litigation finance, everything must be strong: the legal basis, the plaintiff's character, the likelihood of enforcement.Actionable Advice:* When evaluating new bets, use a PM version of Tim's triangle: Strength of case, rational actor, enforceability. Substitute your product's domain as needed. If your bet falls apart on any leg, kill it early.* Don't be afraid to walk away. "We'd spend weeks researching only to discover a fatal flaw." Avoid sunk cost fallacy.2. The Real AI Gold Rush Isn't Just Generation, It's PredictionHarvey (the legal AI startup backed by OpenAI) gets the headlines, but Tim is on the board of an earlier stage adjacent player called Canotera. Instead of drafting, Canotera predicts litigation outcomes. Think of it as a risk analytics layer built from all New York legal precedents, offering lawyers (and insurers, GCs, even arbitrators) a probabilistic view of their odds."It's like calling up a senior partner and getting a second opinion—except this one has read every case."This isn't just a better way to write memos. It's a decision-making accelerator.Product Insight: There are many types of AI value in any vertical:* Efficiency (do more, faster)* Accuracy (better outcomes)* Confidence (de-risking decisions)Harvey is largely #1 and #2. Canotera is going hard at #3.Actionable Advice:* When building AI products, map your feature set to these value levers. Which one are you really selling?* Don't sleep on #3—especially in regulated or high-stakes domains, confidence trumps speed.3. Adoption Gaps Aren't Just Technical—They're Psychological"The number of people in law who haven't touched ChatGPT is shockingly large."Sound familiar? We've all worked with that PM, eng lead, or exec who in late 2022 who thought gen-AI was a toy. The parallel to law is stark: many lawyers fear AI not because it's ineffective, but because it threatens their identity.In both professions, billing hours and writing decks have long been proxies for value. When those tasks are automated, the insecurity is real.Actionable Advice:* Frame AI as augmentation, not replacement. Tim noted the firms that are thriving are those that say, “Yes, we bill per hour—but we'll use AI to deliver more per hour.”* Early adopters are not just tech-savvy—they're secure enough to rethink their role. When evangelizing AI, target the curious and the confident.4. “Doctrinal vs. Practical” Isn't Just a Law School Problem"You come out of law school, and you're good at arguing both sides. But no client wants that."Tim called out how legal education—especially the Socratic case method—trains great thinkers but poor practitioners. Law grads often need years of on-the-job experience before they become useful to clients.Sound like any junior PMs you know?Product teams are often full of doctrinal thinkers—people great at debating frameworks, prioritization models, or vision decks. But if you can't turn that into a working prototype, a roadmap aligned with GTM, or a tough tradeoff call, you're not adding value.Actionable Advice:* “Thinking like a PM” (strategy, ambiguity, storytelling) is necessary but not sufficient. Pair it with executional reps early in your career.* If you're a manager, give your ICs reps they can own end to end. Treat it like an apprenticeship, not just a theoretical seminar.5. Liberal Arts Still Matter—Even in the Age of AGI"If you can't write it clearly, you don't own it."Tim made a powerful case for the liberal arts as the antidote to AI passivity. He sees students turning in polished work generated by LLMs but lacking any real grasp of the content. Writing, he argues, is thinking. If you can't articulate a point unassisted, your judgment muscles don't get built.Actionable Advice:* Don't outsource the first 70% of a product brief, strategy doc, or roadmap to ChatGPT. Use AI to refine and stress-test, not originate.* Push yourself to learn something uncomfortable. Tim's litmus test: "Do hard things that are new to you. That's how you grow judgment."6. You're Not Competing With AI, You're Competing With Humans Using It Better"A junior lawyer with AI tools can be more valuable than a senior one without."In a decade, your job won't be taken by AI—but it might be taken by someone with 5 years less experience who knows how to pair human empathy with AI speed.Actionable Advice:* Learn prompt engineering, yes—but also get great at evaluating AI output. That judgment layer is what companies will pay for.* Practice defending ideas live, without a script. At some point, someone will ask, “Why did you make that decision?” Be ready.7. Forecasting the Endgame: When Courts Run on Code"Maybe one day litigation disappears—two parties upload their facts, the machine decides, and that's enforceable."While Tim was cautious to say this vision is far off, the implications are worth pondering. What happens when not just lawyers, but judges, juries, and arbitrators are augmented—or replaced—by machines?Whether or not this comes to pass, the lesson is clear: no profession is immune. If law can be automated, so can most knowledge work. And product managers will either ride that wave—or be washed away.In ClosingAs PMs, we love talking about disruption—but we rarely get to see it play out in an industry as slow-moving and tradition-bound as law. That's what made this conversation with Tim DeSieno so instructive. Law is changing. AI is changing. And the humans who thrive are the ones who stay curious, adaptable, and relentlessly focused on value—not ego.If this resonated, I offer 1:1 coaching for product leaders at tomleungcoaching.com, and PM consulting through paloaltofoundry.com.OK. Enough pontificating. Let's get back to work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

“We Are Not in Kansas (or Creatorland) Anymore”When I kicked off this Fireside PM interview with Ben Grubbs, I knew we'd cover the creator economy. What I didn't expect was how much of it would end up being an MBA seminar for product managers.Ben isn't just another ex-YouTube guy with creator war stories. He's seen the evolution of the online video ecosystem from its scrappy, quirky beginnings to the billion-dollar global marketplace it is today. His vantage point spans across YouTube FanFest, the launch of YouTube Kids, and later, his own venture Creator+.But this isn't a nostalgia trip. This conversation is about understanding where the creator economy went right, where it went off the rails, and what PMs and builders can learn from those who survived—and thrived.Let's break it down.1. Don't Just Sell Picks and Shovels—Sell Gold Bars TooThere's an old startup trope: during a gold rush, the people who make the money are the ones selling picks and shovels.Ben and I reflected on this assumption when it came to the 2021–2022 wave of creator economy startups—tools for analytics, monetization, editing, payroll, and more.A lot of those bets fizzled.Why?Because the “miners”—the creators—were not your typical enterprise buyers. Most didn't make enough to justify expensive tools, and those who did weren't being well-served.“You had companies working with hundreds or thousands of creators,” Ben said. “But they were all Tier 5 or Tier 6. The top creators—the ones running real businesses—weren't touching these tools. The startups couldn't crack that ceiling.”Creators with scale (think Tier 1) needed tools built with deep empathy for their workflows—but often the tool builders didn't even have relationships with these creators.It's a warning for PMs: Just because there's a problem doesn't mean the solution is a venture-scale business.Ben would often gut-check startup ideas by calling former colleagues at YouTube to ask if the feature in question was in the product roadmap.“If they told me it was far down the list—great. That's a two-year runway. But if it was near the top? I'd pass.”Takeaway for PMs: Before betting your career or company on a “picks and shovels” play, ask:* Can I serve the high-value users, or am I stuck with long-tail?* Is this something the platform will inevitably build?* Does this idea have cross-platform defensibility?If the answer to all three is “no,” it's probably not a durable business.2. The Myth of the Accidental CreatorOne of the most common origin stories in the creator economy is the passionate hobbyist who stumbled into success. But that's no longer the only model—or even the dominant one.Ben contrasted the early YouTube generation with today's operator-led brands like Good Good Golf, where content wasn't the product—it was the acquisition channel.“This wasn't some happy accident. Good Good had a clear business strategy from Day One. Content was the top-of-funnel. They were always going to build a real consumer business.”And build they did. Good Good went from viral YouTube content to a thriving golf apparel and equipment brand, all while keeping production margins high and paid marketing spend low.How? They applied DTC logic to a creator-native model. Instead of paying for reach, YouTube paid them to market their own products.“Some DTC founders were stunned by their margins. But they didn't realize: Good Good gets paid for their marketing.”Ben's point: this isn't selling out. It's growing up.And it's working.Actionable Tip for PMs: When evaluating growth loops, ask yourself:* Is our content serving a bigger business objective?* Can our audience also become customers?* Are we building a brand—or just renting attention?3. Build for the Power LawWe all know the creator economy is a power-law business. But what does that mean for those building around it?Ben shared a fascinating stat from his YouTube days: at one point, 4,500 creators met the threshold to qualify for top-tier partnership. But YouTube had resources to serve just 500.“We couldn't support everyone. And the people who qualified were far more than we could manage. That's when I realized: there's a huge gap.”That gap created opportunities—but only if you could build for the whales.Most of the SaaS tools went after the long tail. Wrong call.“The top creators are basically SMBs. They need operational support, yes—but they also need defensible strategy, content licensing, IP management. That's not just software—that's consulting, services, and deal-making.”Moonbug is a perfect example.They weren't a tool. They were a studio that centralized production, built IP (like Cocomelon), and sold toys, media rights, and more. They exited for over a billion dollars.For PMs and founders, the takeaway is this:* Don't assume the long tail is the market.* Go upstream. Serve the whales.* Focus on full-stack solutions, not just utilities.If you're not building something worth $10M+ in ARR from a dozen clients, you're probably building a feature, not a business.4. MrBeast Is a Company, Not Just a Creator—and That's the PointWe couldn't have this convo without talking about MrBeast.Ben sees Jimmy Donaldson as a pioneer not just in content, but in company structure. His organization isn't a hobbyist's shop—it's a holding company with a real CEO.“Jimmy's not the CEO. He's the chairman. They hired a real operator from public markets. That person is building a corporate org. They're hiring institutional people. It's becoming a conglomerate.”Unlike most creator ventures—where investors buy into just one slice of the pie—MrBeast's holding company gives investors exposure to all ventures.Think Alphabet, not a side hustle.“It's better alignment. If you're putting in capital, you want access to the whole thing—not just the candy bar business or the mobile game.”And that model might just be repeatable.As Ben put it: “A lot of creators say they want to be CEOs. But once they see what CEOs actually do—HR, legal, compliance—they change their mind fast.”Jimmy didn't want to be bogged down in operations. So he hired someone who could be.PM Insight: If you're working with high-talent individuals—creators, researchers, engineers—don't just elevate them to management. Design orgs where they can focus on their strengths and bring in ops leaders to scale.5. AI Is Not the End. It's the Efficiency Revolution.Toward the end of the episode, we dove into AI's impact on the creator economy.Ben doesn't see it as a doomsday scenario. Quite the opposite.“One animation company showed me a tool that turned a sketch into a production-ready 3D model—in real time. That's insane. The question is: do you lower your prices… or do you double your margin?”That's the rub.AI will reduce production costs. Which means more creators will have studio-grade tools at their fingertips. It also means fewer people per production.“I was on a shoot with 50 people. Half weren't doing anything. I realized the producer brought them in for optics—to make it look big-budget.”In other words, there's fat to be trimmed. And AI is the scalpel.I brought up the stability of the power-law impact. The best AI-assisted content will still win. Most will get buried.“It's like CGI in the movies. People feared it would kill cinema. Instead, it became standard. AI might be the same—just another tool.”For your PM roadmap, this means:* Expect higher expectations from users.* Deliver faster, smarter workflows.* Don't fight AI—integrate it.TL;DR: Actionable Advice for PMs in Silicon ValleyHere are the five key lessons from my talk with Ben Grubbs that every PM should remember:1. Validate Against the Platform's RoadmapBefore building around YouTube, TikTok, or Instagram, ask: Is this 12 months from being native? If yes, pivot.2. Serve the Top of the PyramidThe most successful creators need full-stack services and strategic guidance—not basic tools.3. Build Brand, Not Just ProductCreators who win big start with brand ambition, not content luck. Align your product roadmap accordingly.4. Separate Creator Talent from CEO SkillsetsGreat creators aren't always great operators. Your org chart needs to reflect that.5. Use AI to Win on EfficiencyAI won't replace you—but the PM who uses AI will. Bake it into production and product from the ground up.Final Thoughts: Betting on the Right Side of DisruptionAs Ben told me:“You want to be on the side of the disruptor. Not waiting to get disrupted.”That's never been truer than in 2025. Whether you're working at a Big Tech platform, building the next venture-backed app, or leading product at a creator startup—this space is still changing fast so go where the puck is going and realize that puck is leaping ahead every month.If you're navigating a challenging PM role or trying to make your next career move in tech, I offer one-on-one coaching through TomLeungCoaching.com. For companies that want to accelerate their product strategy or AI roadmap, check out my advisory work at PaloAltoFoundry.com.OK, enough pontificating. Let's get back to work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

If you had asked me five years ago whether product managers would need to worry about AI-generated job applicants or remote interviews with operatives from North Korea, I would've laughed you out of the room. But here we are. I recently sat down with Shannon Anderson, longtime recruiter and talent scout at Madrona Ventures, for an episode of the Fireside PM podcast. What started as a reaction to a viral LinkedIn post ended up being one of the most wide-ranging, eye-opening conversations I've had on the topic of recruiting, AI, and the future of work. In this post, I want to unpack that conversation for my fellow PMs—especially early to mid-career professionals—because it's not just a hiring manager problem. The game has changed, and you need to play it differently.

If you had asked me five years ago whether product managers would need to worry about AI-generated job applicants or remote interviews with operatives from North Korea, I would've laughed you out of the room. But here we are.I recently sat down with Shannon Anderson, longtime recruiter and talent scout at Madrona Ventures, for an episode of the Fireside PM podcast. What started as a reaction to a viral LinkedIn post ended up being one of the most wide-ranging, eye-opening conversations I've had on the topic of recruiting, AI, and the future of work. In this post, I want to unpack that conversation for my fellow PMs—especially early to mid-career professionals—because it's not just a hiring manager problem. The game has changed, and you need to play it differently.1. The AI Arms Race Has Arrived—in RecruitingOne of Shannon's first points hit hard:“Everything we learned about remote hiring during COVID was a sea change, but it's already obsolete.”AI isn't just being used to help candidates polish their resumes. It's being used to impersonate them entirely. We're seeing fake LinkedIn profiles, AI-altered Zoom video filters, and entire teams coordinating to pass coding screens. In some extreme cases, Shannon shared concerns (echoed by Cisco and others) about foreign actors infiltrating companies via fake hires—not for the paycheck, but for access to corporate IP.And if you think you're safe because you're hiring PMs, not engineers, think again. AI-generated product portfolios, hallucinated case studies, and polished-but-shallow cover letters are already flooding inboxes. As a PM, you need to be aware that your competition isn't just smart—they may be synthetic.2. Fundamentals Still WinEven though tools like ChatGPT can make anyone look great on paper, Shannon makes the case that they can't replace taste or judgment.“You can throw something into ChatGPT and so can I. But if you haven't developed judgment, you won't know if it's good. That's the difference.”This is a wake-up call for early-career PMs. AI can help you draft a PRD or write your resume, but if you can't tell when something feels off, you're at a disadvantage. So don't just use AI to do your job—use it to learn how to do your job better. Treat it like an intern, not your brain.3. Referrals Matter More Than EverOne of the simplest but most actionable takeaways from Shannon was this:“Referrals reign supreme. Warm intros from trusted networks slice through AI noise like butter.”That line stuck with me. Because in a world of keyword-stuffed resumes and AI-generated portfolios, what cuts through is trust. If you're a PM looking for your next gig, your best bet isn't just optimizing your resume—it's cultivating your network. Build authentic relationships with people you admire. Offer to help. Ask for advice. That's how you earn the referrals that will put you on the shortlist.4. Speed and Specificity MatterWhen it comes to hiring, Shannon noted that the best candidates are snapped up quickly, especially in sales and customer-facing roles. This has lessons for product managers too:* Be decisive: If you're a PM hiring a researcher, analyst, or designer, you can't drag your feet.* Be precise: Know what you actually need in the next 30, 60, or 90 days. Shannon emphasized:“If you don't know what you're solving, you'll never know who to hire.”For PMs trying to break into the role, this also means tailoring your pitch. Don't be the generalist applying to every PM role. Be the best fit for a specific company's specific need—and show you understand their business.5. Beware the Amazonification of HiringShannon made a provocative analogy:“Hiring managers want an Amazon shopping experience. Search, shortlist, get reviews, place the order, and return the bad ones.”But people aren't bunion pads. As PMs, we have to resist this mindset—whether we're hiring or being hired. Great hiring takes time. It takes context. It takes iteration. The more we treat talent like widgets, the more we hurt our teams.So what can you do about it?Actionable Advice for PMs in 20251. Always be recruiting. Shannon's mantra for hiring managers applies just as well to candidates. Talk to people. Stay curious. Keep your resume sharp even when you're not looking.2. Build judgment the hard way. Do the work. Write PRDs by hand before prompting AI. Read other PMs' docs. Critique them. Get feedback. Learn what good looks like.3. Use AI—but don't outsource your thinking. AI is great at suggestions. You're responsible for decisions. Treat it as a brainstorming partner, not a crutch.4. Referrals > Resumes. Spend 10x more time building relationships than updating bullets. Help others first. Ask for warm intros. It works.5. Embrace customer-facing roles. If you can't land a PM job, a sales engineer, support, or success role can give you skills in empathy, communication, and product insight. Note from Shannon: If you're at a company with a sales team looking for top-notch sales interns from UW's Foster School's Professional Sales Program, request an intern here.In the end, Shannon reminded us of the most important principle:“You are who you hire.”Check out Shannon's substack here.As PMs, we build our careers and our products the same way: one thoughtful decision at a time. Let's make good ones.If you're looking for 1:1 coaching, visit tomleungcoaching.com. For product consulting and strategy support, visit paloaltofoundry.com.OK. Enough pontificating. Let's get back to work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

Ex-YouTube exec Ben Grubbs reveals how MrBeast, Good Good Golf, and Moonbug cracked the code—and what PMs can learn about strategy, defensibility, and AI's role in the next wave

Hey Team,In the latest episode of the Fireside PM podcast, I had the pleasure of chatting with Jake McKee—one of the early advocates of modern community strategy in tech. Jake's résumé is legit: he's helped companies like Lego, Apple, and Southwest Airlines transform how they engage their most passionate users—not just as customers, but as collaborators. We covered a ton of ground, and I left the conversation with one overwhelming takeaway:"Features can be copied. Community relationships are the true moat."Jake didn't say that verbatim—but he may as well have. If you're an early- or mid-career product manager trying to build something people will love, advocate for, and stick with, then keep reading. This post is packed with practical advice, examples, and yes—plenty of quotes—to help you rethink how you build products.From Plastic Bricks to Passionate BuildersLet's start with Lego. Jake joined the company during a time when the 18+ fan base—the adults building elaborate train sets and sculptures—was considered almost irrelevant. Lego was laser-focused on their core audience: boys ages 7–12.Jake recalled:“They weren't even considered a segment, let alone a priority. When I joined, the adult fans made up 1% of the business. Today it's closer to 45%.”How did that shift happen?Jake and his team didn't just ask adult fans to buy more products—they encouraged them to share their creations, hold public exhibits, and advocate for Lego in the real world. And they did it for free. These superusers weren't incentivized by checks; they were driven by passion. Jake simply gave them tools and encouragement. He even coached them on things like how to invite media to their events or partner with local retailers for promotions.“I was whispering in their ear—‘Have you ever thought about getting the media here? Handing out coupons?' That kind of thing. I was a connector.”For PMs, the lesson is simple: sometimes the most impactful growth strategy isn't a new feature—it's unlocking what your users already want to do.Community Development ≠ Social Media ManagementBefore we go further, let's get clear on what Jake means by “community.”“It's the formal and informal, direct and indirect ways to connect the company with customers in a way that leads to shared positivity for both sides.”This isn't about launching a Discord or running a Twitter account. It's about building systems of feedback, advocacy, and co-creation—structures that allow customers to influence product development, feel heard, and ultimately take pride in your company's success.And it doesn't always require a fancy platform. It might look like a customer advisory board. A monthly AMA with your PMs. A product preview group of superusers giving you feedback at the 75% build stage.It also doesn't require massive budgets.“I'd much rather give somebody a T-shirt that has the program name on it—something we came up with together—than a $100 gift card. The card gets forgotten. The T-shirt gets worn for years.”That example came from his time at Apple, where they created custom luggage tags for top contributors in the support forums. The packaging was signature Apple. The note inside? “Thank you for being on this journey with us.” No gimmicks. Just gratitude.Community-Driven Product Development: The FrameworkJake has developed a system he calls Community-Driven Product Development (CDPD). It's a four-part framework that any product team can apply:* Find the Right PeopleNot just your loudest users, but a cross-section of your audience: new users, power users, skeptics, experts, novices. Diversity isn't just about demographics—it's about experience and perspective.* Right TimingInvolve users at the right phase of the product cycle. During ideation, you might want 3–4 brainstorming partners. At the 75% mark, you might have 40 people test real workflows. Jake stressed the importance of moving beyond “transactional” feedback loops, like one-off surveys, toward relational ones that evolve over time.* Define OutcomesBe clear on what you're trying to learn. Is it usability? Emotional resonance? Feature clarity? Align your engagement format with your research questions.* Design the Right ActivitiesMake participation meaningful and rewarding—not necessarily with money, but with access, voice, and recognition.“The most joy we saw was when our users were talking directly to product managers. And funny enough, the PMs got more energized too. It made the work feel like it mattered again.”Advice for Silicon Valley PMsJake's message to product managers is blunt: You can't outsource community to marketing. You can't delegate empathy to a survey.“I always say: What's the ROI of a conversation? Of a relationship? You can't calculate it with a spreadsheet. But you feel it when it's gone.”If you're in the middle of building something, consider these tactical shifts:* Invite users early. Don't wait until beta to get feedback. Build relationships during ideation and prototype stages.* Create champions. Identify customers who already love your product and ask them to be part of a long-term council or program.* Think about connection, not control. Your job isn't to “manage” the community—it's to help the company be more transparent, accessible, and human.* Narrate the journey. Share the “why” behind roadmap decisions. Let users see the people behind the product.Overcoming Internal ResistanceJake told a story from his Lego days that really stuck with me. Early on, no one in marketing would accept his meeting invites. So he stood outside their offices and waited for their meetings to end—then slipped in for a five-minute chat.“That happened enough times that they figured, ‘He's gonna talk to me anyway—I may as well put him on the calendar.'”The point? Start small. Be persistent. Show the value through stories, not just decks. Find one internal ally who “gets it” and help them shine.He also emphasized starting where you are.“Do something small that you can grow. A T-shirt. A call. A visit. That's your leverage.”The Value of Real RelationshipsOne of my favorite moments from our chat was when Jake described the joy his scale modeling friends bring him compared to showing his creations to his family.“My family says, ‘That's cool.' But my friends? They ask, ‘How did you make that cut? What glue did you use?' They get it. They care.”That's the energy you want between your product team and your users. Not applause. Understanding.In a world where PMs are drowning in dashboards and AI-generated summaries, that kind of emotional signal is rare—and priceless.My Own Experience: Two Projects, Two OutcomesTalking to Jake made me reflect on two product launches I've led in the past decade.In one, we had users in the office every month. We built trust. We showed them early wireframes. We even debated scope and direction together. That product launched smoothly and hit its adoption goals within months.In another, we did a lot of user research—but it was more transactional. Surveys. Interviews. Data. There was a clear wall between us and the users. The product eventually found its footing, but it took longer and didn't inspire the same loyalty.Why? Because in the first example, our users were co-conspirators. In the second, they were “subjects.”Why This Matters NowJake and I talked about AI, and how it's automating more and more of our day-to-day work. The question becomes: What do we do with the time we save?“We're entering a new phase of creative culture. Hobby and craft are more respected now than ever. The next gen gets that.”That applies to users—but also to us. Community work isn't some soft, squishy side project. It's how you future-proof your product and energize your team.“Nobody is loyal to a brand. They're loyal to a belief, an experience, a person. If you want loyalty, build those.”TL;DR: Takeaways for PMsHere's your tactical cheat sheet:✅ Start early. Bring users into the conversation before the roadmap is locked.✅ Build relationships. Find 5–10 users who are willing to go deeper than surveys.✅ Share your why. Don't just ask for feedback—share your constraints and goals.✅ Create artifacts. T-shirts, notes, community-only events—they go further than money.✅ Help your PMs feel human. Let them talk to real users. It will energize the team.✅ Use community to de-risk launches. Your best advocates are built before launch day.✅ Make it sustainable. One-time research projects are fine, but community is a flywheel.Learn more about Jake here.If you found this valuable and want to build a more community-driven product culture at your company, I'd love to help.

We're back with a Startup Spotlight episode on the Fireside PM podcast. It's not every day you get to speak with someone who's straddled the worlds of architecture, gaming, AI, and robotics—and managed to turn those disparate threads into a startup tackling one of the most important problems in our robotic future. Steven Ren, the co-founder and CEO of Palatial, joined me from Lower Manhattan to share the winding journey of his company—from Cornell's architecture school to optimizing simulations for robot training at scale. We went deep on the technology, market evolution, and product insights he's picked up along the way—and there are dozens of takeaways here for early and mid-career PMs, especially those building infrastructure, devtools, or working in AI-adjacent spaces.

I rarely read career books cover to cover. But when I listened to Search in Plain Sight by Somer Hackley, I was hooked. It wasn't a blog post padded into a book—this was the real deal. Structured, thorough, and full of insights that I wish I had twenty years ago.Naturally, I invited Somer onto the Fireside PM podcast to dig deeper. What followed was a masterclass on how executive search firms actually work, what most job seekers get wrong, and how product managers (PMs) can be far more effective in today's hiring market.This post distills our conversation and offers practical takeaways for early to mid-career PMs in Silicon Valley.1. First, Understand the Recruiter's Job Is Not to Get You a JobMost people think executive recruiters are job-finders. They are not."Recruiters are filling positions for the companies that have hired them," Somer explains. "Job seekers think recruiters help them get jobs—that's the No. 1 misconception."Retained search firms, like Somer's, work for companies. Their job is to find the top 5 people in the world for a specific role. They aren't career counselors. If you email them out of the blue asking, "Can you shop me around?" you're starting off on the wrong foot.Instead, try this:* Introduce yourself briefly.* Acknowledge they may not have a role for you now.* Ask to stay in touch and offer something useful (referrals, trends, etc.).Which leads us to…2. Givers Get Remembered"The best way to lodge yourself in someone's brain is when they want to talk to you."If a recruiter reaches out to you about a role, take the call. Even if it's not a fit, this is your shot to build a real relationship. Give them referrals. Share industry insights. Offer to help.Even cold outreach can work—if it's memorable and has value. But better than cold outreach is being referred by someone they trust."Awesome by association is a real thing."Want to stand out in a recruiter's memory months or years later? Make yourself memorable and refer great people. That moves you into the "awesome bucket."3. Shift From Chronology to ClarityMost PMs walk recruiters through their resumes chronologically. Don't.Instead, use the "Think of me when…" framework."I view recruiting as journey matching, not just title or industry matching."What Somer means is this: articulate the kind of journey you help companies with.For example:* "Think of me when you're taking a Series B startup through its first platform rebuild."* "Think of me when you need a PM to lead a 0 to 1 AI product with regulated data."Be specific. Counterintuitively, the more focused your ask, the more opportunities you'll attract."If you say you do everything, you're not memorable. If you're specific, people will actually ask if you can do other things too."Nail your "Think of me when…" and you'll win more attention and more fit.4. Build Momentum Before You're Job HuntingIf you wait until you're actively looking to reach out to recruiters, it's already too late."Check in once a quarter when you're not looking. Keep doing that. Then 10 years go by and you're top of mind."Also, don't expect a quick match. Recruiters have to work with the roles their clients hire them to fill. That may or may not line up with your profile today. So think long term.5. Your Mindset Is Your FoundationThe hiring process is brutally uncertain. You can be perfect for a role and still not get it."It's not always about the perfect fit. Sometimes it's timing, politics, or just who else is in the mix."So how do you stay sane?Somer recommends two things:* Surround yourself with a personal board of champions."People who want you to win."* Use curiosity to stay grounded."If you approach things with curiosity, you'll take the edge off the pressure to impress."I'd add: don't take silence personally. If a recruiter ghosts you for two weeks, it probably has nothing to do with you.6. Be Transparent with Trusted RecruitersShould you tell a recruiter if you're not sure about a role? Or if you're juggling other offers?Somer says yes—if the recruiter seems trustworthy and aligned."If I put you forward, I want you to win. So tell me what's really going on. Then I can help position things properly with the client."Good recruiters aren't trying to lowball you. They're trying to avoid surprises that make everyone look bad."Let us be your buffer."The caveat: if you get a bad vibe, trust it. Not every recruiter is great. But when you find one who is, work with them, and be honest.7. In Final Rounds, It's About RiskIf you make it to the last stage of interviews, here's the real secret:"They're looking for the safe choice. Not the flashiest."That means:* Be likable.* Be prepared.* Show you've done this kind of thing before.* Ask smart questions that show you understand what success will really take.As a former hiring manager at Google, I can confirm: often, multiple candidates are great. The final choice often comes down to small things: a strong reference, cultural fit, or someone who just de-risked themselves better.8. Own the Compensation ConversationSomer's advice here was nuanced and spot-on.* Talk about comp early and often.* Don't wait until the offer.* Create clarity about your expectations and what you'd be walking away from."It's a multi-channel conversation. We're talking comp on the first call, the second, the fourth. I want to make sure the offer you get will be accepted."Use tools like:* What offers you're currently seeing* What equity you're leaving behind* Comp benchmarks from recruiters or friendsAnd always be clear on your own ask:"You don't have to give a single number. Just be prepared with ranges that reflect your walkaway points."9. Don't Be Afraid to Ask Hard QuestionsCandidates often avoid asking tough questions late in the process. They worry about seeming ungrateful or negative.But:"Asking good questions gives the client comfort that you're thinking about this the right way."Ask about challenges, gaps, political realities. Ask what's not working. If this role might be yours, you need to know. And you earn respect by showing you want to succeed, not just land the job.10. After You're Hired: Stay in TouchRecruiters who place you can become allies for life. Keep the relationship warm."Once you can text someone, it's easy to stay in touch."You never know when you'll:* Build a team and need help hiring* Be looking again* Have someone to referA short "Thinking of you" or "Saw this post and thought of you" goes a long way.Final ThoughtsThis conversation was packed. If you haven't already, pick up Somer's book Search in Plain Sight or listen on Audible. You'll walk away smarter, more grounded, and better prepared to navigate your next search.I'll leave you with this:“Most people show up saying 'Here's my bio.' The best ones show up saying 'Think of me when…'”Let that guide how you introduce yourself from now on.If you're navigating your next big career move or want guidance on positioning yourself more strategically, I offer 1:1 coaching at tomleungcoaching.com.If you're building out a product org and need help hiring or structuring the team, visit paloaltofoundry.com for consulting options. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

I rarely read career books cover to cover. But when I listened to Search in Plain Sight by Somer Hackley, I was hooked. It wasn't a blog post padded into a book—this was the real deal. Structured, thorough, and full of insights that I wish I had twenty years ago. Naturally, I invited Somer onto the Fireside PM podcast to dig deeper. What followed was a masterclass on how executive search firms actually work, what most job seekers get wrong, and how product managers (PMs) can be far more effective in today's hiring market.

Early to mid-career product managers in Silicon Valley often dream of landing the perfect job—high comp, strong team, great product, and a clear path for impact. But what if I told you that sometimes the smartest move is walking away?That was the case for Elizabeth Hague, a seasoned marketing leader with two successful exits under her belt. She recently turned down a VP of Marketing role that came with a $350K offer, and her reasoning provides invaluable lessons for navigating today's brutal job market.This post is packed with her insights, specific examples, and actionable advice to help you avoid career missteps and make smarter choices as you navigate your next big move.Lesson 1: "You Have to Market Yourself"One of the first points Elizabeth made in our conversation was how ironic it is that even experienced marketers struggle to market themselves. And that's true for product managers, too. The hiring market is not what it was in 2017, when smart generalists could land jobs with strong interview skills and broad expertise. Today, hiring managers want hyper-specific, battle-tested experience in their exact industry and problem space."It's an employer's market right now, especially in B2B SaaS. Any small thing can be a reason for rejection," Elizabeth said. "If you're not putting real effort into marketing yourself, refining your personal brand, and strategically positioning your experience, you're already behind."Takeaway: If you're on the job hunt, think about how you're presenting your skills. Are you crafting your story in a way that aligns with what hiring managers are actually looking for? Use data, case studies, and specific examples to sell your impact—not just a list of job titles.Lesson 2: Beware the "Cinderella Fit" TrapElizabeth and I both noted how today's hiring market is much more rigid than in past years. "This is not a market where a hiring manager says, 'Oh, this person is smart and driven, they can figure it out,'" I said. "They want someone who has done this exact job before, maybe even at a bigger scale. They can afford to be that picky."This is why so many PMs struggle to break into new domains or level up into leadership roles. Companies often have 500+ applicants per job, so they optimize for the path of least resistance—hiring the safest, most obvious choice.Takeaway: If you're trying to make a jump—whether it's into leadership, a new industry, or a new function—you need to be strategic. Build bridges, seek out internal opportunities to gain experience before you switch, and cultivate relationships with decision-makers who can vouch for you.Lesson 3: How to Spot Red Flags in Job OffersElizabeth's experience turning down a VP job was a masterclass in knowing when to walk away. She identified multiple red flags in her interview process:* Unrealistic Growth Goals: The company expected to 10X revenue in 12 months but had no product marketing team, no demand gen, and had shut off all paid ads.* Underinvestment in Key Functions: The entire marketing budget—including headcount—was just $1M.* High Turnover: The previous VP was fired, and the team was described as "low performers." That's often code for "leadership doesn't know how to support and develop talent."* CEO With a Misaligned Vision: "When I asked if these aggressive goals came from the board or him, he said they were his own," Elizabeth noted. That suggested an executive with unchecked expectations."If I didn't have my internal list of non-negotiables, I might have ignored these signs and taken the job," she admitted. "It's really easy to rationalize a risky decision when you're in the moment."Takeaway: Before you take an offer, do your diligence. Ask about resourcing, past performance, and leadership expectations. If the math doesn't add up, trust your gut.Lesson 4: The "Honeymoon Discount" and Why You Should Apply ItWhenever I coach product managers on career decisions, I recommend applying a 30% honeymoon discount—whatever you think the job is, assume it's at least 30% harder, messier, and more dysfunctional than it appears."No matter how much diligence you do, there will always be surprises once you're inside," I said in our discussion. "And I have never seen a situation where a job turns out to be better than expected."Takeaway: When evaluating an offer, don't assume best-case scenarios. Consider worst-case risks and be sure you're comfortable with them before signing on.Lesson 5: When It's Okay to Take a "Less Than Ideal" JobNot everyone has the luxury of turning down offers. Some people need to get back in the game, rebuild confidence, or simply pay the bills.Elizabeth acknowledged this, saying: "I got a few angry comments on my LinkedIn post—people saying, 'Must be nice to turn down that money!' And I get it. But I wasn't willing to sacrifice my health and sanity for a role I knew was set up to fail."I also noted that some people take jobs just to “ride the cow while looking for the horse” (an old Cantonese saying). Some PMs strategically take an imperfect job to get back in the market while continuing their search."It's a totally valid approach, as long as you go in eyes wide open and set your own expectations accordingly," she said.Takeaway: There's no shame in taking a suboptimal job if it meets an immediate need. Just be clear on your own boundaries and don't let short-term survival mode dictate long-term career decisions.Final Thoughts: The Career Playbook for Today's PMsThe job market today is tougher than it's been in years. But that doesn't mean you should settle for roles that will burn you out or set you up for failure.Key takeaways:✔ Market yourself strategically—don't assume your resume speaks for itself.✔ Be aware of how the hiring market has changed—"Cinderella Fit" roles dominate.✔ Spot red flags early—don't wait until you're six months in to realize the job is a disaster.✔ Apply the "honeymoon discount"—assume every job will be harder than it looks.✔ If you must take a less-than-perfect job, do it intentionally and keep your options open.If you're a product leader looking for 1:1 career coaching, check out TomLeungCoaching.com. And if you're at a startup needing product strategy consulting, visit PaloAltoFoundry.com.Follow Elizabeth on LinkedIn.As always—let's get back to work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

Earlier on the Fireside PM podcast, I sat down with Carl Wu, a veteran product leader who built and launched an AI-first product from scratch—targeting one of the most conservative and risk-averse professions out there: immigration law.Carl's story isn't just a case study in GenAI product development. It's a case study in how technical intuition, product fundamentals, and real-world empathy for users come together when you're building for high-stakes use cases. If you're building (or planning to build) AI-native products—especially in a vertical domain—this one's for you.From Code to Customer: Carl's Unusual ArcCarl started his career as an engineer at Microsoft before transitioning into product. He later built search engines at Tencent and led teams building video and ML-powered systems at startups.His technical fluency isn't just a badge of honor; it's the lens through which he approaches product thinking. "The biggest mental switch," he said, "was thinking less about system optimization and more about user optimization. But having that technical foundation helped me build credibility and intuition."That background came in handy when he joined a legal-tech startup as their founding AI PM, tasked with turning foundational models into real customer value.AI is Powerful. PM Fundamentals Still Matter More.Carl didn't come in trying to train the biggest model or chase the buzziest trends. His first question was simple: What's the most painful, expensive problem we can solve with this tech?That led to a set of vertical AI theses:* Focus on domains where language is the product* Prioritize workflows with high structure and high stakes* Use the LLM for synthesis, drafting, and structured transformationLegal fit perfectly. Immigration law, in particular, had everything he wanted: repeatable document types, expensive expert time, and huge amounts of unstructured data ripe for automation.Carl explained:"We were working in immigration law, and saw that some law firms were outsourcing their drafting to journalists because the petitions were so complex. That was the lightbulb. If someone is paying a human writer to stitch together legal arguments, an LLM might be able to help."That insight narrowed the use case to a single visa type—one that law firms actively avoided because of the overhead.Actionable Advice: Find the Burning ProblemToo many PMs start with the model and go hunting for a problem. Carl did the reverse:* Pick a high-value domain* Talk to users (lawyers)* Observe workflows* Identify pain so acute that firms were outsourcing or avoiding itTakeaway for PMs: Your GenAI MVP shouldn't be an experiment. It should be a wedge into a critical workflow where users already know they need help.Taking the Technology Risk So the User Doesn't Have ToCarl had a tough call to make: Should they require users to fill out guided prompts and forms, or should they lean fully into autonomous generation from source docs?He chose the latter, betting that removing all user friction—even at the cost of increased technical risk—would pay off."I decided that in a 0-to-1 product, especially one this disruptive, we should optimize for user experience and absorb complexity on the system side."The result? Documents that used to take lawyers six months to draft could now be generated and reviewed in 48 hours.Prompt Engineering Is a System, Not a SkillOne of the most eye-opening parts of our conversation was how Carl talked about prompt systems. Not as static prompts. Not as clever tokens. But as a full-stack orchestration layer that included:* Smart retrieval from unstructured documents* Chained prompts and intermediate reasoning steps* Evaluation systems to assess output quality"It's not just writing a good prompt," Carl said. "You need a full evaluation stack. In our case, that included using GPT-4.5 as an evaluator model to score drafts generated by cheaper, faster models."For example:* Drafts were scored on legal logic, writing style, and argument rigor* Outputs were linked back to citations and source documents to reduce hallucinations* Users could rate and comment on individual sections to create a feedback loopPro tip for PMs: Build your evaluation stack early. Hallucinations are product-killers in high-trust domains. Don't rely on vibes.Integration and Compliance Are Features, Not AfterthoughtsOne of the hardest parts of going from demo to deployment was integration with legacy systems—and gaining trust from clients concerned about privacy and compliance."Clients are asking new questions now. Who trained your model? Where is the data stored? How do we know our documents aren't being used to retrain the model?"This is where Carl's vertical AI strategy paid off. By focusing on a niche domain, the team could:* Build tight integrations with specific case management tools* Offer clear guarantees around data residency and model usage* Design workflows that mirrored existing processes, not replaced themWhat Carl Would Do DifferentlyDespite the success, Carl reflected on one thing he might have underinvested in:"In hindsight, I think we could've done more on the user experience layer. Not just the data outputs, but how those outputs are presented, edited, and refined by the user. UX is perception. And perception is reality."He pointed to Midjourney as an example:* Many models can generate images* But Midjourney added affordances like zoom, re-prompt, and edit* That made the tool feel alive, adaptable, and human-friendlyTakeaway: Don't treat UI as a wrapper. It's a co-pilot.What PMs Get Wrong About AIWe wrapped up the conversation with one of my favorite questions: What do most PMs get wrong about AI?"PMs overestimate what AI can do and underestimate the importance of the core use case. Just because it feels magical doesn't mean you can skip the fundamentals."In other words:* Don't get blinded by novelty* Solve a real, valuable problem* Make it work before you make it scaleFinal Thoughts: It's a Golden Age for Scrappy BuildersCarl ended our conversation with a quiet bombshell:"Five years ago, people would assume you'd need a 30-person team to build this. Today, a handful of builders can launch vertical AI startups serving million-dollar use cases."That stuck with me.We're not just witnessing the rise of foundational models. We're seeing the birth of a new generation of product teams—tiny, focused, fast-moving, and capable of punching way above their weight.If you're early in your PM journey, and you want to be part of this shift:* Learn the fundamentals (value, user pain, workflows)* Embrace ambiguity (AI is still unpredictable)* Be technical enough to evaluate what's feasible* Be empathetic enough to know what mattersAnd if you want help accelerating your journey, I offer 1:1 coaching at tomleungcoaching.com and product consulting services at paloaltofoundry.com.Let's get back to work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

All right, what's going on, team? We are back on the Fireside PM podcast, and today I want to share some hard-earned insights on applying to tech startup accelerators. I just finished reviewing over 80 applications for UC Berkeley SkyDeck and Stanford GSB's summer entrepreneurship programs, and I have a ton of thoughts on what makes applications stand out—and what sends them straight to the 'no' pile.If you're a founder looking to get into one of these programs (or even just raise pre-seed money), listen up. Because after reading and rating all these applications, I've spotted clear patterns in what works and what doesn't.Why This MattersWhether it's Y Combinator, Techstars, or a university-backed accelerator, getting into a top program can significantly change your startup's trajectory. It's not just about funding; it's about credibility, mentorship, and an alumni network that can open doors. But the competition is fierce, and most applications don't make the cut.I'm sharing my perspective not as an official spokesperson for these programs, but as someone who has been on the selection committees. These insights can give you a better shot at getting accepted—or at least prevent you from making rookie mistakes.The Harsh Reality: Most Applications Are MediocreThe first thing that struck me was how many applications were painfully generic. "We are building AI-powered solutions for X." Great. So is everyone else. The reality is:"Most applications don't stand out because they don't make me believe this team is the one to solve this problem."The best applications convinced me that the founders deeply understood the problem, had unique insights, and were doing something difficult yet compelling.1. Show, Don't Tell: Your Idea Is Not EnoughA huge mistake I saw was founders assuming their idea alone was enough. Just having an idea—even a great one—isn't a differentiator. Execution and traction matter."If you're pre-product and pre-revenue, you better have a crazy impressive background or some early traction that proves you're not just another person with a PowerPoint."Some founders just threw in a generic problem statement and a solution slide without showing any proof that they could execute. The best applications showed:* Early customer interest (waitlists, LOIs, pre-sales)* Prototypes or MVPs* Unique industry insights that others don't haveOne application that stood out came from a founder who had already hacked together an MVP and had 100 users testing it. Another had letters of intent from two Fortune 500 companies. Those got a second look.2. Make Your Founder Story Work for YouEvery founder has a story, but not all stories are compelling. A strong application makes it clear why you are uniquely suited to solve this problem."The best applications make me think: ‘Of course this person should be doing this startup.'"If your background doesn't directly tie to your startup, find a way to make it relevant. Maybe you've spent 10 years in the industry and have insights others don't. Maybe you built something similar before. Maybe you have an unfair advantage in distribution. Whatever it is, highlight it.Weak applications left me wondering: why this person? Why now? If I can't answer that, you're in trouble.3. Specificity Wins: Avoid the ‘AI-Powered' TrapA major turn-off was vague, buzzword-heavy descriptions. If your pitch is "We use AI to optimize X," without specifics, it's a red flag. AI is a tool, not a strategy. What exactly are you doing that others aren't?One founder wrote:"We use AI to improve customer service experiences."That's meaningless. Compare that to:"Our AI-driven chatbot for e-commerce brands has reduced support ticket volume by 37% in our pilot with three Shopify stores."The second one gets my attention.4. Big Market? Show Your MathMost applications claim they're tackling a multi-billion-dollar market, but few show how they get there. The best applications broke it down:* TAM (Total Addressable Market): The total demand if everyone in the world used your product* SAM (Serviceable Available Market): The segment you realistically reach with your distribution model* SOM (Serviceable Obtainable Market): The share you can actually capture in the next 3-5 years"If you just throw a $10B market size number without context, I assume you're making it up."Show your math, cite real sources, and make me believe your assumptions.5. The Team Section Can Make or Break YouSome of the strongest applications had killer teams. Not just impressive resumes, but complementary skill sets that made sense together."A red flag is when it's all business folks and no one technical, or vice versa."One startup had two MBAs and no engineer. Another had four engineers but no one who had ever sold anything. That's a tough sell. If you have a gap, acknowledge it and explain how you'll fill it.The Applications That Got a ‘Yes' From MeWhile most applications were forgettable, a few stood out. Here's why:* Traction: Even a tiny bit of real-world validation (a waitlist, a pilot customer, an MVP) made a difference.* Deep market understanding: They articulated why now and why them with clarity.* Clear problem-solution fit: They explained the pain point in a way that made me nod in agreement.* Compelling team: The founders had unique experience or skills that made them credible.Final Thoughts: Get the Basics RightI get it—applying to accelerators is tough, and competition is brutal. But too many founders shoot themselves in the foot by submitting weak applications."If your startup idea doesn't feel inevitable after reading your application, you're not ready."Before you hit submit, ask yourself:* Would an outsider instantly understand why this idea must exist?* Does my traction (or background) de-risk my ability to execute?* Is my founder story compelling?* Have I removed all jargon and made my pitch crystal clear?If the answer isn't a strong "yes" to all four, keep refining.And if you want personalized guidance on your product or startup strategy, check out my 1:1 coaching practice at tomleungcoaching.com and my consulting work at paloaltofoundry.com.Let's get back to work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

I recently had a fascinating conversation with Rodolfo, a Senior Product Manager at Spotify and a good friend from my days mentoring at Harvard Business School. Rodolfo shared a powerful insight into nailing product management interviews, particularly valuable for anyone early to mid-career in Silicon Valley or looking to break into tech. His experience underscores something I frequently coach my own clients about: how you think is more important than what you think.When Rodolfo shared a LinkedIn post and Substack article detailing an interview hack he'd discovered, I knew it was too good to keep to ourselves. Here, I'll break down the core idea, share key quotes from Rodolfo, and offer actionable advice on applying his insights in your career journey.Rodolfo's Journey to Product ManagementRodolfo's path into product management wasn't a straight line. He started in consulting and quickly realized it wasn't his passion. His first real taste of tech came through an operations role at Facebook, which eventually opened his eyes to product management:“Working closely with PMs at Facebook opened my eyes. I started taking on PM tasks and growing into the role by shadowing and volunteering for extra work—essentially making my own PM apprenticeship.”This proactive approach served him well. He transitioned to a PM role at Reddit, pursued an MBA at Harvard, and later joined Cameo to develop deeper business and product skills. Today, Rodolfo leads a zero-to-one team at Spotify, building new user acquisition products—his “dream job,” given his passion for music.Why Product Management?When I asked Rodolfo why he ultimately chose PM, his reasons were relatable:"As someone who thrives on ambiguity and enjoys navigating people, product management was a perfect match. I love switching contexts throughout the day—engineering, design, business strategy—it's never repetitive."This diversity is appealing, but he cautions:“Don't jump into PM just because it's the hot thing. You need a hypothesis about why you're doing it, and then actively test it. Intern, volunteer, create something yourself—don't wait for an official onboarding path.”This mirrors my experience advising aspiring PMs: those who wait for structured training or perfect circumstances often miss out. The role itself demands proactive initiative and the courage to make things happen.The Interviewing Breakthrough: Clarity of ThoughtRodolfo described his early struggles with PM interviews. Despite feeling competent in day-to-day product work, he often stumbled when interviewing because he focused too much on frameworks and getting the "right answer." His breakthrough came during an interview practice with a friend, who bluntly told him:“I'm having trouble following your thought process. Can you explain your steps more clearly?”That simple feedback was Rodolfo's "aha moment." He realized the key to acing interviews isn't necessarily arriving at the perfect solution immediately but clearly articulating the reasoning behind each step of your process.The PM Interview Hack: Communicate Your ThinkingHere's Rodolfo's hack for improving PM interview outcomes:1. State your assumptions clearly:* “I'm assuming Disney Parks and Resorts wants me to focus on enhancing physical experiences rather than digital-only products. Does this align with your expectations?”2. Articulate each step of your process explicitly:* “I've identified that Disney has underutilized assets after closing hours. This might represent untapped revenue opportunities. Let's explore that.”3. Check in frequently:* “Does this approach make sense? Are these user segments resonating with you?”3. Self-correct visibly:* If you sense misalignment, pause and say, “I think I might be veering off course. Can you clarify if I'm addressing your question directly?”This practice accomplishes two critical objectives:* Ensures the interviewer understands your logic and communication style.* Demonstrates your adaptability, a vital skill for PMs dealing with ambiguity.Real-World ApplicationRodolfo emphasized this isn't just an interview technique; it's foundational to successful PM work:“If someone can't follow your thought process in an interview, they won't follow it at work. Being clear in your thinking is essential to rallying cross-functional teams, convincing stakeholders, and leading effectively.”Indeed, clear communication can differentiate you significantly, especially as your career progresses into roles requiring greater alignment, influence, and strategic clarity.Interviewing Mindset MattersYour mindset during interviews matters tremendously. If you approach it like a high-stakes test, anxiety and rigidity often sabotage performance. Rodolfo and I agreed that treating interviews more like collaborative working sessions makes candidates more successful. As I frequently advise:“Treat your PM interview as a collaborative workshop, not a final exam. Engage your interviewer as if they're a colleague you're collaborating with to solve interesting problems.”Three Quick Actionable Tips for PM Interview Prep:1. Practice transparent thinking:Simulate interviews by verbalizing your reasoning aloud at every step.2. Ask clarifying questions proactively:This demonstrates confidence and ensures alignment throughout the interview.3. Research your target companies deeply:Demonstrating specific knowledge about recent company initiatives or competitors shows genuine interest and sets you apart.Quotes to Remember:* “Nailing an interview is more about the how than the what.”* “If someone can course correct during an interview, it almost makes them a better hire than someone who had the right answer from the start.”* “You get promoted as a PM not just because of results but because of how you achieve those results.”Final ThoughtsRodolfo's insights highlight the foundational importance of clear thinking and communication, essential skills for anyone aspiring to grow in product management. Embracing these practices can dramatically shift your interviewing—and career—trajectory. Subscribe to Rodolfo's substack here.Keep Growing Your Product CareerIf you found this conversation helpful and want to dive deeper, I offer personalized 1:1 coaching specifically tailored for product management professionals. You can find out more and book sessions at tomleungcoaching.com.Additionally, if your organization needs support with product strategy, hiring talented PMs, or PM onboarding and training, visit paloaltofoundry.com to learn about my product management consulting services.OK, now let's get back to work! This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

What Lego, Apple, and a golf startup can teach Silicon Valley PMs about designing with—not just for—your users. https://jakemckee.com/

AI is transforming product management, but not everyone is using it effectively. Too many product managers treat AI as a glorified autocomplete—something that speeds up basic tasks but doesn't fundamentally change their workflow. But after my conversation with Mustafa Kapatiya, a former Google executive and AI consultant, I walked away convinced that the best PMs aren't just using AI—they're redefining their entire approach around it.Mustafa has been deep in the trenches, helping product teams harness AI to maximize efficiency and impact. He shared insights from working with organizations that are getting it right—and from those that are stuck at the surface level, frustrated that AI "just doesn't get it." The difference? Knowing how to ask the right questions, structure inputs properly, and train AI to think like your best-performing team members.Why Most PMs Are Stuck in the Shallow EndMost product managers start with AI the same way they started using Google Docs or Jira—it's a tool, not a game-changer. They pop open ChatGPT or Claude, ask for a quick summary, maybe a user story template, and move on. Mustafa has seen this pattern again and again:“Most PMs use AI in a very surface-level way. They play around with ChatGPT, get some decent results, but then get frustrated when AI ‘doesn't get it.' The reality is, they're not using even 20% of what AI can actually do for them.”The key distinction between elite PMs and the rest? Elite PMs don't just ask AI for one-off answers. They integrate it deeply into their workflow. They train it to understand their company's OKRs, their team's strengths and weaknesses, and the nuances of how decisions get made.“Top PMs think about AI in three key dimensions: speed, quality, and effort. They don't just use it to go faster—they use it to produce better work and to minimize the time they personally spend on low-leverage tasks.”AI as Your Second BrainImagine you're a PM trying to make sense of customer feedback from hundreds of app reviews. The average PM might copy-paste a few into ChatGPT and ask for sentiment analysis. The great PM, on the other hand, does something entirely different. They:* Train AI on their past decisions, OKRs, and company priorities.* Give AI structured data and ask for a synthesized, weighted summary.* Use AI to determine which insights actually move the needle, rather than just producing a generic report.“If you ask AI the wrong question, you get a generic response. If you train it on your context, give it structured inputs, and refine its responses, it becomes a true second brain. That's where the magic happens.”Mustafa demonstrated this in real time during our chat. He uploaded raw Figma app reviews into Claude, structured a thoughtful prompt, and within minutes, AI produced a highly actionable summary: key pain points, frequently requested features, and a breakdown of sentiment trends. But he didn't stop there. Instead of just handing that report off to stakeholders, he used AI to determine which insights mapped to team OKRs and who on his team needed to see them first.This is where AI becomes more than a speed tool—it becomes a decision-making engine.The New Playbook for AI-Powered PMsSo how do you move from surface-level AI use to best-in-class execution? Mustafa outlined three core shifts that separate the best from the rest:1. Write Better Prompts (And Reuse Them)Most PMs write one-off prompts each time they need AI to do something. The best PMs treat prompts like reusable assets, refining and improving them over time. Mustafa has even built a PM Playbook—a collection of prompts that cover everything from user research to roadmap prioritization.“You should never be writing the same AI prompt from scratch every time. Write it once, refine it, and reuse it. A great prompt is like a great framework—it saves you hours every week.”2. Train AI on Your ContextIf AI doesn't understand your company, your team, and your unique challenges, it's going to spit out generic advice. The best PMs create “digital twins”—structured datasets that teach AI about their org structure, key stakeholders, and product priorities.“I train my AI coach on five key dimensions: company context, my role, team structure, product specifics, and my strengths/weaknesses. This allows AI to give me insights that feel deeply relevant, rather than just surface-level observations.”3. Use AI to Navigate Organizational ComplexityPMs don't just build products—they navigate company politics, stakeholder expectations, and resource constraints. AI can be a powerful tool for this. Mustafa showed how he uses AI to analyze who in his org is most likely to support or resist a given initiative, helping him craft better pitches and build alignment faster.“One of my favorite use cases? AI as a political coach. It helps me figure out how to frame conversations, who to bring in early, and how to avoid roadblocks before they happen.”The Future: Leaner, Smarter Product TeamsAI isn't just changing how PMs work—it's changing who gets hired and how teams are structured. I shared a hypothesis with Mustafa: what if, in the near future, a small team of elite PMs, deeply trained in AI, could outperform a traditionally structured product org with layers of GPMs, APMs, and specialists?Mustafa agreed—and took it a step further:“I actually think we're about to see a huge shift in how product teams are structured. Instead of large teams with lots of layers, we'll see small groups of highly effective PMs, each managing multiple products with AI as their co-pilot.”If this happens, the role of the PM will evolve. Instead of spending 80% of their time on documentation, synthesis, and reporting, PMs will focus on decision-making, strategy, and creativity. AI will handle the grunt work—PMs will steer the ship.What This Means for YouIf you're a PM today, this shift is already happening. The question is: are you ahead of the curve, or are you still treating AI like a toy?Here's what you can do today:* Start treating AI as a second brain, not a search engine. Train it, refine it, and make it work for you.* Build your own AI playbook. Save and refine the prompts that work. Share them with your team.* Use AI to navigate your organization, not just write documents. It can help you build alignment, anticipate roadblocks, and move faster.Mustafa and I barely scratched the surface in our conversation, but one thing was clear: the PMs who master AI will have an unfair advantage. The ones who ignore it? They'll be left behind.If you're serious about leveling up, I highly recommend checking out Mustafa's AI playbook and following his work on Substack and LinkedIn. And if you want to get direct coaching on AI-driven product management, feel free to reach out.The future belongs to PMs who know how to work with AI. Are you ready?Mustafa's Free Assessment (limited seats): https://bit.ly/4kesaVjMustafa's Linkedin: https://www.linkedin.com/in/kapadiamustafa/Tom's Coaching Page This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

How to Avoid Career Pitfalls and Make Smarter Moves in Today's Job Market Early to mid-career product managers in Silicon Valley often dream of landing the perfect job—high comp, strong team, great product, and a clear path for impact. But what if I told you that sometimes the smartest move is walking away? That was the case for Elizabeth Haig, a seasoned marketing leader with two successful exits under her belt. She recently turned down a VP of Marketing role that came with a $350K offer, and her reasoning provides invaluable lessons for navigating today's brutal job market. This post is packed with her insights, specific examples, and actionable advice to help you avoid career missteps and make smarter choices as you navigate your next big move.

Hiring a Great Product Leader Is Harder Than You ThinkTeam, we're back on the Fireside PM podcast, and today, I want to talk about a topic that keeps coming up: why even experienced executives struggle to hire strong product leaders. If you're a CEO or CPO at a mid-to-late-stage company and you need to hire a killer Director or VP of Product, this post is for you.You go through the hiring process, extend an offer to someone who looks amazing on paper—only to realize months later that it's not working out. Sound familiar?The good news? Most hiring failures happen because of a handful of predictable mistakes. Let's break them down, one by one, so you can avoid them next time.Mistake #1: Trying to Prove How Smart You AreExecutives sometimes treat interviews as a stage to showcase their own expertise. Instead of assessing candidates effectively, they dominate the conversation with industry insights or theoretical debates."We had one hiring manager who spent most of the interview explaining his product strategy instead of evaluating the candidate's thinking. It turned into a monologue."How to fix it: Think of interviews as a collaborative exploration, not a quiz show. Instead of trying to stump candidates with trick questions, create space for them to showcase how they think and solve problems. Ask open-ended questions like, ‘How would you approach building X in our business?' and let them take the lead.For candidates: If an interviewer starts flexing their knowledge too much, try steering the conversation back to your experiences by asking, ‘That's really interesting—here's how I've tackled something similar. How do you think that approach would work here?'Mistake #2: Accepting Surface-Level AnswersGreat PMs don't just recite frameworks—they demonstrate depth in their thinking. But too many hiring processes settle for polished, rehearsed answers rather than pushing for real insights."We hired a candidate who sounded great in the interview, but once they were on the job, we realized they couldn't actually navigate ambiguity."How to fix it: Don't stop at the first answer. Dig deeper:* What was challenging about that situation?* Why was it challenging?* What did you learn, and what would you do differently?Look for signals of intellectual honesty and self-awareness.For candidates: Expect follow-ups. Instead of giving a generic “here's what I did” response, add layers of reflection: ‘Here's what I did, what was difficult about it, what I learned, and how I'd refine it next time.'Mistake #3: Not Testing for True Product SenseThere's a big difference between a good PM and a great one. Good PMs can apply best practices and tweak existing products. Great PMs spot breakthrough opportunities that others miss."We realized too late that the person we hired was great at incremental improvements but struggled to think big."How to fix it: Give candidates real-world problems and see how they think. Ask:* How would you improve X feature in our product?* What's an underserved user need in our market?* How would you prioritize trade-offs between short-term execution and long-term vision?The best candidates don't just apply frameworks—they generate novel insights that connect market needs, user behavior, and technical possibilities.For candidates: Show that you can think beyond standard playbooks. When discussing past work, highlight moments where you spotted opportunities others missed.Mistake #4: Failing to Provide Real-Time FeedbackA lot of hiring managers expect candidates to read their minds. But vague questions and unclear expectations lead to wasted interviews and misjudged candidates."We almost passed on a great candidate because they started out with rambling answers. But once we gave them direct feedback, they nailed it."How to fix it: Give candidates real-time guidance:* If a candidate is being too verbose, gently ask them to summarize in two minutes.* If they misunderstand a question, clarify what you're looking for.* If they struggle with structure, let them know you'd like a more formatted response.The goal is to assess a candidate's ability to learn and adjust, not just their ability to perform under perfect conditions.For candidates: If an interview feels unclear, ask for guidance: ‘Would you like a structured breakdown, or a high-level approach?' Adapt based on their response.Mistake #5: Forgetting That You're Being Interviewed TooThe best PMs have options. If your interview process feels adversarial, disorganized, or uninspiring, top candidates will walk."We lost a great candidate because they said our process felt chaotic and that we weren't aligned on what we wanted."How to fix it:* Be respectful of their time. Don't drag out the process with endless rounds.* Showcase your team culture. Let candidates meet potential colleagues in a way that feels engaging, not like a test.* Sell the role. Top candidates need to know why this is an exciting opportunity for them.For candidates: If a company treats you poorly during interviews, that's a preview of how they'll treat you on the job. Pay attention to red flags.Final Thoughts: Hiring Great PM Leaders Takes More Than LuckThe best product leaders don't just fall into your lap—you have to create a hiring process that identifies them effectively. Avoid these five mistakes, and you'll:* Attract stronger candidates.* Get a clearer picture of their real capabilities.* Increase your offer acceptance rate.* Build a world-class PM team that drives results.If you're a CEO or CPO looking to make a high-impact product hire, or if you want expert guidance on hiring strategy or need help with a can't miss search campaign, I offer product management consulting and contingent searches where I personally vet all candidates at paloaltofoundry.com.Thanks. Now get back to work :-) This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

Lessons from the Fireside PM podcast on how to stop missing top-tier candidates and make your next VP or Director of Product hire a game-changer.  Hiring a Great Product Leader Is Harder Than You Think Team, we're back on the Fireside PM podcast, and today, I want to talk about a topic that keeps coming up: why even experienced executives struggle to hire strong product leaders. If you're a CEO or CPO at a mid-to-late-stage company and you need to hire a killer Director or VP of Product, this post is for you. You go through the hiring process, extend an offer to someone who looks amazing on paper—only to realize months later that it's not working out. Sound familiar? The good news? Most hiring failures happen because of a handful of predictable mistakes. Let's break them down, one by one, so you can avoid them next time.

Why revealing your thinking matters more than your final answer—insider secrets from Rodolfo, Senior PM at Spotify. https://rodolfodays.substack.com/?utm_source=substack&utm_medium=web&utm_campaign=substack_profile

Alright, team—we are back on the Fireside PM podcast, and this time, I had the privilege of speaking with Dave Lu, a veteran in tech and one of the most influential voices in the AAPI founder ecosystem. Dave's career spans Yahoo, Apple, eBay, startups, and venture capital, and in our conversation, he shared his journey and insights on breaking barriers, fostering a strong AAPI network, and navigating leadership as an Asian American in tech.This was a fascinating discussion, and I want to highlight some key takeaways, especially for product managers, startup founders, and anyone looking to advance their career in tech while navigating systemic challenges.From Consultant to PM to Founder: Dave's JourneyDave's path started with finance at Wharton, followed by a brief stint in consulting before realizing it wasn't for him. He pivoted into product management at Yahoo Finance, back when Yahoo was still under 1,000 employees and Jerry Yang sat just around the corner.“It was probably one of the best jobs I've ever had. The team that was there went on to do amazing things.”After Yahoo, personal circumstances led Dave back to New York, where he joined Sony before heading to Stanford GSB for his MBA. From there, he worked at Apple and eBay in product strategy before taking a big leap into startups. His ventures included FanPop, a consumer community platform, and Paired, a labor marketplace for restaurants.“I realized early on that I needed to build something of my own. I didn't want to wait for someone to promote me—I wanted to take control of my career.”The Power of an AAPI Founder NetworkWhile running his startups, Dave noticed a fragmentation in the AAPI founder community. Unlike other groups—Jewish founders, South Asian entrepreneurs—there wasn't a strong network for East Asian and Southeast Asian founders. So, in 2011, he started an informal dinner group with eight founders. That group eventually grew to 200+ members, including the likes of Tony Xu (DoorDash) and Eric Yuan (Zoom).“I'm a firm believer that without a strong network, you can't succeed. That's how you meet investors, hire talent, and find great advisors.”When the pandemic hit, many AAPI founders struggled to raise capital. Dave decided to help by syndicating a few angel investments via AngelList. What started as a plan to fund a few founders turned into Hyphen Capital, a movement that raised $30 million for 90+ startups, with over 50% of them led by women—far exceeding the industry's typical 2% funding allocation for female founders.“Rather than banging our heads against the bamboo ceiling, why don't we just build our own houses?”Overcoming the Bamboo CeilingWe dug into the bamboo ceiling—the systemic barriers that prevent AAPI professionals from reaching leadership roles despite their overrepresentation in technical fields. 50%+ of Silicon Valley employees are Asian, but only about 20% make it to executive roles.Dave pointed out that some companies, like NVIDIA and Pinterest, have higher promotion parity for AAPI employees, largely due to Asian founders setting the culture from the start.We also discussed how South Asian Americans, particularly men, have navigated leadership differently:“There are cultural differences. South Asian men tend to be more emboldened, better at self-promotion, and more comfortable with confrontation.”“A lot of East Asians were raised with Confucian values—respecting elders, keeping our heads down, not rocking the boat. But in corporate America, if you don't advocate for yourself, no one else will.”For many East Asian Americans, self-promotion feels unnatural, but as Dave pointed out, you have to play the game:“If you don't take credit for your work, someone else will.”The Future of AAPI Leadership & The Next GenerationWe also talked about how the next generation of AAPI professionals—kids growing up fully assimilated in the U.S.—might have an easier time navigating leadership.“Our parents had the immigrant scarcity mindset. They came here with nothing, and they made sure we knew it. But our kids? They don't feel guilt about anything.”While that might sound like a joke, there's a real shift happening. Younger generations are:* More willing to take risks (vs. prioritizing stability)* More confident in their leadership abilities* Less burdened by cultural expectations to follow "safe" career pathsDave also emphasized the importance of soft skills—something many Asian Americans don't focus on enough:“Being a good storyteller is one of the most valuable skills you can have. It's critical for sales, leadership, and career growth.”Navigating AI, Tech Trends, and OpportunitiesAs a product guy, I had to ask Dave about AI trends and where he sees opportunities.“AI is obviously taking over everything, but right now there's a lot of noise. The biggest opportunities will be in how AI is actually delivered—UX and experience design will be the differentiator.”He also mentioned that consumer tech isn't getting much VC love right now, but that doesn't mean there aren't opportunities:“Everyone is focused on AI, but I think there are some gems out there in consumer tech that people are overlooking.”Final Thoughts: Getting Involved & Building the FutureAs we wrapped up, we touched on a big topic: the growing anti-China sentiment in the U.S. and how it affects Asian Americans.“It's already happening. Asian hate crimes, the ‘China Initiative' going after innocent professors—it's all connected. The best thing we can do is get more involved: tell our stories, support AAPI representation in politics, and build powerful communities.”Dave's story is a lesson in action. He didn't wait for permission to start Hyphen Capital. He built the network he wished he had.For anyone reading this—whether you're a founder, a PM, or an aspiring leader—don't wait for permission.Build your own house. Advocate for yourself. And always lift others as you climb.Connect with Dave Lu & Fireside PMIf you enjoyed this convo, follow Dave on LinkedIn (@DaveLu) or check out his Substack at DaveLu.com. If you're an AAPI founder looking for funding, visit Hyphen Capital.For more deep dives like this, subscribe to Fireside PM on Substack! And if you're a pre-seed founder looking for advice (or maybe a small check), hit me up. Let's build something great together. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

n this episode of Fireside PM, I sit down with fellow ex-Googler and product consultant Mustafa Kapatiya to dive into how product managers can maximize AI for productivity, decision-making, and strategy. Mustafa shares real-world insights, including a live demo of AI-driven sentiment analysis, a breakdown of how top PMs leverage AI differently, and how organizations can use AI to do more with less. We also explore the future of product teams, AI's impact on PM career paths, and the evolving role of leadership in an AI-powered world. Tune in for actionable tips and deep insights!

Join me for a Fireside PM conversation with Dave Lu, founder of Hyphen Ventures, as we dive into his incredible career journey, the challenges of the Bamboo Ceiling, and his powerful advocacy for AAPI representation in tech and venture capital. From working at top companies like Apple, Yahoo, and eBay to launching Hyphen Capital and championing AAPI entrepreneurs, Dave has been a driving force in breaking barriers. We'll discuss: ✅ His path from corporate tech to investing in the next generation ✅ The Bamboo Ceiling: What it is & how to overcome it ✅ Building wealth and influence for the AAPI community ✅ His thoughts on leadership, mentorship, and making an impact

Hey Fireside PM crew,I had a fantastic conversation in this week's podcast with PJ, a seasoned Director of Product Management and product transformation consultant. PJ shared valuable insights from his journey, starting as a tech-focused developer, moving into product ownership at American Express, working with clients across industries at BCG, and now leading product transformations at EPAM. Here are the top takeaways:1. Driving Product Transformation Across Diverse OrganizationsPJ highlighted that every company has its unique DNA—some are engineering-led, some sales-led, others founder-driven. When companies seek to strengthen their product orientation, the challenge is often not just “what to do” but understanding “what change means for them.”Key steps PJ advises:* Assess the Current State: Understand how the organization defines product success, builds products, and aligns teams.* Establish a Common Product Vision: Everyone, from developers to sales, should share a unified understanding of the product and its purpose.* Break Down Silos: Connect teams to the end customer so that even an engineer sees how their work impacts users.* Small, Incremental Changes: Large overhauls often fail. Success comes from bite-sized adjustments that shift both ways of working and thinking.As PJ put it, “Most organizations recognize that what got them here won't get them where they want to go. The challenge is that they often don't know what that change actually looks like for them. We help them visualize what 'good' looks like and break it down into small, achievable steps.”We discussed, “One of the most common issues I see is silos. The engineering team might be working on their own objectives, while the product managers and sales teams are operating in parallel worlds. Bringing everyone onto the same page around the customer impact can be a game-changer.”2. Common Pitfalls for Product ManagersPJ and I discussed two classic challenges PMs often face:* Over-indexing on Execution: PMs get caught up in the daily grind and lose sight of long-term strategy.* Under-communicating Progress: Even if you're on the right track strategically, failing to proactively communicate with stakeholders can create uncertainty and risk.Successful PMs find a balance: They drive day-to-day delivery while ensuring leadership and stakeholders remain aligned with the strategic vision.“It's so easy to get trapped in the day-to-day. You're shipping features, hitting your sprints, but if you lose sight of the bigger picture, you may end up delivering a lot but not necessarily moving the business forward,” we agreed.On communication, PJ shared, “Under-communication can kill trust. I've seen great teams end up under a microscope simply because stakeholders felt out of the loop. It's not about overloading with updates; it's about consistent, clear communication.”3. Building Product Teams in the AI EraWith 2025 upon us, PJ reflected on debates around the necessity of PMs in a world increasingly assisted by AI. Could engineering managers with chatbots fill the gap? PJ's take:* The PM role can flex, but the core need remains: balancing value, viability, usability, and feasibility.* Engineering or marketing leaders can step into product roles if they develop the right mindset, but that transition requires coaching and organizational patience.“There's a lot of talk about replacing PMs with AI or blending the role into other functions, but product management is fundamentally about balancing multiple perspectives,” PJ explained. “It's not just about what can be built, but whether it should be built, if users will value it, and whether it makes business sense.”He added, “I've seen companies successfully transition engineers or marketers into product roles. The key is investing in their mindset shift and giving them the right support through coaching.”4. Advice for Aspiring PMs and Leaders Hiring PM Talent* Aspiring PMs: You don't need a technical background. Passion, curiosity, and a desire to solve problems matter more.* Hiring Product Leaders: When leading a product transformation, prioritize candidates with experience driving organizational change—especially those with consulting backgrounds—or consider fractional product leaders during transitions.“There's this myth that you need to have a technical background to be a product manager. It can help, but it's not a requirement. Some of the best PMs I know came from non-technical backgrounds and excelled because of their customer empathy and strategic thinking,” PJ emphasized.On hiring, he advised, “If you're transforming your product culture, look for someone who's done it before. They'll bring the experience and playbook to navigate the rough waters. Sometimes, a fractional leader during the transition can be the perfect bridge.”Final ThoughtPJ reminded us that transformation is a journey. Whether you're a PM looking to grow, or a leader reshaping your product team, success lies in aligning teams around customer impact, fostering clear communication, and embracing continuous learning.“Change is hard, but it's worth it. The best product teams I've seen are those that continuously learn and adapt. They put the customer at the center and rally the entire organization around delivering value,” PJ concluded.Check out PJ's daily insights on LinkedIn and his Substack for more product wisdom.Also, if you want to join my upcoming PM accelerator cohort starting soon, apply to join the Backchannel PM 3-month program here and access a $100 discount for my Fireside PM Substack readers only! This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

Hey Fireside PM crew, I had a fantastic conversation in this week's podcast with Priydarshan Jha (PJ), a seasoned Director of Product Management and product transformation consultant. PJ shared valuable insights from his journey, starting as a tech-focused developer, moving into product ownership at American Express, working with clients across industries at BCG, and now leading product transformations at EPAM. Here are the top takeaways: 1. Driving Product Transformation Across Diverse Organizations PJ highlighted that every company has its unique DNA—some are engineering-led, some sales-led, others founder-driven. When companies seek to strengthen their product orientation, the challenge is often not just “what to do” but understanding “what change means for them.” Key steps PJ advises: Assess the Current State: Understand how the organization defines product success, builds products, and aligns teams. Establish a Common Product Vision: Everyone, from developers to sales, should share a unified understanding of the product and its purpose. Break Down Silos: Connect teams to the end customer so that even an engineer sees how their work impacts users. Small, Incremental Changes: Large overhauls often fail. Success comes from bite-sized adjustments that shift both ways of working and thinking. As PJ put it, “Most organizations recognize that what got them here won't get them where they want to go. The challenge is that they often don't know what that change actually looks like for them. We help them visualize what 'good' looks like and break it down into small, achievable steps.” He added, “One of the most common issues I see is silos. The engineering team might be working on their own objectives, while the product managers and sales teams are operating in parallel worlds. Bringing everyone onto the same page around the customer impact can be a game-changer.” 2. Common Pitfalls for Product Managers PJ and I discussed two classic challenges PMs often face: Over-indexing on Execution: PMs get caught up in the daily grind and lose sight of long-term strategy. Under-communicating Progress: Even if you're on the right track strategically, failing to proactively communicate with stakeholders can create uncertainty and risk. Successful PMs find a balance: They drive day-to-day delivery while ensuring leadership and stakeholders remain aligned with the strategic vision. “It's so easy to get trapped in the day-to-day. You're shipping features, hitting your sprints, but if you lose sight of the bigger picture, you may end up delivering a lot but not necessarily moving the business forward,” PJ noted. On communication, he shared, “Under-communication can kill trust. I've seen great teams end up under a microscope simply because stakeholders felt out of the loop. It's not about overloading with updates; it's about consistent, clear communication.” 3. Building Product Teams in the AI Era With 2025 upon us, PJ reflected on debates around the necessity of PMs in a world increasingly assisted by AI. Could engineering managers with chatbots fill the gap? PJ's take: The PM role can flex, but the core need remains: balancing value, viability, usability, and feasibility. Engineering or marketing leaders can step into product roles if they develop the right mindset, but that transition requires coaching and organizational patience. “There's a lot of talk about replacing PMs with AI or blending the role into other functions, but product management is fundamentally about balancing multiple perspectives,” PJ explained. “It's not just about what can be built, but whether it should be built, if users will value it, and whether it makes business sense.” He added, “I've seen companies successfully transition engineers or marketers into product roles. The key is investing in their mindset shift and giving them the right support through coaching.” 4. Advice for Aspiring PMs and Leaders Hiring PM Talent Aspiring PMs: You don't need a technical background. Passion, curiosity, and a desire to solve problems matter more. Hiring Product Leaders: When leading a product transformation, prioritize candidates with experience driving organizational change—especially those with consulting backgrounds—or consider fractional product leaders during transitions. “There's this myth that you need to have a technical background to be a product manager. It can help, but it's not a requirement. Some of the best PMs I know came from non-technical backgrounds and excelled because of their customer empathy and strategic thinking,” PJ emphasized. On hiring, he advised, “If you're transforming your product culture, look for someone who's done it before. They'll bring the experience and playbook to navigate the rough waters. Sometimes, a fractional leader during the transition can be the perfect bridge.” Final Thought PJ reminded us that transformation is a journey. Whether you're a PM looking to grow, or a leader reshaping your product team, success lies in aligning teams around customer impact, fostering clear communication, and embracing continuous learning. “Change is hard, but it's worth it. The best product teams I've seen are those that continuously learn and adapt. They put the customer at the center and rally the entire organization around delivering value,” PJ concluded. Check out PJ's daily insights on LinkedIn and his Substack newsletter for more product wisdom (links below). https://www.linkedin.com/in/priydarshanjha/ https://priydarshanjha.substack.com/  

In this episode of Fireside PM, I sit down with Chris Vandermay, a veteran PM leader with experience at Google, Amazon, and Meta, to dive deep into the concept of controllable inputs. We discuss how top companies use these actionable metrics to drive real business outcomes, how to identify the right inputs versus vanity metrics, and why mastering them can make or break a product's success. Chris also shares insights on how AI is reshaping the role of product managers and what PMs can do to stay ahead in the evolving landscape. Tune in for a conversation packed with real-world examples and practical takeaways for PMs at any stage of their career!

Hey team,Last week on Fireside PM, I had the pleasure of reconnecting with an old Google colleague, Chris Vander May. We first crossed paths at the Kirkland office nearly 18 years ago, and since then, Chris has had an incredible career spanning Amazon, Google, Meta, and now his own AI-driven startup, Product Partner AI.Chris has seen it all—from launching the first version of Google Meet to leading product and engineering teams at Amazon and Meta. Our conversation covered a range of topics, including the key differences between Google, Amazon, and Meta, the power of controllable inputs in product management, and how AI is reshaping the role of PMs. We also delved into how PMs can future-proof their careers, the evolving nature of AI in product management, and the best ways for PMs to leverage AI-driven insights.Google vs. Amazon vs. Meta: The Cultural DifferencesChris offered a fascinating perspective on how these three tech giants operate differently:* Google: “Google, in my time, was very much an engineering-driven culture. PMs were peers to engineers, and leadership pushed a 'Why not?' mentality—do the harder thing, even if it's more work.”* Meta: “At Facebook, the PM was more of an ideas person. The ability to run rapid experiments at scale changed the dynamic. The role of the PM wasn't necessarily about making the best decision upfront, but rather about trying things and seeing what sticks.”* Amazon: “Amazon is much more product-led. There's a strong culture of writing and documentation. You don't just make decisions on the fly—you write things down to think them through rigorously.”Chris expanded on these insights by discussing how leadership styles differ at these companies. At Google, the focus was often on engineering-driven innovation, requiring PMs to align closely with engineering teams. At Meta, the emphasis was on creativity and rapid iteration, where launching and learning from experiments was key. Meanwhile, at Amazon, data-driven decision-making and operational efficiency were deeply ingrained in the company culture.The Power of Controllable InputsOne of the most impactful topics we covered was controllable inputs, a concept deeply ingrained in Amazon's culture. Chris explained:“A controllable input is a metric that you directly influence and that drives business outcomes. Unlike vanity metrics that might look good on a slide deck, these metrics are actionable.”He gave a fantastic example from Frito-Lay:“They figured out that the key metric for stocking chips wasn't total sales, but rather the number of stale bags on the shelf. If there were too many stale bags, they were overstocking. If there were none, they were losing sales. The right number was one stale bag per restock cycle. That's a controllable input.”For PMs, this means moving beyond simple engagement or revenue numbers to find the metric that actually drives sustainable growth.Chris further elaborated that companies often struggle to identify the right controllable inputs because they conflate outcomes with inputs. A revenue target, for instance, is an outcome, but what actually drives it? Identifying and focusing on those drivers—whether it's reducing onboarding friction, improving time-to-value, or optimizing conversion rates—is what separates strong PMs from the rest.He emphasized that a good controllable input should have the following characteristics:* Directly Influenced by the Team: PMs and their teams should be able to take action that moves the metric.* Closely Tied to Business Outcomes: While it may not be a direct revenue number, it should be something that, when improved, positively impacts the business.* Quickly Measurable: Metrics that update in real time or within a few weeks allow for faster iteration and learning.* Resistant to Gaming: Vanity metrics like total app downloads can be manipulated through paid acquisition, but a well-defined input resists such distortions.Chris also stressed the importance of refining controllable inputs over time. Many teams initially choose the wrong input and need to course-correct. A well-calibrated controllable input should help guide strategic decisions and enable PMs to set clear goals, allocate resources efficiently, and align teams around measurable outcomes.Another example Chris shared was Amazon's revenue per thousand opportunities (RPMO) metric for ads:“Instead of just looking at total ad revenue, we focused on how much revenue was generated per thousand ad impressions. This allowed us to optimize for better targeting and engagement rather than simply increasing ad load, which could degrade user experience.”He pointed out that these kinds of inputs serve as a north star for product teams, helping them focus on continuous improvements that compound over time.How AI is Changing the PM RoleAI is transforming the nature of product management, and Chris believes it will lead to fewer but more highly leveraged PMs.“Right now, we have around 900,000 PMs globally. In the future, I think we'll see fewer PMs, but they'll be much more strategic, working across more engineers and leveraging AI to do a lot of the traditional work PMs used to do manually.”For aspiring PMs, Chris had some direct advice:* Develop strong judgment. AI can generate ideas, but it can't (yet) make high-level strategic decisions.* Talk to customers. AI can process feedback, but it still can't replace the intuition of a PM who truly understands user pain points.* Master AI tools. “If you're not using AI to make yourself 10x more effective, you'll be replaced by someone who is.”Chris also discussed the potential impact of AI on cross-functional collaboration. AI-driven insights can help teams make data-informed decisions more efficiently, but it also means PMs will need to refine their ability to translate AI-generated recommendations into actionable product strategies.What's Next?Chris is now leading Product Partner AI, an AI-powered PM tool designed to help PMs be more effective. If you're curious, you can check it out at Product Partner AI.For those of you looking to level up your own PM skills, I've got a few things going on:* Maven Cohort: A three-month small-group coaching program where we break down your career like a product, define your OKRs, and build a roadmap to success. Apply at Maven.* Coaching: If you have a big product decision, job offer, or career move coming up, I offer direct coaching at TomLeungCoaching.com. I also work with company execs to support the coaching and learning of their younger PM teams.Thanks for tuning in to this week's Fireside PM! Let me know in the comments—what are your thoughts on controllable inputs in product management?Until next time,Tom This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

In my latest Fireside PM episode, I explore a compelling question that recently came up in my Backchannel PM Accelerator cohort: What is the future of product management, and how can PMs prepare for it? This discussion is rooted in the rapid technological changes reshaping our profession. Here are my reflections on where we're heading and what it means for PMs at every stage of their careers.1. The Compression of Career LaddersThe traditional PM career ladder, especially for early-career professionals, is under significant pressure. In the past, junior PMs honed their skills on tactical tasks like writing release notes, summarizing interviews, or conducting market research. These foundational experiences taught the nuances of the craft over time.However, automation—led by tools like ChatGPT—has disrupted this model. Many entry-level tasks can now be efficiently handled by AI, raising the bar for early-career PMs. Instead of mastering tactical execution, junior PMs must quickly acquire strategic and leadership skills. The ability to guide teams, evaluate new directions, and collaborate cross-functionally is now essential far earlier in a career.This shift presents a paradox: PMs must move up faster without the years of experience that traditionally prepare them for senior roles. To thrive, they need to develop strong judgment to discern when AI recommendations are valuable and when they fall short.2. AI-Native Products: Wands with ButtonsThe second trend is the shift toward creating AI-native products. The current state of AI integration often feels like "adding buttons to wands"—incremental improvements rather than transformative solutions. True AI-native products, in contrast, feel magical, like wands that fundamentally change the interaction model.A prime example is ChatGPT. It redefines how users acquire knowledge, offering a seamless, conversational interface that replaces traditional search methods. PMs who understand how to harness this potential can redefine industries, solving problems in ways previously unimaginable. This opportunity is greenfield, awaiting those bold enough to move beyond incremental improvements.3. Trust, Safety, and AI GovernanceAI introduces new complexities in trust and safety. Historically, this field focused on mitigating risks from human actions, such as fraud or misinformation. Now, PMs must address unintended consequences of AI systems. As autonomous AI agents gain greater latitude, companies must build robust governance frameworks to ensure these agents act responsibly.This emerging domain is not just a technical challenge; it requires ethical foresight, regulatory navigation, and dynamic risk management. PMs who excel here will be at the forefront of shaping how society interacts with increasingly powerful AI systems.4. Industry Disruption and Cross-Functional LeadershipNo industry is immune to AI-driven disruption. From education and healthcare to the arts and environment, AI is poised to upend established norms. For PMs, this means preparing for a career defined by adaptability. The ability to lead cross-functional efforts and own P&L responsibilities will be valued more than ever.The era of scaling large PM organizations is giving way to a focus on driving tangible outcomes with smaller, high-performing teams. Shareholders will demand measurable financial results, and PMs must rise to the challenge by delivering value that resonates with both customers and the bottom line.5. The Startups of Tomorrow: Lean and ImpactfulThe startup landscape is also evolving. Traditional barriers to entry, such as the need for large engineering teams, are eroding. Startups can now operate leaner while still delivering impactful solutions. While unicorns will remain aspirational, we may see the rise of "thoroughbred" startups—smaller, profitable ventures that deliver consistent value.This shift makes startup experiences even more attractive for PMs seeking diverse, dynamic roles. Startups offer opportunities to learn across functions, develop leadership skills, and embrace the kind of hands-on problem-solving that will define the next generation of PMs.5. Bonus: Double major in a customer/industry and Product ManagementI forgot to include this in the video but in a world where the functional expertise is less valued than before, combining expert PM functional experience with a deep expertise on a customer type and industry (e.g., specialize in PM for health tech, PM for fintech, PM for media, PM for marketing SAAS) could be a wise move.How to Thrive in This New EraThe future of product management is both exciting and demanding. Here's a roadmap to stay ahead:* Develop Leadership Early: Cultivate the ability to guide teams, align cross-functional efforts, and make strategic decisions—skills traditionally reserved for senior roles.* Embrace AI-Native Thinking: Challenge yourself to reimagine products from the ground up, leveraging AI to create fundamentally new experiences.* Prioritize Ethical AI: Build expertise in trust and safety, positioning yourself as a leader in navigating AI's complex challenges.* Adapt to Disruption: Seek opportunities to learn transferable skills that will keep you agile as industries evolve.* Consider Startups: Explore startup roles to gain exposure to diverse responsibilities and build the kind of dynamic experience that larger companies increasingly value.Join the ConversationIf these insights resonate with you, let's connect! I host weekly sessions in my Backchannel PM Accelerator, where we dive deep into topics like these. I also offer one-on-one coaching and interview prep, startup advising, and a manage a free PM-to-PM advice community at TomsList.com.Let me know your thoughts in the comments—where do you agree or disagree? I look forward to hearing from you and shaping the future of product management together. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

In this episode of Fireside PM, I tackle one of the most pressing questions from my Backchannel PM Accelerator: What does the future of product management look like, and how can PMs prepare? We explore the compression of career ladders, the rise of AI-native products, the evolving importance of trust and safety, and the shifting dynamics of startups. Whether you're an early-career PM or a seasoned leader, this episode is packed with actionable insights to help you thrive in a rapidly changing industry.

In this episode of Fireside PM, I had the privilege of interviewing Marcelo Calbucci, a seasoned entrepreneur, tech leader, and author of The PRFAQ Framework: Adapting Amazon's Innovation Framework to Work for You. Marcelo's extensive career spans over two decades, including roles at Microsoft, founding multiple startups, and leading teams at Amazon, where he embraced the PRFAQ framework as a transformative tool for product strategy and innovation.We delved into his journey, the essence of PRFAQ, and how this framework can revolutionize the way product managers and teams think about strategy and alignment.From Microsoft to Amazon: A Journey of DiscoveryMarcelo began his career at Microsoft, where he spent seven years building what eventually became Bing. Reflecting on the culture at Microsoft, Marcelo described a heavy reliance on PowerPoint presentations and thick strategy documents that often lacked the precision he would later find in Amazon's writing culture."I was always fascinated by Amazon's approach to writing. It was a revelation when I joined—it wasn't just about documenting plans but about fostering deeper conversations around strategy and vision."This shift in culture at Amazon inspired Marcelo to explore and later write about PRFAQ, a framework Amazon popularized to guide innovation.What Is the PRFAQ Framework?The PRFAQ (Press Release and FAQ) is a tool designed to frame product strategy by starting with the customer and working backward. The document is divided into three main sections:* Press Release: A hypothetical press release written as if the product were launching today, detailing the customer problem, the solution, and its impact.* Customer FAQs: Questions and answers addressing customer concerns, such as usability, pricing, and setup.* Internal FAQs: A deeper exploration of the feasibility, viability, and organizational impact of the idea.Marcelo explained its utility:"The PRFAQ isn't a tactical plan; it's about vision and strategy. It forces you to ask, 'Why is this the right opportunity?' and 'How does this align with our customer's needs?'"This format encourages clarity, critical thinking, and alignment across teams.Writing vs. Slides: A Culture ShiftOne of the most striking contrasts Marcelo observed between Amazon and other companies was the emphasis on writing over slides. While PowerPoint decks dominate many corporate cultures, PRFAQ's prose format provides a deeper, more structured way to approach strategic conversations."Slides are fine for visuals, but they often lack depth. A bullet point can gloss over critical issues, while writing a PRFAQ forces you to articulate your thoughts in a way that's precise and customer-focused."He also noted that writing a PRFAQ often uncovers blind spots:"When you sit down to write, you realize there are gaps in your thinking. Writing brings those gaps to the surface, which is invaluable for decision-making."PRFAQ Across Contexts: Startups, Corporations, and BeyondAlthough the PRFAQ framework is deeply ingrained in Amazon's culture, Marcelo emphasized its adaptability to other environments. In startups, for instance, PRFAQ can serve as an effective alternative to traditional pitch decks."Most pitch decks feel like commercials—they're all about selling the dream. A PRFAQ, on the other hand, is about asking the hard questions: Is this idea worth pursuing? Is it feasible? Is it something customers actually want?"Marcelo acknowledged that widespread adoption of PRFAQ might require a cultural shift. However, he sees growing interest, particularly as more Amazon alumni introduce the practice to other organizations."It's a reeducation process for both writers and readers. PRFAQ challenges the way we're used to consuming and presenting information."The Collaborative Nature of PRFAQOne of the key strengths of PRFAQ lies in its collaborative approach. The process is designed to iterate and evolve based on input from various stakeholders."The value of PRFAQ isn't just in the document itself—it's in the discussions it sparks. It's a process of alignment, where everyone involved contributes to shaping the vision and strategy."Marcelo outlined how feedback loops work in practice:* Start with a Rough Draft:"Your first draft doesn't need to be perfect. In fact, it's better if it isn't—it invites collaboration."* Engage Stakeholders Early:"Bring in engineers, designers, and legal teams for feedback. The document evolves with each iteration."* Facilitate Open Dialogue:"Create a safe space where everyone, regardless of seniority, feels comfortable contributing."Avoiding Common MistakesMarcelo shared some of the most common pitfalls teams face when adopting PRFAQ:* Mistaking PRFAQ for a Plan:"PRFAQ is about strategy, not execution. It focuses on the 'why' and 'what,' not the 'how.'"* Over-Polishing Early Drafts:"If your draft feels like a masterpiece, it can discourage others from offering feedback. Leave room for collaboration."* Skipping Alignment Steps:"The process of reviewing and iterating is what makes PRFAQ so powerful. Don't rush it."Metrics and Decision-MakingMetrics play a crucial role in PRFAQ, but Marcelo cautioned against overwhelming the document with unnecessary details:"Focus on metrics that matter to customers. Operational KPIs can come later—start with the high-level goals that define success."He also emphasized the importance of clarity in decision-making:"As a leader, be explicit about your decision. If you're saying yes, make it clear. If you need more data, communicate that too. Ambiguity is the enemy of progress."PRFAQ as a Tool for AlignmentMarcelo explained how PRFAQ can be used not only to kick off new projects but also to realign teams when visions diverge:"If a team is misaligned, writing a PRFAQ can bring everyone back to the same page. It's a way to refocus on the customer and the strategy."Writing the Book: Lessons LearnedMarcelo's journey to writing The PRFAQ Framework was itself a lesson in iteration. He revised chapters multiple times, incorporated feedback, and even used the PRFAQ format to guide the book's structure."The hardest part wasn't writing—it was the revisions. Each iteration made the book stronger, but it was a labor-intensive process."The book serves as both a comprehensive guide and a practical reference, complete with examples, checklists, and actionable advice.Final Thoughts from MarceloMarcelo concluded our conversation with advice for anyone looking to adopt PRFAQ:"Start small. You don't need to overhaul your entire process overnight. Try it for a single project and see the impact. Once you experience the clarity and alignment it brings, you'll wonder how you worked without it."He also encouraged readers to explore additional resources at theprfaq.com, where they can find templates, examples, and free chapters from his book.Plug for Tom's ListIf you made it this far, you must be a PM nerd. Join Tom's List which is a community for tech industry product managers to help each other with advice and feedback from big career decisions to writing great PRFAQ's :-) It's free. Sign up today at tomslist.com This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

In this episode of the Fireside PM podcast, I had the privilege of catching up with Karl Isaac, my former manager from Microsoft and a branding expert who has left an indelible mark on some of the world's most renowned companies. Our conversation was not just a trip down memory lane—it was an exploration of how product managers (PMs) can elevate their craft by embracing the power of branding.Karl's career journey spans iconic tech companies like Apple, Microsoft, and Adobe, where he led transformational brand campaigns and initiatives that redefined what it means to integrate brand and product. Below, I'll distill our conversation into actionable takeaways tailored for tech product managers.1. A Nonlinear Path to ExcellenceKarl's journey into the world of branding wasn't planned. He started in architecture, transitioned to design, and later pursued an MBA, which opened doors to Apple. There, he worked on the iTools team—a precursor to today's SaaS products. His career continued at Microsoft, where he took on business development roles, later transitioning to branding.Reflecting on this journey, Karl said, “I didn't set out to be a brand builder, but every step along the way taught me how design, storytelling, and strategy could come together to create something powerful.”Key lesson for PMs: Career paths aren't always linear. Karl's background in architecture and design uniquely positioned him to bring creative problem-solving to technology. PMs can benefit from embracing diverse experiences and perspectives, which often lead to innovative solutions.2. How Brand Shapes PerceptionOne of the most fascinating parts of Karl's career was leading Microsoft's response to Apple's famous "Get a Mac" campaign. Apple had depicted PCs as stodgy and uncool, personified by the character of a nerdy office worker. Karl's team flipped the script with the “I'm a PC” campaign, showcasing real people—scientists, artists, and entrepreneurs—who used PCs to achieve incredible things.Karl shared, “We wanted to show that PCs weren't just for accountants or nerds. They were tools for creators and innovators everywhere. It was about humanizing the technology.”He emphasized that this campaign wasn't just about countering Apple's narrative. It was about highlighting Microsoft's mission to democratize technology.PM takeaway: A product isn't just a set of features; it's a representation of your brand. Every product decision—whether it's a new feature, UI design, or onboarding flow—affects how customers perceive your company. Are you reinforcing your brand's core values, or unintentionally undermining them?3. Why PMs Should Think Beyond FeaturesKarl pointed out that too often, product teams focus narrowly on shipping features, overlooking the broader customer experience. He shared an example from eBay, where he led the integration of brand into the product organization. His team worked to shift eBay's perception from a place for quirky, hard-to-find items to a modern marketplace with fast shipping and reliable customer service.“It's not just about what you're shipping,” Karl noted. “It's about the story your product is telling. Every touchpoint matters, from search results to the checkout experience.”One particularly innovative product initiative involved leveraging AI to integrate eBay's catalog into Facebook Messenger, allowing users to find and purchase items instantly. This wasn't just a product enhancement; it was a branding move that reinforced eBay as a forward-thinking, customer-centric platform.PM takeaway: Every feature you ship contributes to your brand story. Ask yourself, “Does this align with our brand's vision? Does it reinforce the perception we want to build?”4. Brand as an Action, Not a DepartmentKarl challenged the traditional view of brand as the responsibility of marketing or design teams. Instead, he argued that brand is an action—a dynamic, customer-facing experience shaped by every team in the company.“Brand isn't something you define in a vacuum,” Karl said. “It's what customers experience. It's what they say about you when you're not in the room.”At Adobe, Karl spearheaded the use of community-generated artwork for product splash screens in tools like Photoshop and Illustrator. This simple decision not only strengthened Adobe's brand identity but also deepened its connection with its community.PM takeaway: Think of yourself as a brand leader. Every touchpoint—from your product's first-use experience to how it handles errors—shapes how customers perceive your company. Collaborate early and often with brand teams to ensure a cohesive experience.5. Vulnerability as a Leadership SuperpowerKarl reflected on how leadership styles have evolved over the years. Early in his career, intimidation and hierarchy were common management tactics. Today, successful leaders inspire through vulnerability, collaboration, and empathy.“Leading with vulnerability isn't a weakness,” Karl explained. “It's about building empathy, and empathy is the cornerstone of innovation.”He shared how this shift has influenced his work, including his decision to move branding under product at eBay. This change broke down silos, fostering closer collaboration between teams. The result? More cohesive strategies that aligned brand and product goals.PM takeaway: Vulnerability and empathy aren't just for people management—they're critical for understanding your customers. Build teams that aren't afraid to challenge assumptions, admit mistakes, and iterate based on real feedback.6. The Danger of Hubris in TechOur conversation turned to Elon Musk's rebranding of Twitter to X. Karl described it as a textbook example of hubris. Musk ignored the brand equity built over years and replaced it with a vision driven more by personal ego than customer benefit.“Conviction is one thing,” Karl said, “but hubris is something else entirely. It's a lack of listening, and that's where things go off the rails.”In contrast, Karl praised Apple's brand strategy under Steve Jobs, which was rooted in conviction rather than hubris. Apple didn't conduct traditional ad testing but made bold, customer-centric decisions that aligned with its brand values.PM takeaway: Conviction is essential, but it must be rooted in customer insights, not arrogance. Always ask, “What's the benefit for the customer?” If you can't answer that, rethink your approach.7. Community-Led Growth as the FutureKarl advocated for thinking beyond product-led growth to embrace community-led growth. He highlighted how brands like Slack and Adobe built loyal communities by embedding their customers into the product experience.“Your customers aren't just users,” Karl said. “They're co-creators. The more you involve them, the stronger your brand becomes.”For instance, Adobe's decision to feature community artwork in its products wasn't just a branding move—it was a way to co-create value with users. Similarly, Slack's early success was driven by its playful, highly shareable features that delighted users.PM takeaway: How can you involve your customers in shaping your product? Whether it's through community feedback, user-generated content, or co-creation initiatives, a strong community can amplify your product's impact and extend its lifecycle.8. The Brand-Product Feedback LoopKarl's philosophy boils down to one central idea: Brand and product aren't separate—they're deeply interconnected. When done right, brand work sets the stage for great product experiences, and great products reinforce the brand.He left us with a thought-provoking question: “As a product manager, are you making a deposit in the brand bank or a withdrawal?” Every decision you make—whether it's a feature prioritization, a pricing model, or a customer support policy—either strengthens or weakens your brand.PM takeaway: Don't treat brand as an afterthought. Make it a foundational part of your product strategy. Consider bringing a brand leader into your early product discussions, just as you would involve engineering or design.Closing Thoughts: Don't Believe Your Own HypeKarl shared one of the best pieces of career advice he's ever received: “Don't believe your own hype.” Stay humble, listen to people at all levels, and remain open to learning. These principles apply not just to personal growth but also to product and brand strategy.“Great brands aren't built in boardrooms,” Karl said. “They're built by listening to your customers and working across teams to create something they truly love.”As tech PMs, we often pride ourselves on metrics, roadmaps, and shipping features. But Karl's perspective reminds us of the bigger picture. At the end of the day, we're not just building products—we're shaping experiences, perceptions, and, ultimately, enduring brands.What do you think? Should brand and product teams collaborate more closely? How can PMs take a more active role in shaping their company's brand? Let me know in the comments!Learn more about Karl: https://www.linkedin.com/in/brands/Learn more about Tom's executive coaching practice: https://tomleungcoaching.com This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

In this episode of the Fireside PM podcast, I sit down with Karl Isaac, a branding expert and former Microsoft manager, to explore the intersection of product and brand. Karl shares insights from his transformative career at tech giants like Microsoft, Apple, and Adobe, where he spearheaded groundbreaking campaigns, redefined brand strategies, and led cultural shifts. They discuss the evolution of branding in tech, lessons from campaigns like “I'm a PC,” and how integrating brand with product management creates exceptional customer experiences. A must-listen for product managers and brand enthusiasts alike! https://www.linkedin.com/in/brands/

Thriving Under Different Managerial Styles: A PM's GuideDo You Work for the Boss from Hell, Heaven, or Somewhere In Between?In a recent Fireside PM podcast episode, I shared insights inspired by a coaching conversation with a senior PM at a FAANG company. * She was navigating a significant challenge: adapting to a new manager with a starkly different style than her previous one. This conversation resonated with me deeply because it highlighted a universal truth in the workplace: a manager's style can significantly impact your day-to-day experience—sometimes even more than the company you work for.*In this post, we'll dive into the 12 common manager archetypes, explore how to identify them, and discuss strategies to thrive under each. Change is inevitable in professional settings—managers shift roles, organizations restructure, and leadership styles evolve. Equipping yourself to adapt to these changes can accelerate your growth as a product manager and beyond.1. The Former SuperstarFormer superstars often bring their individual contributor (IC) expertise into their new managerial roles, but they express it in two distinct ways:* The Playbook-Enforcer: This manager believes in the methods that made them successful and expects the team to replicate them. They provide detailed guidance on processes, decisions, and outputs.Pro Tip: Align with their playbook initially. “Even if you don't fully agree, embrace their methods as a learning opportunity,” I advised in the podcast. Over time, they might moderate their approach, but until then, understanding and implementing their framework shows respect and adaptability.* The Hands-Off Mentor: At the other extreme, this type may provide minimal oversight, assuming everyone thrives with autonomy.Pro Tip: Proactively seek feedback and guidance. Their lack of involvement might stem from a belief in your independence, but you'll benefit from supplementing their support with advice from peers and mentors.When dealing with either type of former superstar, remember that their past success is often a double-edged sword. Their insights can be invaluable, but their approaches might need adjustment as they transition from IC to manager.2. The Hard-Charging Executive“What have you done for me lately?” might as well be this manager's mantra. Focused on results and efficiency, they have little patience for ambiguity.Pro Tip: Be concise and action-oriented in your communication. This high-pressure environment can sharpen your leadership skills, but be prepared to stay on your toes—even on weekends.Working under such a manager can feel intense, but it's an opportunity to learn how to thrive under pressure. The rigor they demand can often elevate your performance to new heights.3. The Absentee ManagerWhether due to overextension or lack of interest, absentee managers leave you feeling unsupported.Pro Tip: Build relationships across and around the manager's purview. Provide clear, concise updates to ensure they're aware of your contributions, and maintain strong documentation of your work.In the absence of active guidance, finding mentors and fostering peer support becomes crucial. It's also an opportunity to demonstrate initiative and autonomy—skills highly valued in any organization.4. The Rising StarRising stars are often on the company's fast track, closely aligned with top leadership and high-visibility initiatives.Pro Tip: Align with their vision and actively contribute to their success. As I mentioned, “Help them shine, and they'll bring you along for the ride.” Don't hesitate to ask for opportunities once you've proven your value.These managers thrive on momentum. By becoming a trusted ally, you can position yourself as an indispensable part of their ascent, which often translates into shared career growth opportunities.5. The Embattled ExecutiveThe embattled executive may be fighting to maintain their position or struggling under scrutiny.Pro Tip: Be a stabilizing force. Consistently deliver on your OKRs, avoid adding to their stress, and focus on results. “If they bounce back, they'll remember who supported them,” I said. And if they don't, your performance will speak for itself.Navigating this dynamic requires tact. By providing consistent support, you not only aid your manager but also safeguard your own reputation in the organization.6. The Skip-Level ManagerWhen you find yourself reporting directly to your skip-level, it's not quite the same as having an absentee manager. They care, but their scope is broader.Pro Tip: Offer high-level updates, build rapport, and keep your communication concise. If you're ready to step up and fill the gap, subtly showcase your capabilities.Being proactive can help establish trust with a skip-level manager. Think of it as an opportunity to broaden your exposure and potentially accelerate your career trajectory.7. The Visionary DreamerBig-picture thinkers thrive on ideas and innovation but often struggle with execution.Pro Tip: Be the Yin to their Yang. Help validate their ideas with actionable plans and metrics. As I shared, “Complementing their creativity with execution can build a winning partnership.”Visionary dreamers can inspire innovation, but balancing their enthusiasm with grounded strategies is key to turning dreams into deliverable outcomes.8. The MicromanagerMicromanagers often have good intentions, even if their methods feel stifling. They seek frequent updates and want to be deeply involved in decision-making.Pro Tip: Over-communicate initially. “Ask them what they need to see to give you more latitude,” I suggested. Demonstrating reliability can gradually earn their trust and autonomy.Understanding their perspective can help you shift the dynamic from micromanagement to mentorship. Their detailed involvement might even reveal insights you hadn't considered.9. The Empathetic CoachEmpathetic coaches prioritize your growth and well-being. They invest in your development and create a nurturing environment.Pro Tip: Embrace their support fully. Perform well and deliver results to validate their investment in you. “Managers like these are rare gems,” I said.Leveraging their guidance can help you hone both technical and soft skills, creating a strong foundation for long-term success.10. The Tactical Problem-SolverThis manager thrives on dissecting challenges and finding solutions.Pro Tip: Bring them into complex problems and value their insights. Their hands-on involvement can provide invaluable blind spot detection and shared workload.Collaborating with problem solvers can enhance your analytical skills. Their attention to detail often fosters a culture of precision and accountability.Final ThoughtsThe hallmark of a great product manager is adaptability. “You're not always going to pick your manager,” I emphasized. But by understanding and complementing diverse managerial styles, you can thrive under any leadership. These skills not only enhance your immediate performance but also build resilience and versatility for your career's long run.Remember, every manager—no matter their style—offers unique learning opportunities. Embrace the challenge of adapting, and you'll find yourself growing in unexpected and rewarding ways.If these insights resonate with you, let's keep the conversation going. Share this post, leave a comment, and subscribe to Fireside PM on Substack for more content tailored to product managers navigating the complexities of leadership and career growth. Ask a fellow PM for 1:1 advice on my list. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

In a recent Fireside PM podcast episode, I shared insights inspired by a coaching conversation with a senior PM at a FAANG company. * She was navigating a significant challenge: adapting to a new manager with a starkly different style than her previous one. This conversation resonated with me deeply because it highlighted a universal truth in the workplace: a manager's style can significantly impact your day-to-day experience—sometimes even more than the company you work for.

IntroductionWhen was the last time you asked for advice? Perhaps it was about a tough career decision, a thorny product challenge, or simply seeking perspective on your day-to-day PM grind. As a product manager, you're probably no stranger to giving and receiving advice—it's practically a job requirement. Yet, how often do we stop to think about how we approach this exchange?In my latest video, embedded above, I dive into the nuanced art of advice-giving and advice-receiving, sharing some actionable tips from both sides of the conversation. But here on Fireside PM, we'll take a deeper dive into this topic, exploring why advice matters, how to make the most of it, and how to ensure these exchanges elevate your career and your product.Grab a coffee and settle in—we've got a lot to unpack.Why Advice MattersLet's start with a story. Over the weekend, my 14-year-old son Brandon ran his first marathon. As the youngest runner in a small, local race, he had his sights set on finishing in under four hours. He came close—finishing in 4:09—but he learned a tough lesson along the way. Despite receiving advice from experienced runners not to go out too fast, race-day adrenaline took over. He pushed hard early, passing runners in shorter-distance races, and paid the price with slower splits later.Sound familiar? Whether you're running a marathon or navigating a product launch, many of our biggest mistakes are avoidable. Often, we've already been advised about the pitfalls but fail to internalize that wisdom in the heat of the moment. Why? Because advice is only as valuable as our ability to act on it.As PMs, our careers are punctuated by moments where great advice—or the lack of it—can define outcomes. Yet, the process of giving and receiving advice isn't always straightforward. Let's look at how to do it better.Receiving Advice: Five Rules to Live By* Trust the Source The first rule of advice is simple: trust the person giving it. If you've sought input from someone whose expertise and judgment you respect, lean into it. This is especially true if the advice resonates in calmer moments. Unless new data emerges, resist the urge to second-guess it when pressure mounts.* Ask the Right Questions Many people default to asking for advice in binary terms: “What should I do—Option A or Option B?” While this can yield useful guidance, a more powerful approach is to ask, “Have you faced a similar situation? What did you do, and what did you learn?” This invites broader insights, turning the conversation into a storytelling opportunity that helps you extract principles, not just prescriptions.* Be Clear About Your Goals Before seeking advice, clarify your objectives. Are you looking for a quick tactical solution, or are you seeking perspective on a larger strategic dilemma? The more specific you are about your goals, the more tailored and actionable the advice will be.* Reflect, Then Act Once you've gathered advice, don't rush into action. Take time to reflect. Consider the context in which the advice was given and weigh it against your own knowledge and circumstances. Thoughtful implementation is what turns advice into results.* Follow Through One of the most underrated aspects of receiving advice is follow-through. If you've decided to act on someone's input, do so with intention. And if their advice helps you succeed, don't forget to share the win with them—it's a great way to build deeper connections.Giving Advice: Making It CountIf receiving advice is an art, giving it is a craft. Here's how to make your advice resonate:1. Anchor It in Personal ExperienceAdvice that's rooted in real stories carries weight. One of the most impactful pieces of advice I ever received came from a former manager at Google. During a crisis, he recounted how Eric Schmidt, Larry Page and Sergey Brin approached problem-solving with a clear framework: first, get the cow out of the ditch; second, figure out how it fell in; and third, build a fence to prevent future mishaps.The vividness of that story made the advice memorable and actionable. When you give advice, aim to connect it to personal anecdotes that illuminate broader principles.2. Listen FirstBefore diving into solutions, take time to understand the context. What's the problem? What constraints are they facing? By listening actively, you can tailor your advice to their specific situation rather than offering one-size-fits-all solutions.3. Provide Options, Not DictatesGood advice empowers the recipient to make better decisions—it doesn't make the decision for them. Present multiple paths forward, explain the trade-offs, and trust them to choose what's best.4. Follow UpGiving advice isn't a one-and-done exercise. Check in to see how things are progressing. Not only does this show you care, but it also allows you to refine your advice based on how it's being implemented.The Virtuous Circle of Advice in the PM CommunityHere's a truth I've learned over years of working in product management: giving and receiving advice is a virtuous circle. The more you invest in helping others, the more the community invests in you.A PM you mentored might one day provide a crucial reference check for you. A colleague whose advice you followed could later champion your work. The tech industry, and particularly the PM function, thrives on these reciprocal exchanges.One of my favorite examples of this is Tom's List, my new project that connects PMs based on shared interests and challenges for free. Participants share advice, insights, and stories, helping each other navigate their careers. It's been incredible to see how quickly these connections can create ripple effects of mutual support.Common Pitfalls to Avoid* Overloading with Information When giving advice, be concise. A long-winded answer can overwhelm the recipient and obscure the core message.* Ignoring Emotional Context Advice isn't just about logic—it's also about empathy. Consider the emotional state of the person you're advising and tailor your tone accordingly.* Focusing Too Much on Your Own Story While personal anecdotes are powerful, don't make the advice all about you. Strike a balance between sharing your experience and focusing on their needs.* Failure to Build Trust Without trust, even the best advice will fall flat. Build rapport by showing genuine interest and understanding.Closing Thoughts: Advice as a SuperpowerWhether you're a seasoned PM or just starting your career, learning how to give and receive advice effectively is a superpower. It strengthens relationships, accelerates learning, and enables better decisions—not just for you but for your entire team.As you think about your next advice-giving or advice-receiving opportunity, keep these tips in mind. And if you're curious about how to take this to the next level, check out my video embedded below.What's the best piece of advice you've ever received as a PM? Share your stories in the comments or reply to this post—I'd love to hear from you!(Want to connect with other PMs and exchange advice in a curated, high-quality environment? Sign up for Tom's List today!) This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

The 8 Archetypes of Product Leaders: What Type Are You?As product leaders, we often ask ourselves: What is my superpower, and where can I have the most impact? In a recent Fireside PM episode, I explored this idea through the lens of eight common archetypes of product managers (PMs). Think of it as a "personality type system" for product leaders, but with actionable career insights.Whether you're an aspiring PM, a seasoned leader, or hiring your next product team, understanding these archetypes can help you align strengths, roles, and opportunities. Let's dive in.Why Knowing Your Archetype MattersIn the Fireside PM video, I said:“Mid-career forward, you really want to make your superpower as impactful as it can be. That might mean typecasting yourself, but that's okay—because the goal is to know who you are and seek opportunities that align with your strengths.”The key takeaway is this: doubling down on your strengths as a PM can unlock exponential growth. It's about finding environments where your unique skills shine, rather than trying to be everything to everyone.The 8 Archetypes of Product LeadersHere's the breakdown of the eight archetypes I discussed, complete with their strengths, areas for growth, and ideal roles:1. The Ideas PersonThis is the creative visionary who thrives in brainstorming sessions and loves tackling big, ambiguous problems.“These are the folks with colored Post-it notes all over their desks. They're energized by new ideas and out-of-the-box thinking, but they may struggle when it comes to execution.”Strengths: Vision-setting, brainstorming, and identifying new opportunities.Challenges: May lack follow-through or get bored with optimization work.Ideal Fit: Early-stage startups, innovation teams, or V1 product launches.2. The Business StrategistThese PMs bring an MBA-like mindset to their work, excelling in strategy reviews and resource planning.“They're terrific at analyzing industries and aligning business goals with product goals. But don't ask them to dream up a crazy idea for the next big thing—they'd rather plan the roadmap to scale an existing opportunity.”Strengths: Long-term planning, resource allocation, and strategic decision-making.Challenges: May be less comfortable in blue-sky environments or rapid prototyping.Ideal Fit: Enterprise SaaS, regulated industries, or complex B2B environments.3. The Team BuilderIf you need someone to rally the troops, build trust, and create a strong team culture, this is your archetype.“This is the person everyone loves to work for. They're not just managing teams—they're inspiring them to do their best work.”Strengths: Retaining top talent, fostering collaboration, and building a resilient culture.Challenges: May struggle with prioritizing strategy over relationships.Ideal Fit: Fast-growing companies, turnarounds, or teams recovering from a reorg.4. The CEO Whisperer / DealmakerThis archetype is a master of influence, networking, and driving high-stakes deals.“These PMs build trust with executives, secure buy-in, and land game-changing partnerships. They're at the conferences, meeting key players, and always staying ahead of market dynamics.”Strengths: Negotiating partnerships, influencing executives, and navigating complex ecosystems.Challenges: May overlook operational or team-building aspects.Ideal Fit: Strategic partnerships, marketplaces, or industries requiring deep relationship-building.5. The Execution SpecialistIf you want something done on time, on budget, and with precision, this is your PM.“They're detail-oriented and relentless. While others dream about the future, they're making sure the trains run on time.”Strengths: Delivering results, managing dependencies, and executing against tight timelines.Challenges: May lack big-picture vision or flexibility in ambiguous situations.Ideal Fit: Scaling organizations, operational roles, or post-Product-Market-Fit companies.6. The TechnologistThis archetype is a former engineer or technical lead who now brings deep technical expertise to product management.“They thrive in technical environments where their understanding of the underlying architecture or APIs gives them a unique edge.”Strengths: Technical problem-solving, working with engineering teams, and tackling complex challenges.Challenges: May overemphasize technical depth at the expense of user or market needs.Ideal Fit: Developer tools, infrastructure products, or highly technical fields like AI or crypto.7. The Superstar Individual Contributor (IC) Turned LeadThis PM often rises through the ranks by excelling as an IC, taking on leadership roles due to their exceptional performance.“They're the battlefield promotion—you see their results, and you think, ‘Let's see how far Jane can go.' But transitioning from IC to team leader isn't always smooth.”Strengths: Leading by example, setting high standards, and elevating team performance.Challenges: Delegating effectively and adapting to a leadership role.Ideal Fit: Startups or teams where leadership opportunities emerge organically.Developing a Balanced PortfolioWhile I emphasize knowing your archetype, it's also important to recognize that successful PMs often embody traits from multiple archetypes. In the video, I shared:“Everybody has a little bit of all these archetypes. But typically, there are two or three that stand out for you. For me, I'd say I'm an ideas person, a team builder, and a business strategist.”The key is identifying where you naturally excel, then surrounding yourself with complementary archetypes. If you're an ideas person, for example, partnering with an execution specialist can make your visions a reality.What Archetype Does Your Organization Need?The archetype you hire (or aspire to be) should align with your organization's stage and goals. A startup launching its first product might need an ideas person, while a scaling enterprise might prioritize an execution specialist or technologist.“Think of it like building a football team. A running back will thrive on a team like the Seahawks, but a quarterback might prefer the Saints. It's all about fit.”Conclusion: Lean Into Your SuperpowerAs you reflect on your own archetype, here are some questions to ask yourself:* What type of environment brings out my best work?* Which archetypes complement my strengths?* Am I in a role that aligns with my natural tendencies?Whether you're a PM looking for your next role or a leader building a team, understanding these archetypes can guide your decisions.“The goal isn't to be everything to everyone. It's to know who you are and find the opportunities that let you shine.”Share Your ThoughtsI'd love to hear from you:* Which archetype do you resonate with the most?* Did I miss any archetypes that you think are critical?* What archetype does your current role require, and how does it align with your strengths?Let me know in the comments or reply directly to this post!For more insights like this, subscribe to Fireside PM and stay tuned for the next episode. If you're interested in 1:1 coaching, group cohorts, or PM advisory, check out TomsList.com. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

The 8 different types of PM leads, their pros and cons, and best fit companies to work at.

I just shared my three big predictions for 2025 in my latest video. Here's a quick summary, but I'd love to hear your thoughts—especially if you disagree with any of them!* ROI Will Trump AIBy 2025, companies will focus more on ROI over pure AI hype. While AI could contribute $16 trillion to the economy by 2030 (according to PwC), most companies have struggled to see returns that justify their investments. Expect CFOs to demand clear profitability or massive cost reductions, particularly in new product categories. Stats back this up: 80% of growth from leading companies over the last decade came from entering new categories (Harvard Business Review).* A New AI Consumer Decacorn Will EmergeThe consumer AI space is ripe for a breakout moment. While enterprise AI has dominated, 2025 will likely bring a brand-new iconic company in the consumer AI market—something as transformative as ChatGPT but potentially in a marketplace format. My bold bet? This won't come from OpenAI, Anthropic, or Google but from a partnership model, much like Intel and Windows in the 1990s.* The Hiring Market Will NormalizeThe LinkedIn Workforce Report suggests a return to a balanced hiring market after the turbulence of 2022–2023. From my coaching conversations, I've seen PMs landing offers faster recently, indicating a brighter outlook for 2025.Bonus Prediction: Office Space Demand Is ReturningCompanies are growing and pushing for more in-person collaboration. JLL reports an increase in demand for office space. Case in point: the WeWork in Palo Alto is now fully booked for monthly memberships—something unimaginable just a couple of years ago.What do you think—am I spot on, or is one of these predictions way off? Let me know in the comments!p.s. I just launched a new experiment around enabling more PM peer advice called Tom's List. If you're a US based, technology industry PM with 3-33 years of PM experience, I encourge you to join (it's free)! This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

In my recent Fireside PM podcast, I had the privilege of sitting down with Brian Goffman, a repeat guest and one of the most insightful voices in the product management (PM) space. Brian's career spans decades of innovation, from his time at LinkedIn, SmartThings, and Adobe, to his current role leading McKinsey's Software Excellence Practice. His unique vantage point—working across Web 1.0, 2.0, 3.0, and now AI—makes him a treasure trove of lessons for anyone navigating the tech landscape. In this conversation, we dove into career-defining moments, the evolving challenges of leadership, and how AI is fundamentally reshaping the PM profession. Brian shared profound insights and practical advice for professionals at every stage of their journey, sprinkled with the wit and wisdom that only years of experience can bring.

Welcome back to another episode of Fireside PM! Today, I want to share some hard-earned lessons that have shaped my career as a Product Manager (PM) and PM leader. These lessons, grounded in experience, have been instrumental to my journey and are relevant whether you're early in your PM career or already leading teams. Let's dive into these five lessons that, while challenging, are essential for sustained growth and success in product management.

Unlock the secrets of demand generation from Rory Braatvedt, who shares essential frameworks for entrepreneurial product managers and startup founders ready to move beyond their personal networks.

Lessons from the Frontlines of Silicon Valley: How to Recognize Common Pitfalls and Stay Focused on What Really Matters