Podcasts about replit

Jason Lemkin is the founder of SaaStr, the world's largest community for software founders, and a veteran SaaS investor who has deployed over $200 million into B2B startups. After his last salesperson quit, Jason made a radical decision: replace his entire go-to-market team with AI agents. What started as an experiment has transformed into a new operating model, where 20 AI agents managed by just 1.2 humans now do the work previously handled by a team of 10 SDRs and AEs. In this conversation, Jason shares his hands-on experience implementing AI to run his sales org, including what works, what doesn't, and how the GTM landscape is quickly being transformed.We discuss:1. How AI is fundamentally changing the sales function2. Why most SDRs and BDRs will be “extinct” within a year3. What Jason is observing across his portfolio about AI adoption in GTM4. How to become “hyper-employable” in the age of AI5. The specific AI tools and tactics he's using that have been working best6. Practical frameworks for integrating AI into your sales motion without losing what works7. Jason's 2026 predictions on where SaaS and GTM are heading next—Brought to you by:DX—The developer intelligence platform designed by leading researchersVercel—Your collaborative AI assistant to design, iterate, and scale full-stack applications for the webDatadog—Now home to Eppo, the leading experimentation and feature flagging platform—Transcript: https://www.lennysnewsletter.com/p/we-replaced-our-sales-team-with-20-ai-agents—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/182902716/my-biggest-takeaways-from-this-conversation—Where to find Jason Lemkin:• X: https://x.com/jasonlk• LinkedIn: https://www.linkedin.com/in/jasonmlemkin• Website: https://www.saastr.com• Substack: https://substack.com/@cloud—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Jason Lemkin(04:36) What SaaStr does(07:13) AI's impact on sales teams(10:11) How SaaStr's AI agents work and their performance(14:18) How go-to-market is changing in the AI era(19:19) The future of SDRs, BDRs, and AEs in sales(22:03) Why leadership roles are safe(23:43) How to be in the 20% who thrive in the AI sales future(28:40) Why you shouldn't build your own AI tools(30:10) Specific AI agents and their applications(36:40) Challenges and learnings in AI deployment(42:11) Making AI-generated emails good (not just acceptable)(47:31) When humans still beat AI in sales(52:39) An overview of SaaStr's org(53:50) The role of human oversight in AI operations(58:37) Advice for salespeople and founders in the AI era(01:05:40) Forward-deployed engineers(01:08:08) What's changing and what's staying the same in sales(01:16:21) Why AI is creating more work, not less(01:19:32) Why Jason says these are magical times(01:25:25) The "incognito mode test" for finding AI opportunities(01:27:19) The impact of AI on jobs(01:30:18) Lightning round and final thoughts—Referenced:• Building a world-class sales org | Jason Lemkin (SaaStr): https://www.lennysnewsletter.com/p/building-a-world-class-sales-org• SaaStr Annual: https://www.saastrannual.com• Delphi: https://www.delphi.ai/saastr/talk• Amelia Lerutte on LinkedIn: https://www.linkedin.com/in/amelialerutte/• Vercel: https://vercel.com• What world-class GTM looks like in 2026 | Jeanne DeWitt Grosser (Vercel, Stripe, Google): https://www.lennysnewsletter.com/p/what-the-best-gtm-teams-do-differently• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Replit: https://replit.com• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• ElevenLabs: https://elevenlabs.io• The exact AI playbook (using MCPs, custom GPTs, Granola) that saved ElevenLabs $100k+ and helps them ship daily | Luke Harries (Head of Growth): https://www.lennysnewsletter.com/p/the-ai-marketing-stack• Bolt: https://bolt.new• Lovable: https://lovable.dev• Harvey: https://www.harvey.ai• Samsara: https://www.samsara.com/products/platform/ai-samsara-intelligence• UiPath: https://www.uipath.com• Denise Dresser on LinkedIn: https://www.linkedin.com/in/denisedresser• Agentforce: https://www.salesforce.com/form/agentforce• SaaStr's AI Agent Playbook: https://saastr.ai/agents• Brian Halligan on LinkedIn: https://www.linkedin.com/in/brianhalligan• Brian Halligan's AI: https://www.delphi.ai/minds/bhalligan• Sierra: https://sierra.ai• Fin: https://fin.ai• Deccan: https://www.deccan.ai• Artisan: https://www.artisan.co• Qualified: https://www.qualified.com• Claude: https://claude.ai• HubSpot: https://www.hubspot.com• Gamma: https://gamma.app• Sam Blond on LinkedIn: https://www.linkedin.com/in/sam-blond-791026b• Brex: https://www.brex.com• Outreach: https://www.outreach.io• Gong: https://www.gong.io• Salesloft: https://www.salesloft.com• Mixmax: https://www.mixmax.com• “Sell the alpha, not the feature”: The enterprise sales playbook for $1M to $10M ARR | Jen Abel: https://www.lennysnewsletter.com/p/the-enterprise-sales-playbook-1m-to-10m-arr• Clay: https://www.clay.com• Owner: https://www.owner.com• Momentum: https://www.momentum.io• Attention: https://www.attention.com• Granola: https://www.granola.ai• Behind the founder: Marc Benioff: https://www.lennysnewsletter.com/p/behind-the-founder-marc-benioff• Palantir: https://www.palantir.com• Databricks: https://www.databricks.com• Garry Tan on LinkedIn: https://www.linkedin.com/in/garrytan• Rippling: https://www.rippling.com• Cursor: https://cursor.com• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• The new AI growth playbook for 2026: How Lovable hit $200M ARR in one year | Elena Verna (Head of Growth): https://www.lennysnewsletter.com/p/the-new-ai-growth-playbook-for-2026-elena-verna• Pluribus on AppleTV+: https://tv.apple.com/us/show/pluribus/umc.cmc.37axgovs2yozlyh3c2cmwzlza• Sora: https://openai.com/sora• Reve: https://app.reve.com• Everything That Breaks on the Way to $1B ARR, with Mailchimp Co-Founder Ben Chestnut: https://www.saastr.com/everything-that-breaks-on-the-way-to-1b-arr-with-mailchimp-co-founder-ben-chestnut/• The Revenue Playbook: Rippling's Top 3 Growth Tactics at Scale, with Rippling CRO Matt Plank: https://www.youtube.com/watch?v=h3eYtzBpjRw• 10 contrarian leadership truths every leader needs to hear | Matt MacInnis (Rippling): https://www.lennysnewsletter.com/p/10-contrarian-leadership-truths—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

What would you do if someone offered you $1 billion for your six-person startup? Jordanian-American founder Amjad Masad said no—and today, Replit is worth $3 billion. In this episode, we break down his gutsy decision and Marc Andreessen's game-changing advice. Plus: dealmaker Amanda Staveley reveals why Gulf sovereign funds won't be buying more Premier League clubs (and what they're doing instead), and Abu Dhabi Investment Authority places a $65M bet on Chinese AI startup MiniMax—despite it losing half a billion dollars a year. From billion-dollar rejections to shifting investment strategies, here's everything happening in Arab business and tech. Newsletter: aug.us/4jqModrWhatsApp: aug.us/40FdYLUInstagram: aug.us/4ihltzQTiktok: aug.us/4lnV0D8Smashi Business Show (Mon-Friday): aug.us/3BTU2MY

You're winding down for the year?

This week we embrace the chaos of teamwork and tech tools — and somehow make sense of it all. From "vibe coding" with Replit (yes, it's a thing) to CRM philosophies, sales toolboxes, and the mysterious magic of CDPs, we reflect on the tools that actually help teams get stuff done.We dive into:Why English is the new coding language The magic of cloud collaboration (and the rage when it goes wrong)What a “Sales Toolbox” is and why it should still existHow to avoid death-by-governance when using email or CMS toolsThe rise of Customer Data Platforms (CDPs) — and how they're different from CRMsAlso: we pretend we didn't nearly forget what this episode was supposed to be about. Classic us.

In this episode of Future of UX, Patricia breaks down the most important tech and AI shifts of 2025 — the trends that fundamentally changed how we design, build, research, and work. If you missed anything this year or simply want the essential takeaways, this episode is your shortcut.From AI Agents and deepfake-proof UX to vibe-coding, AI-native browsers, research automation, and the rise of general-purpose robots — here are the big transformations shaping the future of design.Why 2025 was the year AI Agents became real — not as chatbots, but as autonomous coworkers running full workflows.• How MCP unlocked the agent ecosystem• Vibe coding and intent-driven development• The shift from execution to oversight in human rolesVisual trust collapsed — and UX became responsible for rebuilding it.• Why humans can't detect deepfakes anymore• What actually worked: C2PA, identity checks, and UI “micro-literacy”• Designing interfaces that communicate authenticity and uncertaintyHow tools like Lovable, Replit, and AI builders changed who gets to create.• From pixel pushing to strategic direction• Conversational creation flows• What this means for designers and innovatorsAI automated more than ever — but made human oversight more important.• Where full autonomy worked• Where humans stayed essential• Why the future depends on intentional human-in-the-loop designResearch and analysis were transformed by automated synthesis.• Superagency: managing research instead of doing it manually• The new trust problem in fast research• Data provenance, model transparency, and expert validationBrowsers became intelligence layers instead of navigation tools.• Context-aware, predictive UX• Browsers that act, not just display• How this changes product and interaction designWhy general-purpose robots finally left the lab in 2025.• Embodied AI• Real-world perception• Language-driven task executionAI for Designers: 5-week Bootcamp

This week showed just how much pressure the AI trade is under. OpenAI's Sam Altman is heading to Jimmy Fallon next week as the company reportedly declares “Code Red.” Nvidia's Jensen Huang is shuttling between Silicon Valley, Washington and Beijing, trying to navigate the toughest geopolitical bind of the company's history. And Replit is locking in a multiyear partnership with Google to push vibecoding to the enterprise. Google's Matt Renner and Replit's Amjad Masad join Deirdre Bosa to discuss. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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

Anthropic asked 1,250 professionals how AI is actually changing their work, and the results reveal a blend of optimism, anxiety, and shifting identity—creatives feeling squeezed, scientists wanting trustworthy partners, and most workers hoping to hand off routine tasks while keeping what defines their craft. The episode also looks at how AI-run interviews collapse the old scale-vs-context tradeoff in research and what that means for understanding real-world AI impact. Headlines include Gemini 3 Deep Think, Replit's enterprise push with Google, Opus 4.5's benchmark surge, Salesforce's Agent Force momentum, and Meta's pivot away from the metaverse.Brought to you by:KPMG – Discover how AI is transforming possibility into reality. Tune into the new KPMG 'You Can with AI' podcast and unlock insights that will inform smarter decisions inside your enterprise. Listen now and start shaping your future with every episode. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.kpmg.us/AIpodcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Rovo - Unleash the potential of your team with AI-powered Search, Chat and Agents - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://rovo.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LandfallIP - AI to Navigate the Patent Process - https://landfallip.com/Blitzy.com - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to build enterprise software in days, not months Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Agent Readiness Audit from Superintelligent - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://besuper.ai/ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614Interested in sponsoring the show? sponsors@aidailybrief.ai

Google announced an expanded partnership with vibe-coding startup Replit that brings the company deeper into the Google Cloud. We sit down with Google Cloud President Matt Renner and Replit CEO Amjad Masad to dig into what the deal means about the future of AI coding boom. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

HEADLINES:• Paramount–Skydance's New Warner Bros. Discovery Bid Secures Backing From Gulf Sovereign Wealth Funds: Variety• Saudi Arabia's PIF Set to Take 93.4% Stake in Electronic Arts in $55 Billion Takeover • Replit, Founded by Jordanian-American Amjad Masad, Targets $1B ARR by 2026 Newsletter: https://aug.us/4jqModrWhatsApp: https://aug.us/40FdYLUInstagram: https://aug.us/4ihltzQTiktok: https://aug.us/4lnV0D8Smashi Business Show (Mon-Friday): https://aug.us/3BTU2MY

Every marketing leader should give their team an AI framework for rethinking how they work. In this week's episode of Growth Talks, Vanessa Hope Schneider, Head of Marketing at Decript, joins host Tyler Elliston, Founder and CEO of Right Side Up, to break down how AI is becoming core to every marketer's role and what that shift means for how modern teams operate. Drawing on her leadership experience from Airbnb, Eventbrite, and Descript, Vanessa outlines a framework for helping teams adopt AI while preserving the human element that defines great marketing.  Find out why learning AI tools and experimenting with real workflows is key to understanding where AI adds value and setting your team up for success.

Jak může architekt dnes využívat AI tak, že mu to ušetří celé týdny práce? A proč je budoucnost v kombinaci odbornosti a umělé inteligence?Do dalšího dílu podcastu Budoucnost nepráce jsem si pozval Martina Jana Rosu – architekta, který nádherně propojuje svou doménovou expertízu s digitálními nástroji a AI. Tohle je další z velmi praktických rozhovorů, které jsem v poslední době vedl.Martina jsem se ptal na konkrétní scénáře, jak využívá AI v architektuře i při práci s daty. V podcastu zazní:Jak AI změnila Martinovu práci za poslední rok [03:25]Kdy má smysl používat skripty a Python v architektuře [07:13]Co je BIM / IFC a proč jsou zásadní [08:56]Automatizace rutinní práce pomocí AI [11:35]Nástroje Cursor, Replit a Cloud Code v praxi [13:59]Jak AI přemýšlí: reasoning a samoopravné skripty [17:12]Budoucnost profesí: doménová znalost + AI [28:39]„Druhý mozek“ a organizace informací [40:54]Proč je pořádek v datech klíčový pro práci s AI [48:13]Tahle epizoda je plná inspirace, konkrétních use cases a praktických tipů, které můžete začít používat hned. Co by se stalo, kdybyste se naučili využívat AI stejně efektivně jako Martin — a kolik práce by vám to ušetřilo?

For their 100th episode, Ray "Growth" Rike and Dave "CAC" Kellogg get philosophical, inspired by the notion that many hold, which is "nothing works" in B2B GTM anymore - especially in regards to pipeline development.They dive into the 2025 State of B2B GTM Report by Kyle Poyar and Maja Voijc to challenge this idea and find out what GTM leaders are actually prioritizing.In this episode, The Metrics Brothers break down:The State of the Market: Analyzing a survey of 195 GTM leaders, including data on small companies, growth rates, and the surprising lack of correlation between GTM motion and growth.The "Pipeline Crisis": Discussing why scaling existing GTM motions is the number one priority, even when many GTM leaders feel their current efforts aren't effective.Too Much Noise: A look at the "distraction chart" [slide 12] showing the staggering number of channels and strategies B2B companies are trying, and why the report suggests this is "too much".The Tried and True GTM Quadrant: Highlighting the activities with the biggest likelihood of impact, including Intimate Events, Intent-Based Inbound, and LinkedIn [slide 13].The Winner Take All Future: Exploring the massive trend of investing in Answer Engine Optimization (AEO) [slide 18] and breaking down tactical recommendations for optimizing for ChatGPT and other answer engines, emphasizing the importance of facts and platforms like Reddit and G2 [slide 19].Must Try GTM Tools: Reviewing the next generation of GTM tools, with a focus on cutting-edge platforms like Clay, Lovable, Sora, and Replit for data automation, outbound, and video generation [slide 29].Whether you're a Founder, CMO, CRO or GTM leader, this episode offers a data-driven look at where to focus your budget and attention in the year ahead.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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Maor Shlomo is the Founder and CEO of Base44, the AI building platform that Maor built from idea to $80M acquisition by Wix, in just 8 months. Today the company serves millions of users and will hit $50M ARR by the end of the year. Before Base44, Maor was the Co-Founder and CTO of Explorium. AGENDA: 00:05 – 00:10: How Vibe Coding is Going to Kill Salesforce and SaaS 00:13 – 00:15: Do Vibe Coding platforms have any defensibility? 00:22 – 00:24: I am not worried about Replit and Lovable, I am worried about Google… 00:28 – 00:29: Margins do not matter, the price of the models will go to zero 00:31 – 00:32: Speed to copy has never been lower; has the technical moat been eroded? 00:47 – 00:48: How does Base44 beat Cursor? 00:56 – 00:57: Do not pay attention to competition: focus on your business 00:57 – 00:58: How Base44 is helped, not hurt by not being in Silicon Valley? 00:58 – 00:59: What percent of code will be written by AI in 12 months? 01:01 – 01:02: OpenAI or Anthropic: Why Maor is Long Anthropic? 01:03 – 01:04: If I could have any board member in the world it would be Jack Dorsey      

Pete Syme talks with Drew Falkman about vibe coding, a way for tour operators to build custom software tools using plain English prompts instead of traditional programming. Drew explains how AI tools like ChatGPT and Claude have been trained on code repositories, allowing them to generate working applications from simple descriptions. The conversation covers why this matters for small operators, what you can build, the learning curve, costs, security considerations, and how this technology could shift the relationship between tour operators and the software they depend on. Pete emphasizes that operators already have the same AI access as hundred million dollar companies and encourages spending at least an hour daily experimenting with these tools.Top 10 TakeawaysYou can build tools without coding knowledge. AI tools trained on code repositories can generate working applications from plain English descriptions, making app building accessible to anyone.Most SaaS tools don't fit your exact workflow. You end up paying for applications where 80% of features you're not using because they're designed for other industries, but the things you do use aren't quite refined enough.Start with internal workflows, not customer-facing apps. Build tools for internal processes first. Don't go public with what you build until you have experience, as you can get 80 to 90% correct quickly, but that last bit is more challenging.Map your processes before building. Write down all your processes on paper, rank what's most important, and list what you really don't like doing. This helps identify where custom tools can have the biggest impact.The learning curve has three main steps. First, learn to plan what you want to build (20 to 30 hours). Second, design the workflow and user interface (a few hours). Third, understand data and databases (a couple days). Total time to get comfortable is roughly a few weeks of focused learning.Tools like Lovable cost around $20 per month. There are small monthly fees for vibe coding platforms, plus hosting costs if your tool is public-facing. Tools like Lovable, Bolt, Replit, Magic Patterns, and N8n each serve different purposes.Keep data storage minimal for security. Don't store sensitive information like credit card numbers or social security numbers. Use third-party authentication (Google, Microsoft, Apple) and payment processors like Stripe to handle sensitive data.You can build custom booking flows and optimize conversions. Create your own booking engine where you control every step, then use analytics tools to see where people drop off and experiment with improvements to increase completion rates.This threatens the traditional SaaS industry. Large companies spending millions monthly on SaaS are already exploring vibe coding to reduce costs. What happens at that level will cascade down through the industry to the tools small operators use today.Just try it to understand the possibilities. Go to lovable.dev, run a prompt, and build something. You won't fully understand what you can do until you experiment. You have nothing to lose with free versions, and no one else will see your experiments.Want to learn vibe coding yourself? Drew teaches courses on building apps without code. Visit drewfalkman.com to explore free resources and paid courses that walk you through the process step by step.

Gemini Pro 3 and Nano Banana Pro push Google into the lead in the race for AGI. Meanwhile, OpenAI isn't far behind with GPT-5.1 Pro & Codex Max. The AI news is relentless! Nano Banana Pro's ability to make infographics and edit images is nearly unprecedented and, combined with Gemini 3's analytical abilities, makes us feel all tingly inside. Web design, vibe coded games, there is so much cool stuff to get into. Plus, OpenAI's updates GPT-5.1 and a cool new tool from Meta called Segment Anything 3. And, of course, who could forget the cutest lil robots. No terminators today folks! TIME TO NANO BANANA OURSELVES INTO OBLIVION. WAIT, THAT SOUNDED BAD. Come to our Discord: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow Show Links Google Nano Banana Pro https://blog.google/technology/ai/nano-banana-pro/ Gavin's Futurama-style Image https://x.com/gavinpurcell/status/1991525928049230170?s=20 14 Inputs on Nano Banana Pro Image https://x.com/nickfloats/status/1991531506397741156 Sims Expansion Packs https://x.com/sinanhelv/status/1991530277974253871 Rowan Atkinson (Mr. Bean) in Total Recall https://x.com/TomLikesRobots/status/1991548219428663586 Gemini 3 Pro https://youtu.be/98DcoXwGX6I?si=Fwd83wo5vRHPb78d https://blog.google/products/gemini/gemini-3/#note-from-ceo Demis Hassabis Talks About Trajectory on Hard Fork https://x.com/slow_developer/status/1990998467611705344?s=20 Crazy Gemini 3 Pro benchmarks https://x.com/OfficialLoganK/status/1990813077172822143?s=20 Google AntiGravity  https://x.com/antigravity/status/1990813606217236828?s=20 3js interactive webdesign https://x.com/EHuanglu/status/1990967259775570262?s=20 Huge improvements on DesignArena benchmark: https://x.com/grx_xce/status/1990815340893245481?s=20 Replit's new tool for webdesign powered by Gemini 3.0 https://x.com/amasad/status/1990859423942893816?s=20 Gavin's quick website test https://gemini.google.com/share/a1e8d50a3d69 Bouncing Ball Test https://x.com/OfficialLoganK/status/1990819310072443340?s=20 Voxel Art https://x.com/goodfellow_ian/status/1990839056331337797?s=20 Demis Recreates ThemePark https://x.com/demishassabis/status/1990818894177513831?s=20 Playables on YouTube:  https://x.com/GoogleDeepMind/status/1991192012691808472?s=20 Updating My Bear Jump Game https://x.com/gavinpurcell/status/1990832098131763340?s=20 OpenAI: GPT-5.1 Codex MAX https://x.com/polynoamial/status/1991212955250327768?s=20 https://openai.com/index/gpt-5-1-codex-max/ GPT 5.1 Pro https://x.com/OpenAI/status/1991266192905179613?s=20 Matt Shumer GPT-5.1 Pro Review https://x.com/mattshumer_/status/1991263717820948651?s=20 Meta Segment Anything 3 Playground  https://aidemos.meta.com/segment-anything Sunday Robotic's Memo Robot https://www.sunday.ai/ Gemini 3 Pro 3D Lego Editor https://x.com/skirano/status/1990813093727789486?s=20 Realistic Water Test From MattVideoPro https://x.com/MattVidPro/status/1990880204760252834?s=20 Power Plant Recreation https://x.com/sebkrier/status/1990814567820058641?s=20 Sourcey: Open Source Robot https://x.com/sourccey/status/1990903761187828199  

Get our free Google Gemini bundle with our favorite prompts + workflows: https://clickhubspot.com/sce Ep. 380 Is Gemini 3 better than GPT-5? Kipp and Kieran dive into the seismic release of Gemini 3 and what it means for the future of marketing, search, and AI-driven business tools. Learn more on how Gemini's state-of-the-art multimodal reasoning unlocks custom interactive apps in search, why dynamic AI-generated UIs signal the end of the blue links era, and how marketers can leverage Gemini to automate research, customer insights, and content more effortlessly than ever before. Mentions Gemini 3 https://gemini.google.com/ ChatGPT 5 https://chat.chatbot.app/gpt5 Claude https://claude.ai/ Replit https://replit.com/ Lovable https://lovable.dev/ Fiverr https://www.fiverr.com/ Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt We're creating our next round of content and want to ensure it tackles the challenges you're facing at work or in your business. To understand your biggest challenges we've put together a survey and we'd love to hear from you! https://bit.ly/matg-research Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Join our community https://landing.connect.com/matg Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat  ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by Hubspot Media // Produced by Darren Clarke.

AGENDA: 04:47 Cursor Raises $2.3BN at $29BN Valuation 11:36 What Gemini 3 Means for Lovable, Cursor and Replit 30:54 Peter Thiel and Softbank Sell NVIDIA: The Bubble Bursting? 48:54 Oracle Credit Default Swaps: The Risk is Increasing 01:07:22 Stripe Does Tender at All-Time High: Why the Best Companies Will Never IPO 01:19:18 Why Retail WIll Cause a Surge of Capital into VC Funds  

AI euphoria is giving way to fear. The industry that once looked unstoppable is starting to bleed from a thousand tiny cuts. Short sellers like Michael Burry and Jim Chanos are circling, warning that the AI buildout isn't a one-time investment but a recurring cost wave. In this Take, CNBC's Deirdre Bosa breaks down the new signals investors are watching, the rising risks behind the spending, and what founders like Amjad Masad of Replit and Navrina Singh of Credo AI see from inside the cycle. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this special live Web Summit edition from Lisbon, I sit down with Tom Haworth, founder of D13 AI, to talk about why “good enough” AI might actually be one of the most dangerous places we can get stuck.And you'll hear Tom say it's time for the leaders of vibe coding platforms (e.g. Lovable, Replit, Cursor) to acknowledge that they're great when you need to “demo not memo”, but not great (today and maybe ever) at delivering production-grade, secure code. We also make a few detours as we detail a ridiculous week in Lisbon, including:How (shocker!) 90% of the conference was about AIWhy “good enough” AI is not a good place to beWhether we'll graduate to great AIAI's ROI now and in the futureWhy it's still iffy whether AI agents they can be trusted to accomplish complex jobsRobots wander Web Summit, do the Macarena, fall downHow tennis great Maria Sharapova uses (IBM's) AI How the presumptuous Web Summit's app prominently suggests we all message Maria… (as if!) Visa wants to help creators monetize (yay! it me!), using Web3 technologies (yes, they said “Web3”; no, I was not expecting to hear a non-ironic use of that phrase)Why self-driving cars are the best robots — and coming soon to more of EuropeHow much Web Summit pampers (and corrupts) the media: I was like a stuffed goose. Hurray for Portuguese custard and other delicacies!How even the beer at Web Summit was high tech---Featured voices:Tom Haworth: Founder of D13 AI, a UK-based consultancy that “builds intelligent tools that help businesses make sense of messy data.”Me (Dan Blumberg) — I'm the host of CRAFTED. and the founder of Modern Product Minds. HMU if you want to build something great. I love building from zero to one.---And if you please…Share with a friend! Word of mouth is by far the most powerful way for podcasts to growSubscribe to the CRAFTED. newsletter at crafted.fmShare your feedback! I'm experimenting with new episode formats and would love your honest feedback on this and other episodes. Email me: dan@modernproductminds.com or DM me on LinkedInSponsor the show? I'm actively speaking to potential sponsors for 2026 episodes. Drop me a line and let's talk.Get psyched!… There are some big updates to this show coming soon!

This episode is for entrepreneurs, small businesses, solopreneurs, creators, and consultants who feel overwhelmed by AI and don't know where to start. You'll learn how a completely non-technical founder used Generative AI to transform two businesses, pivot her career, and build AI-driven systems without writing a single line of code. In this episode of Open Tech Talks, host Kashif Manzoor speaks with UK-based entrepreneur Marnie Wills, whose journey with Generative AI began unexpectedly while franchising her children's PE business. A copywriting challenge introduced her to Jasper AI, and that single moment reshaped everything. Within two years, she used AI tools to fix messaging issues, transform her franchise model, exit her online fitness business, and finally launch her consulting practice. Marnie breaks down how she built her AI-first operating system using ChatGPT, Claude, Perplexity, Abacus AI, and NotebookLM. She explains why customizing your AI, training it on domain knowledge, and owning your data matters for the coming wave of agentic AI. She shares a powerful real example: building a full CRM + GPT workflow for a keynote speaker in 90 minutes using no-code tools. The system identifies events, drafts applications, and enables a VA to manage the entire pipeline, an example of how AI amplifies human roles rather than replacing them. The conversation also explores ethics, the myth of privacy, overwhelm in SMEs, and the misconception that AI = automation. Her philosophy is simple: AI should amplify humans first. Automation comes last. By the end, you'll understand why courses are no longer the main path, how "10,000 hours" has become "10,000 prompts," and why your next breakthrough may come simply from talking to an AI daily. Episode # 174 Chapters 00:00 Introduction to Marni Wills and Her Journey 02:49 The Impact of Generative AI on Business 06:03 Practical AI Implementation Strategies 08:51 Creating Custom AI Models and Data Ownership 11:56 Vibe Coding: No-Code Solutions for Entrepreneurs 14:38 Learning and Adapting in the AI Landscape 17:30 Ethics and Intellectual Property in AI 20:36 Common Challenges for Small Businesses 23:34 Future Skills in an AI-Driven World Today's Guest: Marnie Wills, Founder, Business with AI Strategist, AI Consultant & Trainer She is a multi-passionate entrepreneur and international athlete, dedicated to revolutionizing the integration of AI into everyday life and business. LinkedIn: MarnieWills What Listeners Will Learn: How a non-tech founder transformed two businesses using Jasper AI, ChatGPT, Perplexity, and agentic tools Why the AI-first mindset matters more than tools, coding, or technical background How to build your personal AI operating system using 5–6 core tools daily Why custom instructions, private models, and a "second brain" dramatically improve AI output Real examples of vibe coding and building no-code platforms with Lovable, Replit, and GoMocka How to reimagine your workday using AI as your Chief Operating Officer Why most people are "lazy AI users" and exactly how to avoid that trap Why automations should come last and why amplifying humans comes first The biggest challenge SMBs face (overwhelm) and the simplest way to begin The future of AI agents and agent-friendly websites Resources: MarnieWills

Eric Simons is the CEO and co-founder of StackBlitz, the company behind Bolt.new, which reached $40 million ARR in five months after launching in October 2024. Bolt.new is an AI-powered platform that allows anyone to build, edit, and deploy full-stack web applications directly in the browser.In this episode of World of DaaS, Eric and Auren discuss:The explosive growth from $0 to $40M ARRPioneering usage-based pricing for AI toolsCompeting with Replit, Lovable, and VercelBuilding WebContainers technology for seven yearsLooking for more tech, data and venture capital intel? Head to worldofdaas.com for our podcast, newsletter and events, and follow us on X @worldofdaas.You can find Auren Hoffman on X at @auren and Eric Simons on X at @EricSimons.Editing and post-production work for this episode was provided by The Podcast Consultant (https://thepodcastconsultant.com)

Jen Abel is GM of Enterprise at State Affairs and co-founded Jellyfish, a consultancy that helps founders learn zero-to-one enterprise sales. She's one of the smartest people I've ever met on learning enterprise sales, and in this follow-up to our first chat two years ago (covering the zero to $1 million ARR founder-led sales phase), we focus on the skills founders need to learn to go from $1M to $10M ARR.We discuss:1. Why the “mid-market” doesn't exist2. Why tier-one logos like Stripe and Tesla counterintuitively make the best early customers3. The dangers of pricing your product at $10K-$20K4. Why you need to vision-cast instead of problem-solve to win enterprise deals5. Why services are the fastest way to get your foot in the door with enterprises6. How to find and work with design partners7. When to hire your first salesperson and what profile to look for—Brought to you by:WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUsLovable—Build apps by simply chatting with AICoda—The all-in-one collaborative workspace—Where to find Jen Abel:• X: https://x.com/jjen_abel• LinkedIn: https://www.linkedin.com/in/earlystagesales• Website: https://www.jjellyfish.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Welcome back, Jen!(04:38) The myth of the mid-market(08:08) Targeting tier-one logos(10:50) Vision-casting vs. problem-selling(15:35) The importance of high ACVs(20:45)  Don't play the small business game with an enterprise company(25:09) Design partners: the double-edged sword(28:11) Finding the right company(36:55) Enterprise sales: the art of the deal(43:21) The problem with channel partnerships(44:41) Quick summary(50:24) Hiring the right enterprise salespeople(56:49) Structuring sales compensation(01:01:01) Building relationships in enterprise sales(01:02:07) The art of cold outreach(01:07:31) Outbound tooling and AI(01:14:08) Lightning round and final thoughts—Referenced:• The ultimate guide to founder-led sales | Jen Abel (co-founder of JJELLYFISH): https://www.lennysnewsletter.com/p/master-founder-led-sales-jen-abel• Mario meme: https://www.linkedin.com/pulse/missing-meme-led-me-woman-johann-van-tonder-im6df• Kathy Sierra: https://en.wikipedia.org/wiki/Kathy_Sierra• Cursor: https://cursor.com• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Justin Lawson on X: https://x.com/jjustin_lawson• Stripe: https://stripe.com• Building product at Stripe: craft, metrics, and customer obsession | Jeff Weinstein (Product lead): https://www.lennysnewsletter.com/p/building-product-at-stripe-jeff-weinstein• He saved OpenAI, invented the “Like” button, and built Google Maps: Bret Taylor on the future of careers, coding, agents, and more: https://www.lennysnewsletter.com/p/he-saved-openai-bret-taylor• OpenAI's CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• Linear: https://linear.app• Linear's secret to building beloved B2B products | Nan Yu (Head of Product): https://www.lennysnewsletter.com/p/linears-secret-to-building-beloved-b2b-products-nan-yu• Gemini: https://gemini.google.com• Microsoft Copilot: https://copilot.microsoft.com• How Palantir built the ultimate founder factory | Nabeel S. Qureshi (founder, writer, ex-Palantir): https://www.lennysnewsletter.com/p/inside-palantir-nabeel-qureshi• McKinsey & Company: https://www.mckinsey.com• Deloitte: https://www.deloitte.com• Accenture: https://www.accenture.com• Building a world-class sales org | Jason Lemkin (SaaStr): https://www.lennysnewsletter.com/p/building-a-world-class-sales-org• Peter Dedene on X: https://x.com/peterdedene• Hang Huang on X: https://x.com/HH_HangHuang• Hugo Alves on X: https://x.com/Ugo_alves• A step-by-step guide to crafting a sales pitch that wins | April Dunford (author of Obviously Awesome and Sales Pitch): https://www.lennysnewsletter.com/p/a-step-by-step-guide-to-crafting• Clay: https://www.clay.com• Apollo: https://www.apollo.io• Jason Lemkin on X: https://x.com/jasonlk• Gavin Baker on X: https://x.com/GavinSBaker• Jason Cohen on X: https://x.com/asmartbear• Baywatch on Prime Video: https://www.primevideo.com/detail/Baywatch/0NU9YS8WWRNQO1NZD5DOQ3I8W6• Playground: https://www.tryplayground.com• ClassDojo: https://www.classdojo.com• Jason Lemkin's post about Replit: https://x.com/jasonlk/status/1946069562723897802—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

There's like a bajillion AI agents.

Ep. 376 This guest grew her Instagram from zero to over 418,000 followers in just a year—almost entirely on autopilot with AI-powered content repurposing. Kipp, Kieran, and guest Sabrina Romanov, of Blotato, dive into how solopreneurs and marketers can go from a simple app idea to launching viral lead magnets, driving traffic, and scaling their brand with AI, even if you don't have technical experience. Learn more on no-code “Vibe coding” tools to build micro apps, automation strategies for distributing your content across eight platforms, and the secret formula to creating content that actually gets noticed (and converts). Mentions Sabrina Romanov https://www.youtube.com/@sabrina_ramonov Blotato https://www.blotato.com/ Lovable https://lovable.dev/ Replit https://replit.com/ Zapier https://zapier.com/ Pegasystams https://www.pega.com/ Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt We're creating our next round of content and want to ensure it tackles the challenges you're facing at work or in your business. To understand your biggest challenges we've put together a survey and we'd love to hear from you! https://bit.ly/matg-research Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Join our community https://landing.connect.com/matg Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by Hubspot Media // Produced by Darren Clarke.

Start building AI apps with Replit: https://replit.com/refer/calumjohnson9Start your business today with Shopify: https://shopify.com/calumjohnsonDownload the exact prompts that Jack uses to create his videos here: https://calum.bio/pages/jack-promptsFollow Us!https://www.instagram.com/calumjohnson1/https://x.com/calum_johnson9Guest: @JackVsAI Timestamps00:00 Intro02:38 Why we released this episode early (the AI gold rush is happening now)07:22 The spark moment: the insane power of generative AI08:47 Nano Banana is the tool that will change everything (Jack's Prediction!)15:05 How small creators are making thousands with AI ads22:41 The 3 tools running 2026 (Sora 2, Nano Banana, VEO 3)25:19 Inside Jack's workflow (the 3-step creative system!!)31:10 Real-world demo: building a product brand from scratch35:16 Why most people fail with AI prompts (and how to fix it)41:00 Turning a static image into a high performance ad!46:50 AI filmmaking is addictive (and what that means)55:10 The first Super Bowl ad made entirely with AI (you have to watch this)1:00:20 The rise of the one-person, million-dollar agency1:04:10 Sora 2 is changing UGC forever....1:13:32 How to actually start TODAY (step-by-step plan)1:17:00 The #1 skill that will help you create world class AI video1:25:58 The moral question: will AI destroy or democratize creativity?About the Guest / About the EpisodeToday's guest is Jack vs AI, he is a VFX artist turned AI video expert with over a decade working in the advertising industry. He's now pioneering the next era of filmmaking, teaching creators how to use tools like Sora 2, Nano Banana, and VEO 3 to produce cinematic videos, ads, and full short films in minutes. In this episode, Jack breaks down the exact process he uses to go from idea to cinematic video, world class product images and UGC video that sells products

Sometimes, you only need one smart idea to change your whole business. On this episode, I talked with Bill McIntosh, an entrepreneur and tech builder, about how fast things are moving with A.I. and business. We broke down how people can build websites, sales funnels, and apps (even full businesses) with just a few prompts thanks to new A.I. technologies. Bill brought in real stories, lessons, and numbers from his hands-on experience and explained the concept of “vibe coding”—a fresh way people are creating online today. If you're wondering how to use A.I. to start or grow your own website, app, or business, you'll find plenty of practical ideas here.Topics DiscussedAI-Assisted Creation: How the evolution of AI is enabling rapid website, app, and sales funnel creation—even for non-technical entrepreneurs.Vibe Coding Explained: Bill demystifies the concept of “vibe coding,” discussing its opportunities and potential pitfalls.Entrepreneurial Principles: The timeless business fundamentals Bill still relies on—even as technology changes.Solving Real Problems: A step-by-step approach to using research and online communities to identify business opportunities and create solutions.Challenges of AI Tools: Early adopter experiences with AI coding platforms, and the need for more accessible, user-friendly solutions.Buildy AI: Bill introduces his new venture, detailing how it helps entrepreneurs launch and scale digital businesses easily.App & Funnel Creation: Practical tips and stories around building sales funnels, websites, and custom apps with AI.Fundraising & Startup Growth: Insights into scaling a tech company through fundraising versus bootstrapping.The Future of AI Entrepreneurship: Predictions for industry adoption, and how “one prompt” could unleash creative and business potential for anyone.Resources MentionedBuildy AI: https://www.buildy.ai/Base44: https://base44.com/Lovable: https://lovable.dev/Replit: https://replit.com/GitHub: https://github.com/Hustle & Flowchart is proud to be part of the HubSpot Network.Hubspot has launched a whole new suite of AI Tools, check them on the Hubspot Spotlight: https://www.hubspot.com/spotlightCheck out other podcasts on the HubSpot Podcast Network: https://www.hubspot.com/podcastnetwork

HEADLINES:♦ Snoonu Founder Backs Mamdani After Criticism for Eating with Hands♦ Abu Dhabi-Based G42 Denies US Claims of Links to Chinese Missiles ♦ UAE Opens Government Sukuk Investments to Individuals for the First Time♦ Jordan Partners With Amjad Masad's Replit to Launch “Siraj,” an AI Learning Assistant Newsletter: https://aug.us/4jqModrWhatsApp: https://aug.us/40FdYLUInstagram: https://aug.us/4ihltzQTiktok: https://aug.us/4lnV0D8Smashi Business Show (Mon-Friday): https://aug.us/3BTU2MY

A16z Podcast: Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- Amjad Masad, founder and CEO of Replit, joins a16z's Marc Andreessen and Erik Torenberg to discuss the new world of AI agents, the future of programming, and how software itself is beginning to build software.They trace the history of computing to the rise of AI agents that can now plan, reason, and code for hours without breaking, and explore how Replit is making it possible for anyone to create complex applications in natural language. Amjad explains how RL unlocked reasoning for modern models, why verification loops changed everything, whether LLMs are hitting diminishing returns — and if “good enough” AI might actually block progress toward true general intelligence. Resources:Follow Amjad on X: https://x.com/amasadFollow Marc on X: https://x.com/pmarcaFollow Erik on X: https://x.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Amjad Masad, founder and CEO of Replit, joins a16z's Marc Andreessen and Erik Torenberg to discuss the new world of AI agents, the future of programming, and how software itself is beginning to build software.They trace the history of computing to the rise of AI agents that can now plan, reason, and code for hours without breaking, and explore how Replit is making it possible for anyone to create complex applications in natural language. Amjad explains how RL unlocked reasoning for modern models, why verification loops changed everything, whether LLMs are hitting diminishing returns — and if “good enough” AI might actually block progress toward true general intelligence. Resources:Follow Amjad on X: https://x.com/amasadFollow Marc on X: https://x.com/pmarcaFollow Erik on X: https://x.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Jack Hoss compares the top AI vibe coding tools—V0, Bolt, Replit, and Lovable—to find the fastest, easiest way to build real estate funnels.In this RealDealCast episode, Jack Hoss tests four of the most talked-about AI website-building platforms — V0, Bolt, Replit, and Lovable — to see which one actually delivers the best results.He gives each platform the same prompt and compares the output, layout, and usability when creating a simple real estate funnel page. You'll discover which AI coding tools save time, where they fall short, and how real estate investors can leverage them to create high-converting marketing pages.You'll learn:What “vibe coding” is and how it simplifies software creationThe pros and cons of V0, Bolt, Replit, and LovableWhich AI builder produces the most usable website for investorsWhy Lovable stood out with the best real-world contentHow to use these tools to quickly test your real estate ideasIf you're a real estate professional or investor looking to automate, market faster, or improve lead funnels, this episode gives you an inside look at the latest AI tools that can save hours of trial and error.

A new paper from the Center for AI Safety proposes a measurable definition of artificial general intelligence—and by their framework, GPT-5 is already 58% of the way there. NLW breaks down how researchers quantified AGI across ten cognitive domains, why memory remains the biggest bottleneck, and what this means for investors, labs, and the timeline to true general intelligence. Plus: Claude Code comes to the web, Replit projects $1B in revenue, and OpenEvidence raises at a $6B valuation.Brought to you by:KPMG – Discover how AI is transforming possibility into reality. Tune into the new KPMG 'You Can with AI' podcast and unlock insights that will inform smarter decisions inside your enterprise. Listen now and start shaping your future with every episode. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.kpmg.us/AIpodcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Blitzy.com - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to build enterprise software in days, not months Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Agent Readiness Audit from Superintelligent - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://besuper.ai/ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614Interested in sponsoring the show? nlw@aidailybrief.ai

Dave and Shannon open Casual Friday with a Shopify nod, then spotlight listener David's “vibe-coded” Replit app for high-school sports. His web iPad tool tracks scoring, fouls, streaks, and biggest leads, exports structured summaries to an AI project, and let him publish recaps before leaving the gym. The hosts urge […] The post FridAI – ChatGPT Did My Taxes?! Business Brain 693 appeared first on Business Brain - The Entrepreneurs' Podcast.

In this episode, Eric shares how to set up AI agents using Lindy, Replit, and Claude Code—and how to choose the best one for your workflow. You'll see real projects like a meeting-prep bot, a Slack recruiting agent, and MCP-powered sub-agents inside Cursor. Eric also covers how to use calendar triggers, send automated messages, and scale ROI-driven workflows that save time and boost productivity. Key takeaways ● Lindy vs. Replit vs. Claude Code: setup and use cases ● Build a meeting-prep agent with social research ● Scale MCP sub-agents for marketing ROI TIMESTAMPS (00:00) AI agents intro and goals (00:19) Lindy setup and templates (04:34) Replit agents and Slack bot (06:44) Claude Code MCP with Cursor (08:21) Agentic leverage and workflow tips

Get Greg's AI Million Dollar Idea Generator prompt: https://clickhubspot.com/kgj Ep. 370 Is making a million dollars with AI really that easy? Kipp, Kieran, and Greg Isenberg, Co-founder of Ideabrowser and host of The Startup Ideas Podcast, dive into Greg's proven frameworks and hands-on tools for building successful AI-powered businesses from scratch. Learn more on how to spot high-potential AI opportunities, the best way to validate product ideas before building, and why leveraging AI tools for audience building and distribution could be your unfair advantage in the AI gold rush. Mentions Greg Isenberg https://www.linkedin.com/in/gisenberg Ideas Browser https://www.ideabrowser.com/ The Startup Ideas Podcast https://podcasts.apple.com/us/podcast/the-startup-ideas-podcast/id1593424985 Lovable https://lovable.dev/ Claude https://claude.ai/ Replit https://replit.com/ Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt We're creating our next round of content and want to ensure it tackles the challenges you're facing at work or in your business. To understand your biggest challenges we've put together a survey and we'd love to hear from you! https://bit.ly/matg-research Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Join our community https://landing.connect.com/matg Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat  ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by Hubspot Media // Produced by Darren Clarke.

In this episode, Tina Tower dives into the rapidly evolving world of artificial intelligence (AI) and its impact on the course creation industry. Tina reflects on her early predictions about AI, how those have played out, and what has really changed in the last 12–24 months—especially when it comes to information accessibility and course value. She offers actionable insights on how to future-proof your business, leverage AI as a superpower, and why human connection and transformation remain at the heart of successful online programs. Resources: Join Her Empire Builder: https://www.herempirebuilder.com/join ChatGPT (for general AI tasks) CastMagic (podcasting support) Canva AI (AI-generated design & artwork) Delphi AI (Tina's AI-powered personal guide, launching soon) Replit, Lovable (tools for customizable learning paths) Key Topics Covered Current AI Landscape: ChatGPT has become the leading AI tool for many tasks. Other platforms used include Cast Magic for podcasting, Canva AI for design, and the soon-to-be-rolled-out Delphi AI for tailored support. AI's Impact on Course Creation: Information is cheaper and more accessible than ever. Traditional evergreen online courses without community or support are becoming obsolete (“the $2K course is dead”). Differentiators now include guided transformation, community, and genuine support. Future Trends in AI & Learning: Rise of AI-powered personalized learning paths (“choose your own adventure” style courses). Hyper-personalized feedback via coaching bots and simulated mentors (for example, Tina's Delphi AI project). Courses shifting focus from information delivery to actual transformation. The Ongoing Value of Human Connection: Emotional intelligence, lived experience, and real-time human interaction are irreplaceable. Personal stories, community, and live events will continue to be major value drivers. Even with AI answering questions, people crave and pay for real human support and engagement. Practical Strategies for Course Creators: Use AI to free up your time by automating backend and admin tasks. Invest more energy into coaching, community, and personalized connection with members. Stay updated, experiment with new AI tools, but don't rush into unproven platforms. Remember, AI enhances your business but does not replace the unique value you bring. AI is reshaping online learning, but it can't replace the power of human connection. The real opportunity is in blending AI efficiency with personal support and community, creating programs that deliver transformation—not just information. Where to find Tina: Her Empire Builder: https://www.herempirebuilder.com/ Instagram: https://www.instagram.com/tina_tower/ YouTube: https://www.youtube.com/@herempirebuilder  

AI Assisted Coding: From Deterministic to AI-Driven—The New Paradigm of Software Development, With Markus Hjort In this BONUS episode, we dive deep into the emerging world of AI-assisted coding with Markus Hjort, CTO of Bitmagic. Markus shares his hands-on experience with what's being called "vibe coding" - a paradigm shift where developers work more like technical product owners, guiding AI agents to produce code while focusing on architecture, design patterns, and overall system quality. This conversation explores not just the tools, but the fundamental changes in how we approach software engineering as a team sport. Defining Vibecoding: More Than Just Autocomplete "I'm specifying the features by prompting, using different kinds of agentic tools. And the agent is producing the code. I will check how it works and glance at the code, but I'm a really technical product owner." Vibecoding represents a spectrum of AI-assisted development approaches. Markus positions himself between pure "vibecoding" (where developers don't look at code at all) and traditional coding. He produces about 90% of his code using AI tools, but maintains technical oversight by reviewing architectural patterns and design decisions. The key difference from traditional autocomplete tools is the shift from deterministic programming languages to non-deterministic natural language prompting, which requires an entirely different way of thinking about software development. The Paradigm Shift: When AI Changed Everything "It's a different paradigm! Looking back, it started with autocomplete where Copilot could implement simple functions. But the real change came with agentic coding tools like Cursor and Claude Code." Markus traces his journey through three distinct phases. First came GitHub Copilot's autocomplete features for simple functions - helpful but limited. Next, ChatGPT enabled discussing architectural problems and getting code suggestions for unfamiliar technologies. The breakthrough arrived with agentic tools like Cursor and Claude Code that can autonomously implement entire features. This progression mirrors the historical shift from assembly to high-level languages, but with a crucial difference: the move from deterministic to non-deterministic communication with machines. Where Vibecoding Works Best: Knowing Your Risks "I move between different levels as I go through different tasks. In areas like CSS styling where I'm not very professional, I trust the AI more. But in core architecture where quality matters most, I look more thoroughly." Vibecoding effectiveness varies dramatically by context. Markus applies different levels of scrutiny based on his expertise and the criticality of the code. For frontend work and styling where he has less expertise, he relies more heavily on AI output and visual verification. For backend architecture and core system components, he maintains closer oversight. This risk-aware approach is essential for startup environments where developers must wear multiple hats. The beauty of this flexibility is that AI enables developers to contribute meaningfully across domains while maintaining appropriate caution in critical areas. Teaching Your Tools: Making AI-Assisted Coding Work "You first teach your tool to do the things you value. Setting system prompts with information about patterns you want, testing approaches you prefer, and integration methods you use." Success with AI-assisted coding requires intentional configuration and practice. Key strategies include: System prompts: Configure tools with your preferred patterns, testing approaches, and architectural decisions Context management: Watch context length carefully; when the AI starts making mistakes, reset the conversation Checkpoint discipline: Commit working code frequently to Git - at least every 30 minutes, ideally after every small working feature Dual AI strategy: Use ChatGPT or Claude for architectural discussions, then bring those ideas to coding tools for implementation Iteration limits: Stop and reassess after roughly 5 failed iterations rather than letting AI continue indefinitely Small steps: Split features into minimal increments and commit each piece separately In this segment we refer to the episode with Alan Cyment on AI Assisted Coding, and the Pachinko coding anti-pattern.  Team Dynamics: Bigger Chunks and Faster Coordination "The speed changes a lot of things. If everything goes well, you can produce so much more stuff. So you have to have bigger tasks. Coordination changes - we need bigger chunks because of how much faster coding is." AI-assisted coding fundamentally reshapes team workflows. The dramatic increase in coding speed means developers need larger, more substantial tasks to maintain flow and maximize productivity. Traditional approaches of splitting stories into tiny tasks become counterproductive when implementation speed increases 5-10x. This shift impacts planning, requiring teams to think in terms of complete features rather than granular technical tasks. The coordination challenge becomes managing handoffs and integration points when individuals can ship significant functionality in hours rather than days. The Non-Deterministic Challenge: A New Grammar "When you're moving from low-level language to higher-level language, they are still deterministic. But now with LLMs, it's not deterministic. This changes how we have to think about coding completely." The shift to natural language prompting introduces fundamental uncertainty absent from traditional programming. Unlike the progression from assembly to C to Python - all deterministic - working with LLMs means accepting probabilistic outputs. This requires developers to adopt new mental models: thinking in terms of guidance rather than precise instructions, maintaining checkpoints for rollback, and developing intuition for when AI is "hallucinating" versus producing valid solutions. Some developers struggle with this loss of control, while others find liberation in focusing on what to build rather than how to build it. Code Reviews and Testing: What Changes? "With AI, I spend more time on the actual product doing exploratory testing. The AI is doing the coding, so I can focus on whether it works as intended rather than syntax and patterns." Traditional code review loses relevance when AI generates syntactically correct, pattern-compliant code. The focus shifts to testing actual functionality and user experience. Markus emphasizes: Manual exploratory testing becomes more important as developers can't rely on having written and understood every line Test discipline is critical - AI can write tests that always pass (assert true), so verification is essential Test-first approach helps ensure tests actually verify behavior rather than just existing Periodic test validation: Randomly modify test outputs to verify they fail when they should Loosening review processes to avoid bottlenecks when code generation accelerates dramatically Anti-Patterns and Pitfalls to Avoid Several common mistakes emerge when developers start with AI-assisted coding: Continuing too long: When AI makes 5+ iterations without progress, stop and reset rather than letting it spiral Skipping commits: Without frequent Git checkpoints, recovery from AI mistakes becomes extremely difficult Over-reliance without verification: Trusting AI-generated tests without confirming they actually test something meaningful Ignoring context limits: Continuing to add context until the AI becomes confused and produces poor results Maintaining traditional task sizes: Splitting work too granularly when AI enables completing larger chunks Forgetting exploration: Reading about tools rather than experimenting hands-on with your own projects The Future: Autonomous Agents and Automatic Testing "I hope that these LLMs will become larger context windows and smarter. Tools like Replit are pushing boundaries - they can potentially do automatic testing and verification for you." Markus sees rapid evolution toward more autonomous development agents. Current trends include: Expanded context windows enabling AI to understand entire codebases without manual context curation Automatic testing generation where AI not only writes code but also creates and runs comprehensive test suites Self-verification loops where agents test their own work and iterate without human intervention Design-to-implementation pipelines where UI mockups directly generate working code Agentic tools that can break down complex features autonomously and implement them incrementally The key insight: we're moving from "AI helps me code" to "AI codes while I guide and verify" - a fundamental shift in the developer's role from implementer to architect and quality assurance. Getting Started: Experiment and Learn by Doing "I haven't found a single resource that covers everything. My recommendation is to try Claude Code or Cursor yourself with your own small projects. You don't know the experience until you try it." Rather than pointing to comprehensive guides (which don't yet exist for this rapidly evolving field), Markus advocates hands-on experimentation. Start with personal projects where stakes are low. Try multiple tools to understand their strengths. Build intuition through practice rather than theory. The field changes so rapidly that reading about tools quickly becomes outdated - but developing the mindset and practices for working with AI assistance provides durable value regardless of which specific tools dominate in the future. About Markus Hjort Markus is Co-founder and CTO of Bitmagic, and has over 20 years of software development expertise. Starting with Commodore 64 game programming, his career spans gaming, fintech, and more. As a programmer, consultant, agile coach, and leader, Markus has successfully guided numerous tech startups from concept to launch. You can connect with Markus Hjort on LinkedIn.

Send us a textIn this episode we interview Evan Read, Head of Marketing at Quipli, a vertical SaaS platform built for independent equipment rental businesses across the U.S. and Canada.What you'll learn in this episode:How to productize your content using AI tools like Replit and v0Why templates and interactive tools outperform traditional blog posts in the age of AI searchThe strategy behind building free micro-SaaS tools to increase inbound leadsHow Evan's team turned non-indexable content into a defensible SEO moatA tactical breakdown of embedding tools directly into CMS pages without developersWhy "content so good it could be sold" should be your new benchmarkReal-world examples of how free tools lead to long-term customer conversions

Our 221st episode with a summary and discussion of last week's big AI news!Recorded on 09/19/2025Note: we transitioned to a new RSS feed and it seems this did not make it to there, so this may be posted about 2 weeks past the release date.Hosted by Andrey Kurenkov and co-hosted by Michelle LeeFeel free to email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.aiRead out our text newsletter and comment on the podcast at https://lastweekin.ai/In this episode:OpenAI releases a new version of Codex integrated with GPT-5, enhancing coding capabilities and aiming to compete with other AI coding tools like Cloud Code.Significant updates in the robotics sector include new ventures in humanoid robots from companies like Figure AI and China's Unitree, as well as expansions in robotaxi services from Tesla and Amazon's Zoox.New open-source models and research advancements were discussed, including Google's DeepMind's self-improving foundation model for robotics and a physics foundation model aimed at generalizing across various physical systems.Legal battles continue to surface in the AI landscape with Warner Bros. suing MidJourney for copyright violations and Rolling Stone suing Google over AI-generated content summaries, highlighting challenges in AI governance and ethics.Timestamps:(00:00:10) Intro / BanterTools & Apps(00:02:33) OpenAI upgrades Codex with a new version of GPT-5(00:04:02) Google Injects Gemini Into Chrome as AI Browsers Go Mainstream | WIRED(00:06:14) Anthropic's Claude can now make you a spreadsheet or slide deck. | The Verge(00:07:12) Luma AI's New Ray3 Video Generator Can 'Think' Before Creating - CNETApplications & Business(00:08:32) OpenAI secures Microsoft's blessing to transition its for-profit arm | TechCrunch(00:10:31) Microsoft to lessen reliance on OpenAI by buying AI from rival Anthropic | TechCrunch(00:12:00) Figure AI passes $1B with Series C funding toward humanoid robot development - The Robot Report(00:13:52) China's Unitree plans $7 billion IPO valuation as humanoid robot race heats up(00:15:45) Tesla's robotaxi plans for Nevada move forward with testing permit | TechCrunch(00:17:48) Amazon's Zoox jumps into U.S. robotaxi race with Las Vegas launch(00:19:27) Replit hits $3B valuation on $150M annualized revenue | TechCrunch(00:21:14) Perplexity reportedly raised $200M at $20B valuation | TechCrunchProjects & Open Source(00:22:08) [2509.07604] K2-Think: A Parameter-Efficient Reasoning System(00:24:31) [2509.09614] LoCoBench: A Benchmark for Long-Context Large Language Models in Complex Software EngineeringResearch & Advancements(00:28:17) [2509.15155] Self-Improving Embodied Foundation Models(00:31:47) [2509.13805] Towards a Physics Foundation Model(00:34:26) [2509.12129] Embodied Navigation Foundation ModelPolicy & Safety(00:37:49) Anthropic endorses California's AI safety bill, SB 53 | TechCrunch(00:40:12) Warner Bros. Sues Midjourney, Joins Studios' AI Copyright Battle(00:42:02) Rolling Stone Publisher Sues Google Over AI Overview SummariesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Morgan Housel, global expert on personal finance, shares powerful lessons on Warren Buffett's hidden struggles, Elon Musk's sacrifices, money trauma and financial habits, how to invest wisely, and the psychology behind saving, spending, and success.  Morgan Housel is a partner at Collaborative Fund, former columnist for The Wall Street Journal, and a speaker on investing, saving, spending, and financial independence. He is also the bestselling author of books, such as: ‘The Psychology of Money' and ‘The Art of Spending Money'. He explains: ◼️ Why more money rarely solves unhappiness ◼️ How envy and social comparison drive overspending ◼️ Why extreme wealth often comes at the cost of health and relationships ◼️ How inflated definitions of “wealth” fuel endless consumerism ◼️ Why true happiness comes from family, friends, and health - not luxury (00:00) Intro (02:33) The Importance of Spending Money (04:43) Why Will This Podcast Make My Life Better? (07:54) Is There Something Wrong With Chasing Status? (10:26) What's the Evolutionary Basis for This Stuff? (15:43) There's Always a Trade-Off (17:55) Saving Addiction (19:41) Can Money Make You Happy? (25:08) Are We All Stuck in a Status Game? (29:14) Is the "Freedom" Culture Actually Making People Unhappy? (31:12) Your Favorite Form of Saving Is Spending (33:17) Jealousy of Other People's Wealth (35:17) The Spectrum of Financial Independence (38:57) How Do People Achieve Financial Independence? (41:32) How Does Dopamine Factor Into All of This? (49:07) We're Wired to Want More (54:51) People Retiring Early Tend to Wish They Hadn't (55:52) Passive Income Myths (58:06) Ads (59:07) Do I Need to Know About Economics for This? (1:05:01) What's Going On in the World? (1:08:55) How Wealth Inequality Is Dividing People (1:10:50) The Charlie Kirk Shooting (1:19:04) Is There a Way Back From This Divide? (1:23:39) What Should We Be Doing to Help? (1:25:28) Are You Optimistic About the Western Economy? (1:27:23) Favorite Chapter From the Book (1:32:34) Ads (1:34:42) Why You Should Try New Things (1:37:29) Are You Chasing a Lifestyle That's Not Right for You? (1:40:48) Does Jack Think Steven Is Happy? (1:49:37) Should We Feel Guilty About the Lack of Contentment? (1:52:49) The Relationship Between Money and Kids (1:55:42) The Exact Formula for Spending (2:02:05) Humble Bubble (2:04:07) Do You Have Major Regrets in Life? Follow Morgan: Instagram - https://bit.ly/3KllnvJ X - https://bit.ly/4pJf4lT You can purchase Morgan's book, ‘The Art of Spending Money', here: https://amzn.to/46F9JTO The Diary Of A CEO: ◼️Join DOAC circle here - https://doaccircle.com/  ◼️Buy The Diary Of A CEO book here - https://smarturl.it/DOACbook  ◼️The 1% Diary is back - limited time only: https://bit.ly/3YFbJbt  ◼️The Diary Of A CEO Conversation Cards (Second Edition): https://g2ul0.app.link/f31dsUttKKb  ◼️Get email updates - https://bit.ly/diary-of-a-ceo-yt  ◼️Follow Steven - https://g2ul0.app.link/gnGqL4IsKKb  Sponsors: Linkedin Jobs - https://www.linkedin.com/doac  Vanta - https://vanta.com/steven   Replit - http://replit.com with code STEVEN

SaaStr 822: SaaStr's Top 10+ AI Agents: AI SDR, AI BDR, AI RevOps + More: The How, The Who, The Why with SaaStr CEO Jason Lemkin Join us in this comprehensive deep dive into the use of AI agents within SaaStr's operations, as requested by many of our followers.  Led by SaaStr CEO and Founder, Jason Lemkin, and SaaStr Chief AI Officer, Amelia Lerutte, we'll detail our journey from having no AI at the start of the year to utilizing 20 different AI agents, including 11 core ones that we rely on daily. Learn from our insights on our most utilized AI agents, their workings, actual data, and how we manage them for optimal results. Discover specific tools like Artisan, Qualified, Gamma, and Replit, and understand how they're integrated into our outbound, inbound, and sales processes. This episode also covers how we've internally developed AI-powered solutions for speaker application reviews, content review, startup valuation, and more. If you're interested in bringing intelligent automation to your business, this session offers practical advice and firsthand experiences to guide you on your AI journey. --------------------- This episode is brought to you by Intercom:   Fin is the #1 AI Agent for resolving complex queries like refunds, transaction disputes, and technical troubleshooting—all with speed and reliability. See how Fin can deliver the highest resolution rates and highest-quality customer experience at fin.ai/saastr.   --------------------- If you're serious about B2B and AI, you need to be in London this December.   SaaStr AI London is bringing together more than 2,000 leaders and founders for two days of practical advice on scaling into the new year.    We'll have speakers flying in from OpenAI, Wiz, Clay, Intercom, and all your favorite SaaS companies, including yours truly with Harry Stebbings for a live 20VC podcast. It'll be fun, and it's all in the heart of London.    Don't miss out: get your tickets with my exclusive discount by going to podcast.saastrlondon.com   ---------------------   Hey everybody, the biggest B2B + AI event of the year will be back - SaaStr AI in the SF Bay Area, aka the SaaStr Annual, will be back in May 2026.    With 68% VP-level and above, 36% CEOs and founders and a growing 25% AI-first professional, this is the very best of the best S-tier attendees and decision makers that come to SaaStr each year.     But here's the reality, folks: the longer you wait, the higher ticket prices can get. Early bird tickets are available now, but once they're gone, you'll pay hundreds more so don't wait.    Lock in your spot today by going to podcast.saastrannual.com to get my exclusive discount SaaStr AI SF 2026. We'll see you there.

This episode was recorded at https://www.imaginationinaction.co/  Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends    Amjad Masad is the Co-Founder & CEO of Replit Salim Ismail is the founder of OpenExO Dave Blundin is the founder & GP of Link Ventures  – Connect with Amjad: https://replit.com/  X: https://x.com/amasad  Connect with Peter: X Instagram Connect with Dave: X LinkedIn Connect with Salim: X Listen to MOONSHOTS: Apple YouTube – *Recorded on Sep 9th, 2025 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Julie Zhuo is the former VP and Head of Design at Facebook (now Meta), author of the bestselling book The Making of a Manager, and co-founder of Sundial, an AI-powered data analysis company. Also, my first-ever podcast guest over 3 years ago!In our conversation, we discuss:1. The three core manager skills that translate directly to managing AI agents2. How her team uses AI to learn new skills 10x faster3. The “diagnose with data, treat with design” framework for balancing gut and data4. Why hypergrowth AI companies have terrible data infrastructure (and why it doesn't matter)5. How to give feedback that actually lands—including Julie's exact script for difficult conversations6. What Julie's teaching her kids about an AI future (hint: it's not coding or STEM)—Brought to you by:Mercury — The art of simplified financesDX — The developer intelligence platform designed by leading researchersPostHog—How developers build successful products—Transcript: https://www.lennysnewsletter.com/p/from-managing-people-to-managing-ai-julie-zhuo—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/172723725/my-biggest-takeaways-from-this-conversation—Where to find Julie Zhuo:• X: https://x.com/joulee• LinkedIn: https://www.linkedin.com/in/julie-zhuo/• Website: https://www.juliezhuo.com/• Newsletter: https://lg.substack.com/• Sundial: https://sundial.so/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Welcome back, Julie!(05:18) The success of The Making of a Manager(08:41) Why AI will make everyone a manager(11:38) The future of management roles(14:00) Empowering teams with AI(21:30) Specific roles being accelerated by AI(26:53) Data analysis in AI companies(32:02) The role of data in design(37:21) The evolving role of managers in the AI era(40:22) Embracing change and uncertainty(42:14) Timeless lessons for managers(49:03) Balancing strengths and weaknesses(57:49) Building a feedback culture(01:05:33) Creating win-win situations(01:09:27) Being aware of your own energy and conviction(01:12:12) Navigating disagreements with higher-ups(01:15:57) AI corner(01:20:08) Contrarian corner(01:23:14) Lightning round and final thoughts—Referenced:• Julie Zhuo on accelerating your career, impostor syndrome, writing, building product sense, using intuition vs. data, hiring designers, and moving into management: https://www.lennysnewsletter.com/p/episode-2-julie-zhuo• Waymo: https://waymo.com/• How we restructured Airtable's entire org for AI | Howie Liu (co-founder and CEO): https://www.lennysnewsletter.com/p/how-we-restructured-airtables-entire-org-for-ai• Cursor: https://cursor.com/• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Inside ChatGPT: The fastest growing product in history | Nick Turley (Head of ChatGPT at OpenAI): https://www.lennysnewsletter.com/p/inside-chatgpt-nick-turley• Behind the founder: Marc Benioff: https://www.lennysnewsletter.com/p/behind-the-founder-marc-benioff• OpenAI's CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• The Magic Loop: https://www.lennysnewsletter.com/p/the-magic-loop• Dunning-Kruger effect: https://en.wikipedia.org/wiki/Dunning%E2%80%93Kruger_effect• Eric Antonow on LinkedIn: https://www.linkedin.com/in/antonow/• Methaphone: https://methaphone.com/• Replit: https://replit.com/• “Baby” by Justin Bieber on Spotify: https://open.spotify.com/track/6epn3r7S14KUqlReYr77hA• Kingdom Rush: https://www.kingdomrush.com/• Dr. Becky on TikTok: https://www.tiktok.com/@drbeckyatgoodinside• Emily Oster on TikTok: https://www.tiktok.com/@profemilyoster• La La Land on Netflix: https://www.netflix.com/title/80095365• Granola: https://www.granola.ai/• Matic robots: https://maticrobots.com/• Limitless pendant: https://www.limitless.ai/• How I AI: https://www.youtube.com/@howiaipodcast—Recommended books:• The Making of a Manager: What to Do when Everyone Looks to You: https://www.amazon.com/Making-Manager-What-Everyone-Looks/dp/0525540423• High Output Management: https://www.amazon.com/High-Output-Management-Andrew-Grove/dp/0679762884/• Zen and the Art of Motorcycle Maintenance: An Inquiry into Values: https://www.amazon.com/Zen-Art-Motorcycle-Maintenance-Inquiry/dp/0061673730• Conscious Business: How to Build Value Through Values: https://www.amazon.com/Conscious-Business-Build-through-Values/dp/1622032020• Good Inside: A Practical Guide to Resilient Parenting Prioritizing Connection Over Correction: https://www.amazon.com/Good-Inside-Guide-Becoming-Parent/dp/0063159481/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

AGENDA: 00:00 Opendoor's Potential and Market Valuation 03:32 Why Did Kaz Leave $300M on the Table to Join Opendoor 04:44 Why Does Kaz Believe OPEN Can Be a Good Business When the Market Doesn't 06:34 How does Kaz Feel About OPEN Becoming a Meme Stock? 17:25 Kaz's $0 Salary but $1BN Stock Based Compensation 23:41 Oracle and OpenAI Partnership: WTF is Going On? 42:21 Microsoft's Investment in OpenAI: A Financial Perspective & Who Has the Power 44:46 Why Sam Altman is the Greatest Politician of our Time 48:33 How Anthropic's Revenue Could Go to Zero Overnight? 50:12 Replit Raises $250M at $3BN Valuation and Higgsfield Raises $50M at $50M ARR 01:06:33 IPO Insights: Figure, Gemini, and Via All Go Public 01:11:26 Why Adobe Have Failed in an Age of AI and What Incumbents Have To Do? 01:13:20 Quick Fire Round: Adobe Up or Down by EOY? What Price Will OPEN Be EOY?  

Howie Liu is the co-founder and CEO of Airtable, the no-code platform valued at around $12 billion. After a viral tweet declared “Airtable is dead” based on incorrect data, Howie led a radical transformation: reorganizing the entire company around AI, becoming an “IC CEO” who codes daily, and achieving over $100 million in free cash flow.What you'll learn:1. The “fast thinking” vs. “slow thinking” team structure that lets Airtable ship AI features weekly (inspired by Daniel Kahneman)2. Why Howie uses AI hourly (not daily) and is Airtable's #1 inference-cost user globally3. Why CEOs must become ICs again in the AI era (and how to restructure your calendar to make it possible)4. Why “playing” with AI tools should be mandatory—Howie tells employees to cancel all meetings for a week to experiment5. The specific skills product managers, engineers, and designers need to develop to succeed in the AI era6. Why evals can kill innovation (and when to use “vibes” instead)—Brought to you by:LucidLink—Real-time cloud storage for teamsDX—The developer intelligence platform designed by leading researchersClaude.ai—The AI for problem solvers and enterprise—Where to find Howie Liu• X: https://x.com/howietl• LinkedIn: https://www.linkedin.com/in/howieliu/• Email: howie@airtable.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Howie Liu and Airtable(04:05) The “Airtable is dead” viral tweet controversy(08:07) The rise of IC CEOs(10:57) AI's paradigm shift in product development(16:27) Specific changes Airtable has made(21:38) Fast- and slow-thinking teams(32:57) The emergence of new form factors in AI models(34:48) Airtable's vision and philosophy(40:20) Empowering teams with AI tools(46:50) Encouraging experimentation and play(50:55) Cross-functional skills in product teams(01:03:35) The importance of evals and open-ended testing(01:08:06) Key strategies for AI-driven success(01:12:43) Counterintuitive startup wisdom(01:22:21) Don't step away from the details that you love(01:25:50) Advice for aspiring engineers and designers(01:30:00) Lightning round and final thoughts—Referenced:• Airtable: https://www.airtable.com/• All In podcast: https://allin.com/• Nikita Bier on X: https://x.com/nikitabier• Figma: https://www.figma.com/• The AI-native startup: 5 products, 7-figure revenue, 100% AI-written code | Dan Shipper (co-founder and CEO of Every): https://www.lennysnewsletter.com/p/inside-every-dan-shipper• Every: https://every.to/• Cursor: https://cursor.com/• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Windsurf: https://windsurf.com/• Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO): https://www.lennysnewsletter.com/p/the-untold-story-of-windsurf-varun-mohan• Rippling: https://www.rippling.com/• Omni: https://www.airtable.com/lp/ai-psu-plp• How ChatGPT accidentally became the fastest-growing product in history | Nick Turley (Head of ChatGPT at OpenAI): https://www.lennysnewsletter.com/p/inside-chatgpt-nick-turley• Palantir: https://www.palantir.com/• Harvey: https://www.harvey.ai/• v0: https://v0.dev/• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Replit: https://replit.com/• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• Lovable: https://lovable.dev/• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (CEO and co-founder): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• Runway Game Worlds: https://play.runwayml.com/login• Sesame: https://www.sesame.com• NotebookLM: https://notebooklm.google• Salesforce: https://www.salesforce.com• Andrew Ofstad on LinkedIn: https://www.linkedin.com/in/aofstad/• Stripe: https://stripe.com/• Eames chair: https://en.wikipedia.org/wiki/Eames_Lounge_Chair• OpenAI's CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• IDEO design thinking: https://designthinking.ideo.com/• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• The Studio on AppleTV+: https://tv.apple.com/us/show/the-studio/umc.cmc.7518algxc4lsoobtsx30dqb52• Silicon Valley on HBOMax: https://www.hbomax.com/shows/silicon-valley/b4583939-e39f-4b5c-822d-5b6cc186172d• Self Edge: https://www.selfedge.com/• Studio D'Artisan: https://www.selfedge.com/studio-dartisan• Whitesville T-shirt: https://store.toyo-enterprise.co.jp/shopbrand/ct48/• Guest Series | Dr. Paul Conti: How to Understand & Assess Your Mental Health: https://www.hubermanlab.com/episode/guest-series-dr-paul-conti-how-to-understand-and-assess-your-mental-health—Recommended books:• Thinking, Fast and Slow: https://www.amazon.com/Thinking-Fast-Slow-Daniel-Kahneman/dp/0374533555• The Three-Body Problem: https://www.amazon.com/Three-Body-Problem-Cixin-Liu/dp/0765382032• Trauma: The Invisible Epidemic: How Trauma Works and How We Can Heal From It: https://us.amazon.com/Trauma-Invisible-Epidemic-Works-Heal/dp/1683647351/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Asha Sharma leads AI product strategy at Microsoft, where she works with thousands of companies building AI products and has unique visibility into what's working (and what's not) across more than 15,000 startups and enterprises. Before Microsoft, Asha was COO at Instacart, and VP of Product & Engineering at Meta, notably leading product for Messenger.What you'll learn:1. Why we're moving from “product as artifact” to “product as organism” and what this means for builders2. Microsoft's “seasons” planning framework that allows them to adapt quickly in the AI era3. The death of the org chart: how agents are turning hierarchies into task networks and why “the loop, not the lane” is the new organizing principle4. Why post-training will soon see more investment than pre-training—and how to build your own AI moat with fine-tuning5. Her prediction for the “agentic society”—where org charts become work charts and agents outnumber humans in your company6. The three-phase pattern every successful AI company follows (and why most fail at phase one)7. The rise of code-native interfaces and why GUIs might be going the way of the desktop8. What Asha learned from Satya Nadella about optimism—Brought to you by:Enterpret—Transform customer feedback into product growth: https://enterpret.com/lennyDX—The developer intelligence platform designed by leading researchers: http://getdx.com/lennyFin—The #1 AI agent for customer service: https://fin.ai/lenny—Transcript: ⁠https://www.lennysnewsletter.com/p/how-80000-companies-build-with-ai-asha-sharma⁠—My biggest takeaways (for paid newsletter subscribers): ⁠https://www.lennysnewsletter.com/i/171413445/my-biggest-takeaways-from-this-conversation⁠—Where to find Asha Sharma:• LinkedIn: https://www.linkedin.com/in/aboutasha/• Blog: https://azure.microsoft.com/en-us/blog/author/asha-sharma/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Asha Sharma(04:18) From “product as artifact” to “product as organism”(06:20) The rise of post-training and the future of AI product development(09:10) Successful AI companies: patterns and pitfalls(12:01) The evolution of full-stack builders(14:15) “The loop, not the lane”—the new organizing principle(16:24) The future of user interfaces: from GUI to code-native(19:34) The rise of the agentic society(22:58) The “work chart” vs. the “org chart”(26:24) How Microsoft is using agents(28:23) Planning and strategy in the AI landscape(35:38) The importance of platform fundamentals(39:31) Lessons from industry giants(42:10) What's driving Asha(44:30) Reinforcement learning (RL) and optimization loops(49:19) Lightning round and final thoughts—Referenced:• Copilot: https://copilot.microsoft.com/• Cursor: https://cursor.com/• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Inside ChatGPT: The fastest growing product in history | Nick Turley (Head of ChatGPT at OpenAI): https://www.lennysnewsletter.com/p/inside-chatgpt-nick-turley• GitHub: https://github.com• Dragon Medical One: https://www.microsoft.com/en-us/health-solutions/clinical-workflow/dragon-medical-one• Windsurf: https://windsurf.com/• Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO): https://www.lennysnewsletter.com/p/the-untold-story-of-windsurf-varun-mohan• Lovable: https://lovable.dev/• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (CEO and co-founder): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• Bolt: http://bolt.com• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder and CEO of StackBlitz): https://www.lennysnewsletter.com/p/inside-bolt-eric-simons• Replit: https://replit.com/•Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• He saved OpenAI, invented the “Like” button, and built Google Maps: Bret Taylor on the future of careers, coding, agents, and more: https://www.lennysnewsletter.com/p/he-saved-openai-bret-taylor• Sierra: https://sierra.ai/• Spark: https://github.com/features/spark• Peter Yang on X: https://x.com/petergyang• How AI will impact product management: https://www.lennysnewsletter.com/p/how-ai-will-impact-product-management• Instacart: http://instacart.com/• Terminator: https://en.wikipedia.org/wiki/Terminator_(franchise)• Porch Group: https://porchgroup.com/• WhatsApp: https://www.whatsapp.com/• Maslow's Hierarchy of Needs: https://www.simplypsychology.org/maslow.html• Satya Nadella on X: https://x.com/satyanadella• Perfect Match 360°: Artificial intelligence to find the perfect donor match: https://ivi-fertility.com/blog/perfect-match-360-artificial-intelligence-to-find-the-perfect-donor-match/• OpenAI's GPT-5 shows potential in healthcare with early cancer detection capabilities: https://economictimes.indiatimes.com/news/international/us/openais-gpt-5-shows-potential-in-healthcare-with-early-cancer-detection-capabilities/articleshow/123173952.cms• F1: The Movie: https://www.imdb.com/title/tt16311594/• For All Mankind on AppleTV+: https://tv.apple.com/us/show/for-all-mankind/umc.cmc.6wsi780sz5tdbqcf11k76mkp7• The Home Depot: https://www.homedepot.com/• Dewalt Powerstack: https://www.dewalt.com/powerstack• Regret Minimization Framework: https://s3.amazonaws.com/kajabi-storefronts-production/sites/2147500522/themes/2148012322/downloads/rLuObc2QuOwjLrinx5Yu_regret-minimization-framework.pdf—Recommended books:• The Thinking Machine: Jensen Huang, Nvidia, and the World's Most Coveted Microchip: https://www.amazon.com/Thinking-Machine-Jensen-Coveted-Microchip/dp/0593832698• Tomorrow, and Tomorrow, and Tomorrow: https://www.amazon.com/dp/0593466497Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed.My biggest takeaways from this conversation: To hear more, visit www.lennysnewsletter.com

Amjad Masad is the founder and CEO of Replit, a cloud-based coding platform. He is also an outspoken voice on cultural and educational shifts in technology. www.replit.com The ultimate wireless hack. Make the switch at Visible dot com. Learn more about your ad choices. Visit podcastchoices.com/adchoices