Podcasts about Saas

On the podcast: why app economy disruption won't happen as fast as everyone seems to think, how AI is just as useful for defending against copycats as creating them, and why the real barrier to app success is still distribution, not code. This conversation is shorter than usual and will be featured in RevenueCat's State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:

Is your traditional SaaS experience becoming obsolete? In this new 20-minute rapid-fire format, Sam Jacobs, AJ Bruno, and Asad Zaman tackle a specific listener question: How does a senior operator transition from a legacy B2B SaaS role into a high-growth AI company? The market is shifting toward a meritocracy where recent hands-on capability outweighs decades of tenure on a CV. The hosts break down exactly how to position yourself for companies like CoreWeave and EliseAI. They discuss why hiding your lack of technical engineering skills is a mistake, how to build a portfolio of "work product" using low-code tools like Replit and Claude, and why being able to articulate the failures of AI models is actually the strongest signal of fluency. Key Takeaways: - Stop relying on a static resume and start building a portfolio of practical applications. As Sam Jacobs notes, the hiring landscape has shifted so that "your work product needs to speak for itself... demonstrating that you're capable of working with these tools, not theoretically, but practically through your conversations that you're having with hiring managers." - We are entering a career reset where agility beats seniority. Asad Zaman warns that "whenever there is a platform shift... the value of experience goes down a little bit," which creates a massive opportunity for younger leaders to "move up faster if you present in a very compelling manner because people are not looking at titles the same way." - Cultural currency matters as much as technical skill. To be taken seriously by founders in this space, you must consume information where they do. As Asad Zaman puts it, "If they find out that you're not on AI Twitter or AI X, I think they will think you're not a serious person... the information is not gonna be found in these old school channels." Connect with the Hosts: Host: Sam Jacobs - https://www.linkedin.com/in/samfjacobs/ Host: AJ Bruno - https://www.linkedin.com/in/ajbruno3/ Host: Asad Zaman - https://www.linkedin.com/in/azaman1/   Topline is not JUST a YouTube Channel! Subscribe to Topline Newsletter: https://www.joinpavilion.com/topline-newsletter Tune into Topline Podcast, the #1 podcast for founders, operators, and investors in B2B tech: https://www.joinpavilion.com/topline-podcast Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast: https://www.joinpavilion.com/topline-slack   Chapters: 00:00 Intro 01:58 Viewer Q: Transitioning to AI 02:48 Show Work Product, Not Just CVs 04:36 Applying SaaS Principles to AI 05:58 The AI-First Mentality 08:58 Articulating AI Limitations 11:30 The Meritocracy Shift 13:55 Unexpected AI Wins 21:27 Staying Culturally Relevant 24:29 Summary: How to Get Hired  

Mitchell Green is a legendary growth equity investor and the Founder and Managing Partner of Lead Edge Capital, a firm with over $5 billion in assets under management. Known as a relentless "money maker", Mitchell has led investments in the likes of Bytedance, Toast, Procore, Duo Security and more. AGENDA: 0:00 The SaaS Apocalypse: Why Incumbents Aren't Going to Zero 05:50 "Dead Money": Why Public Software Estimates Were Too High 08:15 Leverage is the Enemy: Lessons from the 1999 Retail Crash 11:50 The Truth About Growth Equity: Zeroes vs. 10X Returns 15:40 Mainframes to AI: Why Oracle and SAP Will Thrive 20:35 The "Stock-Based Comp" Scandal: Silicon Valley's Hidden Crime 24:35 ByteDance vs. The World: Why China Could Win the AI War 31:50 Selling is the Job: Why Buying is the Most Glamorous Part of VC 35:45 Too Many Tourists: Why 50% of VCs Shouldn't Be in the Business 44:10 The Gross Dollar Retention Rule: The Only Number That Matters in SaaS

On the podcast: product-driven retention as the foundation for lifecycle marketing, working backwards from results to nail activation, and why talking to individual users can lead you astray.This conversation is shorter than usual and will be featured in RevenueCat's State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:

Core Reasons for Being Trapped: The primary reasons owners cannot leave their businesses include strong emotional attachment (37%), financial dependence on the business income (25%), inability to sell at a profitable price (20%), and a lack of suitable buyers (19%). According to LinkedIn. Workload and Burnout: Many owners are forced to work longer hours, with 60% struggling to get time off and 54% having given up hobbies and personal activities, according to Medium. For Laurie Barkman: Growing up, I launched my first services business at age 10, mowing lawns, raking leaves, and babysitting. In high school, I leaned into leadership, learned how to address challenges head-on, and made a lasting impact on my community. That drive to build winning teams took me to Cornell University, where I studied Industrial and Labor Relations. I began my career at Ingersoll-Rand, a global engineering firm, working shoulder-to-shoulder with engineers and plant teams to reengineer operational processes for productivity and cost improvements. It was there that I first saw how analytical and technical leaders think.   Later, I earned my MBA from Carnegie Mellon University, intentionally choosing a rigorous quantitative program to refine the analytical skills I knew I'd need to lead and advise in structured, technical environments. Over the years, I built a career spanning Fortune 500s and startups, leading teams through high-growth transformation, including time in logistics, SaaS, e-commerce, and operations, often in collaboration with engineers, data-driven founders, and technical teams.   The search was part of a long-term succession plan. A third-generation family business and leading transportation and logistics company in North America sought a new divisional CEO. In the interview process, I was told, “We're not interviewing you for the next 2 years…we're interviewing you for the next 20.” Playing the long game excited me. Taking on this role was a perfect storm of high expectations, internal resistance, and every eye was watching. I wasn't necessarily who they expected, but I knew how to create value. I steadied the ship and shifted mindsets towards transformation. Eventually, we guided the company to a successful sale to a Global Fortune 50 company. After the acquisition was completed, I stayed on as a senior executive and served on the Integration Steering Committee, advising on the launch of new e-commerce fulfillment services. Back to the original notion of staying in the company for 20 years. As things played out, my tenure was only three. Was I disappointed? Heck no. I realized that while we may have a plan, sometimes plans change for good reason. The acquisition “put some money in my jeans” and gave me the flexibility to pursue my entrepreneurial passions.   For more information: https://lauriebarkman.me/ LinkedIn: @LaurieBarkman Learn more about your ad choices. Visit megaphone.fm/adchoices

Alex Rampell and Erik Torenberg speak with Mike Cannon-Brookes, cofounder and CEO of Atlassian, about how to make sense of the SaaS selloff, why not all software companies face the same AI-driven risks, and how Atlassian is thinking about the shift from records to processes. They also examine the real design challenge of getting everyday users to trust and benefit from AI agents in enterprise workflows.   Resources: Follow Alex Rampell on X:  https://twitter.com/arampell Follow Erik Torenberg on X:   https://twitter.com/eriktorenberg Follow Mike Cannon-Brookes on X: https://twitter.com/mcannonbrookes Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show 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.

Have you ever bought a ticket to a show and wondered why the experience still feels strangely disconnected, with one app for ticketing, another for marketing, another for refunds, and a dozen spreadsheets held together by late nights and good intentions? In this episode of Tech Talks Daily, I'm joined by Ritesh Patel, co-founder of Ticket Fairy, to talk about the technology behind live events and why it has lagged behind other industries in some surprisingly familiar ways. Ritesh makes the case that most organizers are operating more like creative founders than corporate operators, building "mini cities" for a weekend with tiny teams, tight budgets, and very little margin for error. That reality shapes every technology decision, and it explains why fragmented tools and siloed data can become a hidden tax on the business. Ritesh walks me through Ticket Fairy's full stack approach, bringing ticketing, marketing, CRM, logistics, and payments into a single system, and why unifying data changes the economics of running an event. We dig into practical examples that go beyond vague AI talk, including how small workflow fixes can speed up entry, improve the on-site experience, and even translate into real revenue uplift once you multiply time savings across thousands of attendees. We also get into where AI agents and large language models are already finding a foothold in events, particularly around unstructured documents like artist specs, supplier agreements, and operational paperwork that can swallow hundreds of hours. Ritesh shares why "AI-native" should mean more than a writing assistant in a text box, and what it looks like when AI becomes an extension of a lean events team, including a prototype voice agent designed to handle common ticket-holder questions without creating new support bottlenecks. If you're interested in the real business mechanics of events, and how SaaS, payments, data, and AI can quietly shape everything from entry lines to repeat attendance, this conversation offers a fresh way to think about an industry that touches all of us, even when we don't think of it as a tech story. And as a bonus, Ritesh leaves a music recommendation that sent me back to an album I had not played in years, Burial's Untrue, with "Archangel" as the track to start with. After listening, tell me this, where do you think unified data and practical AI will make the biggest difference in live experiences over the next couple of years, on the promoter side or the fan side, and why?

Learn How to Let Consumption Drives Revenue & Turn Content Into Your Most Powerful Sales Engine Consumption drives revenue and in this episode, we pull back the curtain on exactly why the businesses winning right now aren't the ones with the biggest ad budgets, but the ones building audiences that actually engage with their content. We're joined by two powerhouse guests who reveal the three ingredients guaranteed to drive revenue for creators, why the traditional marketing funnel born in the 1800s is officially dead, how AI is leveling the playing field for first-time sellers, and why the most overlooked hiring strategy might just be a Facebook Live stream. Whether you're selling digital products or scaling a service business, this episode will completely change how you think about content, community, and conversion. Justin Smith is the CEO of SamCart.com, where he helps tens of thousands of creators sell smarter, boost conversions, and maximize customer value at every touchpoint. With a background in seed-stage startups and high-growth SaaS companies, Justin has been a zero-to-one product builder, scaled companies to millions in revenue, and contributed to over $100M in capital raised. Ricky Regalado is a serial entrepreneur, visionary, and the driving force behind Rosalotto, a Latino-owned building services company expanding across 20+ states, as well as the founder of the niche hit podcast Cleaning and Cocktails, which now reaches over 2 million impressions per week across 30 countries. Both guests bring rare, real-world insight into what it actually takes to grow beyond seven figures. KEY TAKEAWAYS: The more content your audience consumes, the shorter your sales cycle becomes. Grit, compelling sales copy, and a warm audience are the three non-negotiables for creator success. Being world-class at your craft does not automatically translate into revenue without strong conversion copy. AI tools like ChatGPT helped SamCart jump onboarding conversions from 3% to 16% using AI-generated landing pages. The traditional short-form funnel is dead and today's buyers only operate in impulse purchase or long-term content relationship mode. Google's post-2020 data confirms buyers cycle through exploration and evaluation before committing, making consistent content non-negotiable. A community-driven brand is one of the most powerful and underutilised recruiting strategies available to growing businesses. Celebrating every role in your organisation, not just leadership, directly drives pride, performance, and retention. Growing your business is hard, but it doesn't have to be. In this podcast, we will be discussing top level strategies for both growing and expanding your business beyond seven figures. The show will feature a mix of pure content and expert interviews to present key concepts and fundamental topics in a variety of different formats. We believe that this format will enable our listeners to learn the most from the show, implement more in their businesses, and get real value out of the podcast. Enjoy the show. Please remember to rate, review and subscribe to the podcast so you don't miss any future episodes. Your support and reviews are important and help us to grow and improve the show. Follow Charles Gaudet and Predictable Profits on Social Media: Facebook: facebook.com/PredictableProfits Instagram: instagram.com/predictableprofits Twitter: twitter.com/charlesgaudet LinkedIn: linkedin.com/in/charlesgaudet Visit Charles Gaudet's Wesbites:  www.PredictableProfits.com www.predictableprofits.com/community https://start.predictableprofits.com/community  

Join us on the STILL RELEVANT tour: https://simulationtheory.ai/16c0d1db-a8d0-4ac9-bae3-d25074589a80Join Simtheory: https://simtheory.ai

On the podcast: breaking free from the paid acquisition treadmill, how to repurpose offline events into millions of online impressions, and why a celebrity partnership can go viral but still completely flop.This conversation is shorter than usual and will be featured in RevenueCat's State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:

On the podcast: what the explosion in new apps means for the market, how the top 10% of apps grew 306% while the median barely beat inflation, and why hard paywalls convert 5X better than freemium.This conversation is focused on RevenueCat's State of Subscription Apps report. Head to https://www.revenuecat.com/state-of-subscription-apps to download the report.Top Takeaways:

Episode Title: Tesla's Building A Robot Army — And A $1.5 Trillion Merger | Cern Basher Short Description: Bitcoin isn't money — it's a cyber security technology. And we're going to need it desperately. Cern Basher, CFA, breaks down why AI agents will choose Bitcoin, the Tesla robotaxi economics, the SpaceX–xAI mega-merger, and why Strategy might be the world's largest digital security company. Full Description: How do you constrain trillions of AI agents roaming the internet? Not with passwords and code — AI will hack all of that. You do it with physics. You do it with Bitcoin. In Part 2 of my conversation with Cern Basher — CFA charterholder, CIO of Brilliant Advice, and one of the sharpest analysts at the intersection of AI, Bitcoin, and macroeconomics — we go deep on Jason Lowery's classified Softwar thesis and why the US Department of Defence placed it under security review. Cern explains why Bitcoin is actually a cyber security protocol hiding in plain sight, disguised by the word "coin" in its name — just like gunpowder was disguised as medicine for years before engineers figured out what it really was. We also break down the deflationary tsunami hitting every industry — SaaS companies losing billions in market cap overnight, Salesforce and the consulting industry being hollowed out by AI agents, and why deflation is actually something we should celebrate, not fear. We already lived through it with the iPhone and we loved it. Cern shares his brilliant analogy for why Tesla is massively undervalued — a kid running a lemonade stand who's secretly training to become a surgeon, but Wall Street only sees the lemonade. We get into whether SpaceX and Tesla will merge, the economics of putting AI data centres in space, manufacturing pharmaceuticals in zero gravity, and the incredible opportunity for any individual to own a small fleet of robotaxis and replace their income. For New Zealand, this is a call to action. Be first. Be forward-thinking. Or watch other countries leapfrog us. In this episode we discuss: Bitcoin as a cyber security technology, not just money — and why that's even more valuable Jason Lowery's Softwar thesis — proof of work as digital defence Why AI agents unanimously choose Bitcoin for transactions The gunpowder analogy — Bitcoin's real use case is hiding in plain sight Google's centralised censorship of health and supplement companies OpenClaw and the Pandora's box of billions of AI agents SaaS is cooked — Salesforce, consulting, and legal getting hollowed out Deflation is good — the iPhone proved it and we all benefited The ice cutter disruption story — this is nothing new The K-shaped economy — will abundance lift the bottom 50%? Universal high income and making goods freely available like water Strategy (MicroStrategy) as the world's largest digital security company Tesla undervalued — the lemonade stand to surgeon analogy Will SpaceX and Tesla merge? Pros, cons, and what Cern is hearing AI data centres in space, pharma in zero gravity, and Starship economics Owning your own robotaxi fleet — replacing your income New Zealand's opportunity to leapfrog the world Links mentioned: Cern Basher on X: https://x.com/CernBasher Brilliant Advice: https://www.brilliantadvice.net Jason Lowery's Softwar thesis (MIT): https://dspace.mit.edu/handle/1721.1/153030 Cern's GDP & Dematerialisation post: https://x.com/CernBasher/status/1913993658572984440 Part 1 of this episode: https://youtu.be/eh0hKibH6Zs

Simon Swords founded Fundipedia after starting in a backyard shed building bespoke software. Originally a custom development shop, his firm built a data governance platform for major buy-side asset managers including HSBC, Barclays, and Legal & General. Over time, Fundipedia evolved into a high-retention enterprise SaaS platform with strong net revenue retention and Rule of 40 performance. Simon navigated long consultative sales cycles, regulatory tailwinds, and a tightly networked financial services market to build a durable recurring revenue engine. After turning down an initial offer, Simon grew ARR further and ultimately sold in 2024 at approximately 10x ARR. He exited fully, used ChatGPT extensively in diligence, and now reflects on endurance, discipline, and surviving long enough for luck to compound. Key Takeaways Survive First — Don't make a mistake that kills you or the business. Staying alive creates the opportunity for luck to compound. Enterprise Patience — Two-year sales cycles are normal at the top end. Persistence and reputation matter more than speed. Rule Of 40 Discipline — Strong growth plus profitability gives founders leverage in exit timing and valuation. Problems Over Product — Founders obsess over product; buyers care about solving painful, expensive problems. Build To Exit Cleanly — Structure the company so it runs without you before you start acquisition conversations. Quote from Simon Swords, Founder of Fundipedia "I think the most important thing is not to make a mistake that kills you or the business. While you're in the arena and you've not been taken out yet, dragged off by the hyenas or lions, whatever they used back in the Roman days, you've still got a chance to make something magical happen. "You do something stupid, kill the business, kill your reputation, you're done. Entrepreneurs hate the word luck. I do feel luck. I am lucky. Of course I'm lucky. I have to be lucky. You make your own luck.  "But I'll tell you what I didn't do. I didn't make a mistake that killed me or the business and the entire way through. Even when I was going through hell, never, no matter how neurotic or anxious or all the negative kind of traits you can imagine would have flown through me. I never made a mistake that killed the business." Links Simon Swords on LinkedIn Fundipedia on LinkedIn Fundipedia website FE fundinfo website Podcast Sponsor – LaunchBay LaunchBay helps B2B software companies automate client onboarding and implementation so customers activate faster and everyone stays aligned. If your onboarding includes data collection, setup steps, approvals, training, or any level of customization, LaunchBay replaces the messy mix of emails, spreadsheets, and meetings with a clear, all-in-one onboarding system. Teams use LaunchBay to onboard clients faster, stay on top of follow-ups automatically, and deliver a smoother experience, without hiring more people or adding more tools. Visit launchbay.com/practical and get 25% off your first 3 months on any LaunchBay plan. The Practical Founders Podcast Tune into the Practical Founders Podcast for weekly in-depth interviews with founders who have built valuable software companies without big funding. Subscribe to the Practical Founders Podcast using your favorite podcast app or view on our YouTube channel. Get the weekly Practical Founders newsletter and podcast updates at practicalfounders.com. Practical Founders CEO Peer Groups Be part of a committed and confidential group of practical founders creating valuable software companies without big VC funding.  A Practical Founders Peer Group is a committed and confidential group of founders/CEOs who want to help you succeed on your terms. Each Practical Founders Peer Group is personally curated and moderated by Greg Head.

Send a textIn this episode of the WTR Healthcare Happenings, Adam Fraser, COO of Omniscient Neurotechnology—a privately held, Australian‑based but U.S.-focused company pioneering AI‑driven brain mapping—joins Water Tower Research Co‑Founder Tim Gerdeman and Healthcare Analyst Robert Sassoon for a deep dive into the future of clinical connectomics. The discussion explores how Omniscient's flagship platform, Quicktome, uses advanced AI to transform complex brain data into intuitive, Google‑Maps‑style network visualizations that enhance neurosurgical planning, support coma and mental‑health assessments, and inform broader brain‑care decisions. Fraser also walks through the company's growth trajectory, funding milestones, and strategy to scale across the U.S. hospital market while laying the groundwork for global expansion and broader neurotech partnerships. The conversation concludes with Omniscient's long‑term vision to build a comprehensive “brain data economy” capable of powering next‑generation innovations—from BCIs and DBS to emerging solutions like TMS for major psychiatric conditions.

Send a textHow to turn founder instincts into a repeatable pipeline engine. Guest: Javier Lozano, Fractional CMO & GTM Leader  --  Founder-led sales is often the fastest way to get an early-stage SaaS company off the ground. But at some point, the very thing that helped you close your first customers becomes the bottleneck preventing your company from scaling.In this episode of SaaS Backwards, Ken Lempit sits down with fractional CMO and GTM leader Javier Lozano of Bolder Media to break down why founder-led sales eventually stop working—and how SaaS leaders can turn founder instincts into a repeatable revenue engine.They discuss how to extract the winning patterns inside a founder's head, transform those insights into positioning and messaging, and build a predictable pipeline that sales teams can execute at scale.You'll also learn why hiring sales leaders too early often backfires, how to create a “blue ocean” positioning that separates your SaaS product from crowded markets, and what investors really look for when evaluating early-stage SaaS growth.If you're a SaaS founder, CRO, or GTM leader trying to move beyond founder-led growth, this episode provides a practical framework for building a scalable go-to-market engine.Key Topics CoveredWhy founder-led sales works early but breaks at scaleTurning founder knowledge into a repeatable SaaS GTM playbookHow positioning and messaging create predictable pipelineWhy hiring a CRO too early can stall growthBuilding a scalable revenue engine before raising capital---Not Getting Enough Demos? Your messaging could be turning buyers away before you even get a chance to pitch.

What if your next breakthrough isn't more hustle, but ruthless focus on what actually matters?Scott Levy, Founder and CEO of ResultMaps, joins Sivana Brewer for a candid, zero-fluff conversation on why most CEOs and COOs are drowning in distraction and what separates “second in command” leaders who skyrocket growth from those stuck grinding. They pull apart why ambitious teams spiral into task overload, the critical metrics every department truly needs, and the battle-tested rituals that free up your brain for high-stakes decisions.Ready to step off the treadmill of constant fires, endless meetings, and “yet another platform” promises? This episode exposes the cost of delay and throws you a direct path out, real systems, real clarity, real results. If you wait, you risk another year of burnout and missed breakthroughs. Press play now for inside strategies unavailable anywhere else.Timestamped Highlights[00:54] – Why “good” content became too dangerous for Speaker A to binge (and what that reveals about focus)[02:09] – The real operations heartbreaks hidden behind entrepreneurial success stories[07:09] – Why small teams will devour giants in the AI revolution (the Special Forces lesson nobody teaches MBAs)[10:34] – The shockingly simple hack for bypassing bloated CRMs and running your pipeline on autopilot[12:02] – How to extract a Vivid Vision in 30 minutes—no trust falls required[16:13] – “Eff your feelings, follow the plan?” Dissecting the truth (and limits) of systemizing emotional chaos[26:52] – The fatal flaw of cascading goals—and what truly separates winners from burned-out operators[44:36] – The raw moment CEOs finally break—and why some refuse to suffer the same mistakes twice About the GuestScott Levy is the Founder and CEO of ResultMaps, a cutting-edge SaaS platform designed to help founders and leadership teams obliterate operational friction, scale clarity, and get real results. With a background spanning management consulting, software, and building systems for high-growth companies, Scott's passion is turning entrepreneurial chaos into decisive execution. He's especially known for integrating technology and coaching with powerful simplicity.

On the podcast: why web onboarding should sell the problem instead of the solution, how discounted paid trials are beating free trials, and why creative that flopped for app ads might crush it for web funnels.This conversation is shorter than usual and will be featured in RevenueCat's State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:

What does it take to grow a SaaS business from $1 million to $5 million annual recurring revenue when your revenue has plateaued? Michael Sliwinski, founder of the productivity app Nozbe, joins Nathan Barry to diagnose the core issues his business faces and map out a clear path forward. Michael, who flew all the way from Europe for this conversation, dives into the challenges of competing in a crowded market, the impact of a product rebuild, and the search for a compelling new positioning. This episode is a masterclass in auditing your business, identifying roadblocks, and strategizing for breakthrough growth, especially for founders navigating a competitive landscape and aiming for their next big milestone.Timestamps:00:00 Introduction01:05 Michael's journey to Nozbe02:51 From side hustle to $1 million ARR04:47 The Japan growth explosion06:17 Rebuilding Nozbe from scratch10:14 Competing with industry giants12:58 Breaking down business metrics and building blocks19:07 Understanding max MRR and the S-curve22:42 The flatlining awareness and traffic25:02 Expansion and multi-seat customers29:43 Legacy customers on the old vs. new Nozbe30:52 Strong customer retention and low churn37:25 Key metrics and dashboard visibility39:46 Accountability through weekly revenue meetings42:07 The effectiveness of current content strategies46:27 Partnership success with a productivity consultant51:09 Direct sales for partners53:01 Reframing positioning for growth56:19 The core promise of Nozbe: The tool teams actually use59:43 The "boulder pushing" analogy1:02:18 Strategy for identifying and incentivizing new partners1:11:34 Tapping into true fans for new partner leads1:14:57 Michael's reflections and next stepsIf you enjoyed this episode, please like and subscribe, share it with your friends, and leave a review. I read every single one.Learn more about the podcast: https://nathanbarry.com/showFollow Nathan:Instagram: https://www.instagram.com/nathanbarryLinkedIn: https://www.linkedin.com/in/nathanbarryX: https://twitter.com/nathanbarryYouTube: https://www.youtube.com/@thenathanbarryshowWebsite: https://nathanbarry.comKit: https://kit.com/?utm_campaign=29661554-nathan_barry_show&utm_source=youtube&utm_medium=podcast&utm_term=nathanbarryshow&utm_content=youtube_descriptionFollow Michael:X: https://twitter.com/msliwinskiInstagram: https://www.instagram.com/michaelsliwinskiMastodon: https://social.nozbe.com/@michaelNozbe: https://nozbe.comFeatured in this episode:Kit: https://www.kit.comNozbe: https://nozbe.comHighlights:02:17 – ZDNet feature blew up Nozbe05:13 – iPad app success in Japan09:27 – Impact and the $5M goal11:54 – Customer loyalty despite competitors22:15 – Demo meetings and their conversion rates32:27 – Customers prepaid until 204057:33 – Why simpler is better for teams

Feeling financially successful on paper but trapped in real life can change everything. In this episode, C-suite executive and board director, Leilani Latimer, shares how unintentionally becoming house poor while living in Italy as a young adult forced her to confront anxiety, control and independence. When she sold the house, those lessons ultimately set the foundation for her to achieve a healthier, more balanced relationship with money. Leilani is a global C-suite executive and NACD Certified Board Director who leads companies through critical inflection points. She drives growth, connects strategy to execution and builds operating models designed for scale and resilience. Her track record spans B2B, SaaS, Marketplace, AI/ML and Enterprise Technology companies across public, PE-backed and venture-backed organizations. She has held executive roles in sales, marketing, commercial operations, product and customer success, bringing a comprehensive understanding of how these functions integrate to drive performance. She is currently a strategic advisor to growth-stage technology companies, partnering with Founders, CEOs, VCs and PEs to shape business models, strengthen go-to-market execution and design the teams and structures required to scale. She has led early-stage companies in supply chain, retail and medtech through transformational growth, building commercial and marketing engines from startup through acquisition, delivering significant revenue growth and improved forecasting. Leilani’s deep technology expertise includes 25 years with Sabre Inc. (NASDAQ: SABR), a global leader in travel, hospitality and transportation technology. In leadership roles spanning sales, product, marketing, strategy and sustainability across North America and Europe, key achievements include repositioning the hospitality business for IPO, developing award-winning enterprise sustainability systems and products, restructuring global product investment plans and helping build the Southern European division from inception to 15% market share. Leilani currently serves as an Independent Board Director at Black Diamond Group (TSE: BDI), Sedex and Narratize, and as an Advisory Board Member at Fiutur and FoodMesh. Her board contributions span governance, strategic capital allocation, compensation and risk oversight. Her unique perspective on corporate risk and reputation is shaped by her expertise in sustainability, over 15 years of leadership in European markets and extensive experience across multiple industries. Based in San Francisco, she is a dual US and Italian citizen. Independence, Investing and Intentional Choice Leilani's story reminds us that financial independence is not a fixed destination but an evolution. From navigating cross-border careers and complex benefits systems to rethinking what fairness means in partnership, she shows how money can either create anxiety or expand possibility. Today, her focus on teaching her children to invest early, supporting female founders and building values-aligned portfolios reflects a deeper truth: wealth is a tool for choice. The freedom to decide where you live, what you support and how you show up in the world is the ultimate return on investment. If you are considering board service, navigating career transitions or thinking more intentionally about how and where you invest, an Aspiriant advisor can help you align your wealth with your values and design a strategy that supports both independence and impact. Follow Money Tales on Spotify, Apple Podcasts or YouTube Music for more real stories that inspire smarter, more intentional decisions with your money.

What happens when the real "close" isn't the signature—but the customer's commitment to consume? In this episode, Peter Winick talks with Art Fromm, a keynote speaker and sales enablement leader focused on what many B2B organizations still miss: the costly gap between pre-sales and sales. Art's thought leadership centers on building seamless partnership, not a messy handoff, so clients win sooner and revenue sticks longer. Art makes the shift unmistakable. The market moved from one-time enterprise transactions to SaaS, recurring revenue, adoption, retention, and usage-based economics. That means "closing" is no longer the finish line. It's the starting gun. If customers don't adopt and succeed, the deal never really happened. From there, Art outlines his core platform: aligning pre-sales and sales into a true divide-and-conquer team. No delegation games. No dictation. Just shared ownership of the client outcome. He points to research suggesting seamless collaboration can lift sales impact materially—because the biggest unlock is often already sitting on the table. This is also where Art's content engine comes in. He's clear that thought leadership isn't a "someday" project. It's a practice. Write. Publish. Learn what lands. Then refine. He shares how he captures and distributes ideas through posts, podcasts, and a dedicated hub on his website (teamsalesdevelopment.com) with events and articles that keep the thinking accessible. Art's book "Making SEAMless Sales" plays a central role in the platform. He describes it as a labor of love and a high-leverage calling card—less about book sales, more about clarifying the model and creating a door-opener for bigger engagements. If you lead sales, enablement, customer success, or go-to-market in a subscription business, this episode will challenge your definitions. The question isn't "Did we win the deal?" The question is "Did we build the conditions for sustained consumption and retention?" Three Key Takeaways: • "Closing" has changed: In SaaS and recurring revenue models, the win isn't the signature—it's adoption, usage, and retention (a commitment to consume). • Alignment is the lever: The biggest performance unlock is often true partnership between pre-sales and sales—shared ownership of client outcomes, not a handoff. • Thought leadership that sells: A repeatable writing engine (book + ongoing blogs/articles) clarifies the framework, builds authority, and creates higher-quality conversations that lead to revenue. If Art's "commitment to consume" mindset resonated, queue up Steve Watt's episode "Using Thought Leadership to Earn Your Way Into Sales Consideration" next. Steve digs into how thought leadership earns you a seat in the buying conversation before prospects are ready to buy—the same strategic shift from "pitching" to building credibility and momentum. Listen to both and you'll get a one-two punch: how to align your revenue team for outcomes (Art) and how to use thought leadership to generate and accelerate demand (Steve).

Brought to you by TogetherLetters & Edgewise!In this episode: Several Meta employees have started calling themselves 'AI builders'Lovable-hosted app littered with basic flaws exposed 18K users, researcher claimsForget solid-state batteries – researchers have made a lithium-ion breakthrough that could boost range and drastically lower costsUber acquiring parking app SpotHero as it moves beyond ride-hailing and food deliveryHow a doomsday AI blog post wiped out billionsThis App Warns You if Someone Is Wearing Smart Glasses NearbyHands on: I'm super impressed with the Galaxy S26 Ultra's new Privacy DisplayTesla touts California robotaxis but does nothing to get permitsFedEx will refund customers for Trump's tariffs — if there ever are any refundsAndroid's Find Hub adds iPhone-like luggage tracking linksAnother Oracle outage is messing up US TikTokTech Rec:Sanjay - TogetherLettersAdam - Wisper FlowFind us here:sanjayparekh.com & adamjwalker.comTech Talk Y'all is a proud production of Edgewise.Media.

In today's market, AI valuations are expanding faster than fundamentals can justify. Companies with minimal free cash flow are being priced as if dominance is already secured.  Capital continues to circulate between venture portfolios, strategic partners, and ecosystem incumbents, reinforcing growth narratives that assume liquidity remains abundant. But markets don't reward narratives forever. When growth slows or capital tightens, the question shifts from projected upside to structural durability. Does the business generate real cash? Does it control proprietary data that compounds value? Is it positioned to be acquired or forced to sell? This is where discipline separates operators from spectators. Daniel Nikic has spent years operating inside early-stage capital markets, studying transaction patterns, portfolio structures, and acquisition behavior. From that vantage point, valuation is less about headlines and more about capital flows, strategic adjacency, and who holds liquidity when cycles turn. In this episode, we look beneath the surface of today's AI enthusiasm to examine what actually drives valuation, how smart founders reverse-engineer an exit, and why companies entering a slowdown with balance sheet strength don't just survive, they consolidate.   About the Guest  Daniel Nikic is an investment research professional and entrepreneur dedicated to delivering tailored insights and strategic solutions. With over two decades of experience, Daniel has built a career dedicated to empowering investors and businesses with actionable insights. Born and raised in Canada, He earned a Bachelor's Degree in Business Administration from Brock University, where his passion for market dynamics and financial analysis began to take shape. ​As the founder of Cohres, a boutique investment research firm, Daniel specializes in helping high-net-worth individuals, venture capitalists, and startups navigate complex markets and emerging industries such as AI, SaaS, and data. His career journey includes impactful roles at HB Reavis, where he managed €500M real estate projects, Zursh, where he led AI-focused initiatives, and Azafran Capital Partners, where he developed investment strategies and managed data teams. ​Through his dedication to innovation, Daniel combines a global perspective with a hands-on approach, helping clients uncover growth opportunities and achieve their goals. His leadership has positioned Cohres as a trusted name in investment research and strategic planning. To learn more, visit https://www.danielnikic.com/.    About Your Host From pro-snowboarder to money mogul, Chris Naugle has dedicated his life to being America's #1 Money Mentor. With a core belief that success is built not by the resources you have, but by how resourceful you can be. Chris has built and owned 19 companies, with his businesses being featured in Forbes, ABC, House Hunters, and his very own HGTV pilot in 2018. He is the founder of The Money School™ and Money Mentor for The Money Multiplier. His success also includes managing tens of millions of dollars in assets in the financial services and advisory industry and in real estate transactions. As an innovator and visionary in wealth-building and real estate, he empowers entrepreneurs, business owners, and real estate investors with the knowledge of how money works. Chris is also a nationally recognized speaker, author, and podcast host. He has spoken to and taught over ten thousand Americans, delivering the financial knowledge that fuels lasting freedom.   Resources Get Your FREE Copy Of 'The Private Money Guide'  and 'Mapping Out The Millionaire Mystery'.  Keep up with us every week on our FREE Live webinars for more conversations like this, and as a BONUS, get our newest mini-ebook instantly upon signing up! https://moneyschoolrei.com/wednesday-webinar (digital download). Dive into money, mindset, and motivation videos on my YouTube Channel, and be sure to subscribe so you can be notified of our weekly LIVE streams. Find out about our next weekend workshop, and see what others are saying: https://www.moneyschooltraining.com/registration.      

Who dares to make predictions in the current landscape? We do!  Our Predictions are back. Will our track-record continue on a high or will we be fundamentally wrong? Listen in to our Predictions for 2026 Navigation: Intro What will 2026 be all about? AI, AI and … more AI The big Hardware movements Of Start-ups and VCs Regulatory & Geopolitical Headwinds… and the Wars Fintech, Crypto and Frontier Tech Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show:   Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Bertrand Schmitt Introduction Welcome to Tech Deciphered Episode 74. That would be an episode about some predictions about 2026. What will be 2026 all about? I guess this year is probably starting with a bang. We saw the acquisition of xAI by SpaceX. We saw an acquisition from Grok by NVIDIA. What’s your take about what would be the big themes in 2026? I guess it would be for sure about AI and space. Nuno Goncalves Pedro What will 2026 be all about? Yeah. I predict a year that will be a little bit more of a year of reckoning in some way. There will be a lot of things that I think we’ll start seeing through. The fact that we are in the midst of an amazing transformational era for technology, the use of AI, but at the same time, obviously, a ridiculous bubble that is going alongside it as we’ve discussed in previous episodes. I think that we’ll start seeing some early reckonings of that, companies that might start failing, floundering, maybe a couple of frauds along the way, etc. I’ll tell you what I will not make many predictions about today, which is geopolitics. Geopolitics, I will not make predictions at all. Who the hell knows what’s going to happen to the world this year in 2026? I don’t dare making any predictions on that. Back to things where I would make predictions. I think on AI, we’ll have a little bit of reckoning. We’ll talk about it a little bit more in detail during this episode. Interesting elements around the hardware and physical space. Physical space, we just dedicated a full episode to it. We won’t go into a lot of details on that, but definitely on the hardware side, we’ll talk a little bit more about it. The VC landscape is going through an incredible transformation. We’ll talk about it today as well and some of our predictions for this year. What will happen to the asset class? It seems to be transforming itself dramatically. Obviously, that has a very direct impact on startups, so we’ll talk about that as well. And then to close a little bit the chapter on this, we will address some regulatory and geopolitical, let’s call it, headwinds without making maybe too many complex predictions. We shall see. Maybe by that time of the episode, we will be making some predictions. You guys should stay and listen to us, and maybe we will actually make some predictions about the geopolitical transformations that we will see this year in the world. Then last but not the least, we’ll talk about fintech, crypto, frontier tech, and a couple of other areas before concluding the episode. A classic predictions’ episode. We normally have a pretty good track record on some of these, but right now, the world is going a bit interesting, not to say insane. Bertrand Schmitt Yes, and going back to some news, Groq technically was not acquired, but, practically, it’s as if it got acquired. I’m talking about Groq, G-R-O-Q. The AI semiconductor company focused on inference AI, and it was late December. It was a way to end the year. This year, we started again with an acquisition of xAI by its sister company, SpaceX. I guess that’s where we are starting. AI, AI and … more AI We are going to start on AI. That’s definitely the big stuff. Everything these days, I guess, is about AI or has to have some connection with AI, or it doesn’t matter. I think every company in the world has seen that. You have to have the absolute minimum on AI strategy. You better execute on this strategy and show results, I would say. For the companies that were not AI native, you truly have to have a way to transform yourself. I guess at some point, the stretch might be too much, and it’s not really reasonable. Then you maybe better stay on what you are doing, especially if you’re in tech, you better be moving faster to AI. Nuno Goncalves Pedro Just to highlight, and I think throughout the episode, you’ll see that there’re obviously a lot of implications that would manifest themselves into capital markets. I mean, we’ll specifically talk about VCs and startups later on. But the fact that everything needs to be AI, the fact that there’s so much innovation happening right now, in my opinion, and this is maybe the first pre-topic to AI, is we’ll see a tremendous increase in M&A activity this year across the board. I mean, we’ve seen already some big acquihires we mentioned in some of our previous episodes, but we’ll see a lot more activity on M&A this year. Normally, that’s a precursor to the opening of capital markets. I predict also that there will be a reopening of the IPO market that never really reopened last year, to be honest. M&A, a lot more, reopening of the IPO market. Normally, it happens in the second or third quarter of the year. That’s what my M&A friends tell me. First quarter of year, everyone’s figuring out stuff. Then last quarter of the year, things should be more or less closed. Maybe the third quarter is the big quarter. We shall see. But definitely, as a precursor to our conversation today, I think we’ll see a lot of M&A, and we’ll see reopening of the IPO mark. Bertrand Schmitt I guess last year was not as big as you could expect on M&A given the tariff situation announced in April and May. I mean, it became quite tough to do IPO in such market conditions. Definitely, we can hope for something dramatically different in 2026. I guess talking about public markets and IPO, I guess the big one everyone is waiting for is SpaceX. SpaceX getting even more interesting with its xAI acquisition. Nuno Goncalves Pedro Do you think that because of the acquisition, it’s more likely that it will happen this year, or because of the acquisition, it’s less likely that it will happen this year? Bertrand Schmitt That’s a good question. My guess is the acquisition of xAI is all about xAI needing more financing and cheaper financing. This acquisition is a pathway to that. SpaceX being a much bigger company, a company that is also making much more revenues. I could bet that there is higher probability that, actually, SpaceX will go public in order to finance itself. At the same time, will it have enough time to prepare itself for the IPO given this acquisition just happened? Can they do that in 6 months? I mean, if anyone can do it, I guess it’s Elon Musk. It’s a strategy to present an even more attractive company with an even more interesting story, a story of vertical integration from AI to space. I guess the story as it’s presented itself right now, it’s one about having your AI data centers in space. Because in space, you have much better solar energy production with solar panels. You have a perfect cooling situation because you are in space. Thanks to Starlink, you have the mean to communicate between the satellites and with Earth itself. I think if someone can pull up a story like AI data center in space, I guess Elon Musk can. There is, of course, a lot of questions about is it practical? Is it economical? Yes. I certainly agree. I’m not clear on the mass, and can you make it work? Again, I mean, Elon Musk single-handedly, with SpaceX, managed to transform the space market on its head. I mean, they are the biggest satellite launching company in the world. They have the most satellites in the world. I mean, I’m not sure I would bet against him, and I guess I would probably believe that he could pull up something. Time frames, different story. The 2-3 years data center in space for AI as cheap as on Earth, I have more trouble with that one. I mean, it’s a usual suspect with Elon Musk. You promise something unachievable in a few years, but, ultimately, you still manage to reach it in 5 or 10. Again, I would not bet against the strategy. Nuno Goncalves Pedro Yeah. I’ve talked to a couple of space experts, people that have launched rockets, and have worked JPL, NASA, and a couple of other places, etc. For what it’s worth, their feedback is, “No way in hell, and we’re decades away.” We’ll see. I mean, to your point, Elon has pulled very dramatic stuff. Not as fast as he normally says he’s going to pull it, but within a time span that we all see it. Difficult to bet against him. In terms of actually the prediction, maybe to respond to the prediction as well, will SpaceX IPO? I’m going to make a prediction that has a very high likelihood of missing the mark, but I think Tesla’s going to buy and merge them both into it. It’s going to become a public company through Tesla. That’s my hypothesis. Bertrand Schmitt No. That’s supposed to be it. That’s how you solve that. Nuno Goncalves Pedro And Elon controls the whole universe. X, xAI, Tesla, SpaceX, all under one umbrella beautifully run. And SolarCity is well in there, of course, so wonderful. Bertrand Schmitt That’s possible. Certainly, you are not the only one thinking Tesla will acquire or merge with SpaceX. To remind everyone, Tesla is around 1.3, 1.5 trillion market cap. Depending on the day, SpaceX seems to be valued at similar range, 1.2, 1.3 trillion. It looks like it’s the most valued private company at this stage. These are companies of similar size, so that’s one piece of the puzzle. When you think about the combined company, we could be talking about a 3 trillion entity. Playing right here with the biggest companies in the marketplace today. Nuno Goncalves Pedro With a couple of tweets from Elon, it will rapidly get to 4 to 5 trillion. Bertrand Schmitt That’s so tricky. Nuno Goncalves Pedro Yes. On AI and back to AI, one thing I think that we’re about to see is this will probably be the year of agentic AI. Obviously, we predict a lot of growth on that side of the fence, in particular on the enterprise B2B side. We see a lot of opportunities coming through. From our perspective, at least at Chamaeleon, we generally believe that there’s going to be a lot of movements on agentic AI. It’s also going to be probably the year of the first big fails of agentic AI that will be newsworthy. There will be some elements about that loop and how it gets closed that will happen. I think we might see some scandals already. We’re already seeing the social network of bots talking to bots. We will see other scandals going on this year even in the consumer space and in the bot to bot space, which we now can talk about or in the AI agent to AI agent space. My prediction is we will see some move forwards. There’ll be some dramatic funding rounds along the way. We’ll see a couple of really cool things out of the gates coming out that are really impressive, but we’ll also see the first big misses of the technology stack. I don’t think we’ll go fully mainstream yet this year, so it’s probably maybe something more for 2027 along the way. That would be my prediction again. I think enterprise will lead the way. We’ll definitely see a lot of stuff on consumer as well that is cool. Then we’ll all have our own personal assistance in our hands, basically, literally in our phones. Bertrand Schmitt Going back to agentic AI, we also started the year with some pretty dramatic move. I mean, the launch of Clawdbot, renamed OpenClaw. I mean, this stuff took fire in like a week or 2. It was coded by just one person who actually didn’t even code the product but used AI to build the product, 100% used AI, proposing some new ways also to leverage AI to do coding. He has a pretty unique approach. It’s not vibe coding. I would say it’s a better way to do that. Then the surprising evolution with the launch of a social network for AI agents, Moltbook. I mean, this stuff, probably there is some fake in it. But at the same time, I think it’s quite impressive because it’s the first time we see truly 100,000 plus agents communicating directly to each other. Yeah. I mean, that’s the first time we see surfacing the possibility of some sort of hive mind on the Internet. It’s pretty surprising. Right now, all of this is a hack done in a few days. By end of year, by 2 years, 3 years, we might discover that, actually, the best approach to AI might not be the AI assistant like we are doing today, but a combination of hundreds of thousands of AI working closely together. We might be witnessing the first sign of new intelligence in a way. Nuno Goncalves Pedro Things like this social network might either be Skynet, the beginning of Skynet. They might be the beginning of Her, or they might just be a fad and nothing really happens. It’s just interesting to see what these agents are doing. Bertrand Schmitt Totally. Nuno Goncalves Pedro Obviously, there are real and clear and present dangers of some of the integrations of AI we’re seeing in the market. Interesting enough, and I’ll ask you for your prediction a bit, Bertrand. I think we’ll probably see the first big mishap of AI being used in some infrastructural decision in the age of AI. I mean, we’ve seen AI issues in the past and software issues in the past. We talked in previous episodes about that as well. Mishaps of software that have led to people dying. But I think probably the first big mishap will happen this year as well. Very public mishap of the use of AI and serve its interactions with infrastructure or something that’s very platform related, etc, that will have big impact that everyone will notice. That’s my prediction for the year as well. We’ll have the first big oops moment, as I would call it, for AI in this new age of full on AI. Bertrand Schmitt I would say first some perspective. I think today, people are not using AI directly for life and death decision, at least not that I’m aware. We’re not going to let AI fly a plane, for instance, tomorrow so you can be, reassured. At the same time, given there is such a race to AI, there definitely might be some mistakes. We were talking about the social network for AI agents, Moltbook. Apparently, all the keys used to secure the AI were shared by mistake because it was not properly locked down. We can see that indirectly, mistakes will be made for sure. Two, it’s highly probable that some people will trust AI too much to do some stuff, and this stuff might not work and might have some grave consequence. Hopefully, there is not so much of this. Hopefully, it’s mostly AI used for the good. But you’re right. I mean, at some point, the more we use the technology, the more there would be issue. I mean, it’s highly probable. Nuno Goncalves Pedro That will lead me to another prediction, which is, and we’ll talk about more of it later, but it probably will lead to the first significant movement in terms of regulatory environment certainly in the US at some point if it happens in the US in particular, where there will be some movement that will be like, “Hey, you guys can’t do this anymore.” Because this will probably emerge from mismanaged interfaces. From systems having access to stuff that they shouldn’t have access to in the first place. Talking a little bit more about what’s happening in AI. You’ve already mentioned some of the issues that relate actually to security and cybersecurity. We keep talking about AI. We keep talking about all these infrastructure pieces and platforms that are being built. I think we’ll have a lot more incidents like the one you just mentioned where things will be shared that shouldn’t have been shared, where people will break systems and get into it, etc. Let’s see where that takes us, which is a little bit ironic because, obviously, with AI, the promise is that cybersecurity becomes more robust as well because there’re agents working on our behalf on the cybersecurity side. There’s also agents working on the other side. Bertrand Schmitt It’s a constant race. It’s the attackers, defenders. Each time you have new technology, you have a new race to who is going to attack or defend the best. Each new wave of technology, it’s an opportunity to challenge the status quo. Nuno Goncalves Pedro The attackers have been winning, and I feel they’ll continue winning in 2026. I think it’s going to still be a year of attack. We’ll see more and more breaches, more and more stuff that will happen. Bertrand Schmitt I don’t know if they will win. I mean, it’s normal that they win once in a while. For sure, some infrastructure is not updated as it should. Some stuff are not managed as it should, so there will always be breaches. I don’t know if things are dramatically going to change because, again, everyone who cares who is going to update his infrastructure with AI for defense. There is no question that you have no choice. We will see. That I don’t know. For sure, AI will be used to attack directly with AI. Maybe you’re able to do bigger, larger scale attack. Or thanks to AI, you are simply able to create new type of attacks more easily. AI can be used behind the scene as a way to prepare and organise new type of attacks, even if it’s not used directly live in the battle. Nuno Goncalves Pedro One topic that we’ll come back to later is the geopolitics of everything, but maybe more broadly. On the geopolitics of AI, it’s very clear that we have an arms race going on. Obviously, the US on the one hand, China on the other hand is the two extremes, putting tremendous amount of capital into data centers just at the base of that infrastructure. Chipset development, chipset access, a huge theme in terms of the export restrictions, etc, that are being forced by the US. I think it will continue. From a European standpoint, obviously, they’re stuck between a rock and a hard place, to be very honest. Let’s see what happens on that side of the fence. My view of the world is that certainly from a US and China perspective, we’re going to see a lot more movements in 2026, like big movements. The Chinese movements we always see in delay.  It takes us a couple of months, sometimes even more than that to understand exactly what’s going on. I think we’re going to see some huge moves this year in terms of the States, the United States of America, and China really pouring capital into the creation of the next big winners around AI. I think the US is obviously more visible. We see a lot of these companies. We’ve just discussed xAI and its acquisition by SpaceX or merger. I don’t know what they’re calling it exactly. Effectively, on the China side, the movements I think are already very big. As I said, it will take a while to figure out exactly what those moves are. One thing that I propose is that at some point, China will have very little dependency on chipsets from the US. I’m not sure it’s going to happen this year, but I think the writing is on the wall. Irrespective of any other geopolitical issues that is coming to the fore at this moment in time. That’s one of the key areas or in arenas of fight. Bertrand Schmitt It makes sense. If you are China, you will look at what happened. You would think that you cannot just depend on the largest of one country. It makes rational sense, the same way it makes rational sense for the US to limit exports to China because there is value to delay some peer pressure that could use these technologies for good but also for bad. If you were an ally of the US, that would be one thing. But when you are not an ally of the US, that certainly should be a different perspective. Maybe one last point concerning agents, I think there will be a lot that will revolve around coding. We can see OpenAI with Codex. We can see Cloud with code. There was, of course, [inaudible 00:18:28] that was trying to be big on agentic coding. I think agentic coding was one of the big transformation in 2025 and is going to get bigger in 2026. I think for a lot of people who do coding, there was a radical transformation in terms of what you can achieve, what you can do, how much you can trust AI to help you code. I start to think we might see this year, the replacement of not just one AI replace one coder, but one AI replace a full team because of the new ability to manage that at scale. Coding might be a common activity where you are going to think about outcomes, think about objective, think about how you organise, but not really coding by itself anymore. A big change, like you used to code, directly your hand on the stuff, but step by step, everyone is going to become a manager of agent. I think in one year, we saw enough transformation to think that in the coming year, the transformation can be even more dramatic. Nuno Goncalves Pedro The big Hardware movements Now switching gears to hardware. Obviously, a lot of movements in 2025 and over the last few years. One piece of thesis that we’ve had long-standing at Chamaeleon is that we will see the emergence of AI devices. Some of them have been tremendous failures as we discussed in the past. I predict that we’ll have a couple of really interesting full stack AI devices in the market this year. Why does that matter? Because, as many of you know, obviously, there’s compute that can happen in data centers and cloud infrastructure all over the world, but also there’s compute that can happen at the edges. The more you can move to the edges and the more you can create devices that actually allow you to have user experiences that are very distinctive at the edge, the more powerful some of these devices might become. I predict Apple will not be the first to launch anything on this. I predict probably OpenAI, after the acquisition of IO, will maybe not launch something this year, but will announce something this year. I’ll step back on that prediction. They’ll announce something this year, but maybe not launch. But we’ll start seeing some devices that have some interesting value in the market, probably devices that are AI devices, but they are very focused on very specific user flows, and so very much adequate to specific activities. I won’t make a prediction on that, but I think areas that would make sense for that to happen would be obviously around fitness, health, et cetera, et cetera, where we already have the ascendancy of products like Oura Ring and others out there. Definitely, that’s one area that might have quite a lot of developments. I think AI-first devices, devices that are very focused on compute at the edges, providing user flows that are AI-enabled to end users, we’ll see a lot more of that and a lot more activity this year. Again, I don’t think Apple will be necessarily ahead of the game. Again, maybe OpenAI will give us something to at least think about and look forward to. Bertrand Schmitt First, I’m not sure it will be that transformational because if it’s not in your phone, in your pocket, there is only so much you can do with it, and there is only so much computing power you will have. I’m doubtful it would be really impactful this year. Nuno Goncalves Pedro I feel we’ve been discussing this shift of paradigm in input and output. For me, some of these devices could lead to that shift. Because, again, a mobile phone is not a great long-term paradigm for the usage that we have because it’s really constrained by the screen. The screen is really what takes most of the battery life away. If we didn’t have that screen, what could we do? If we have the block that is as big as a mobile phone, and it didn’t have a screen, it was just compute, that’s a mini computer, a microcomputer. Bertrand Schmitt That’s a fair point, but I don’t see that transformation this year. That’s really more my point. I can see that you can have AI-enabled smart glasses, and it’s clear there is a race to AI-enabled smart glasses. My point is more to go beyond the gadget, it would take quite a while. It would need to have cameras. It would need to analyse what you see. It would need to hear what you hear. Again, it might come, but then at some point, it would be okay, what do you do with it? We have the example of the movie Her. That’s showing Her what it could be. There are definitely possibilities. It’s clear that if you take the big VR headset like the Apple Vision Pro, there is a failure from that perspective in the sense that I think it’s a great, amazing device. The big problem is that it’s doing way more that makes sense. I think there will be a clearer separation between your smart AR glasses that has to be light, that has to be always unconnected, and that’s primarily there to help you make sense of the world around you. The true VR headset that doesn’t really require much in terms of AI, and it’s just there to immerse you in a different world. For this, we know, unfortunately, in some ways, that there is not a lot of demand for it. Maybe there is little demand because you are too hidden in your own world. The technology is not working well enough yet. There are a lot of reasons. But I think Apple trying to do both at the same time, AR and VR, with the Vision Pro, was a pretty grave structural mistake. I think we would see a clearer line of separation between the two. There is bigger market opportunity for AR glasses. That, I certainly agree. There is opportunity to connect that to a computing device. As you talk about, your glasses are your screen, your phone becomes something in your pocket connected to your glasses. Nuno Goncalves Pedro For me, Apple has their way of doing things. From the perspective of what you said, they normally really plan their devices. Even if it’s a big shift in terms of a new area, like they tried with the Vision Pro, and we criticised them for launching it as a device that should have been more of a dev device that they really launched as a full-on device, but that’s their playbook, classically. I think Apple needs to change how they put products out and how they experiment with those products, et cetera. I think they have enough money to be doing everything all the time and figuring it out. If they don’t want to put it out, then they need to do a lot more hell of testing internally with their silos, but they should be playing across all these arenas, VR, AR, everything. They just should put devices out that are either ready for prime time, or they should call it something else. They should call it like this is a dev device or whatever it is. Bertrand Schmitt I agree with you. My complaint is more that it was marketed as a consumer device when it was not. It was a true developer device. Two, they tried to mix the two at once, and it made no sense. No one is going to walk in their home or in the street with their Vision Pro on their head. You have to be deranged, quite frankly, to have use cases like this. I think that for me is a crazy mistake from a company like Apple that prides itself in pure UI, pure user interface, very well-designed device for one specific use case, not mixing the two use cases. We still don’t have Macs with a touchscreen, you know?  We still don’t have an iPad with a good OS that makes use of this great hardware. For some strange reason, they decided to mix everything in the Vision Pro with a device that weighs a ton on your head and is so uncomfortable. That’s why, for me, I’m like, “Guys, what is wrong? Why did you let this team run crazy?” I hope at some point, Apple will go back to the drawing board. My understanding is that that’s what they are doing. They are going to have two devices, one smart glasses, an evolution of the Vision Pro, just focus on VR. They might actually abandon the concept of the pure VR-oriented headset. Because, from a market size perspective, it might not be big enough for Apple, quite frankly. Nuno Goncalves Pedro I read on all of the above, and people at this point was like, “Why are then players like Samsung and others not doing it. LG, et cetera?” Because those players historically have not invented new categories. They’re amazing at catching up once the category is invented, and then they scale the hell out of it, and that’s what these companies have been exceptional at. I wouldn’t see a dramatic innovation, I think, in terms of devices coming from any of the big ones on that side of the fence. Not to disrespect them in any way, but I think that’s not been their playbook ever. Again, if the origination doesn’t come from a start-up or from an Apple, I don’t see those guys going after it. My bet is that we’ll see some start-up activity and, again, hopefully, some announcement from IO now within the OpenAI world. Bertrand Schmitt I would slightly disagree with you. I see where you are coming from. But take the Samsung Galaxy Note, that sudden much bigger headphone that no one was doing that was launched by Samsung, at some point, it forced Apple to launch an iPhone Max. Let’s look at the Z Fold that Samsung launched 7 years ago, copied by everyone. Now Samsung launching a trifold. Apple has still not launched their foldable phone. I think there is a mix, actually, of sometimes- Nuno Goncalves Pedro For me, that’s not a proper new category. It’s still a mobile phone. It just happens to have a screen that folds in half. Bertrand Schmitt The iPhone was still a mobile phone, you could argue.  Nuno Goncalves Pedro No. I think the iPhone was…  I could actually agree with you on that point. Maybe Apple is not as innovative in that case. I think what Steve Jobs was exceptionally good at in terms of his ability as this master product manager was to be an exceptional curator of user flows and user experiences, and creating incredible experiences from devices based on that. That was his secret sauce. Could you say, “Wasn’t all of this stuff already around?” It was. You just put it all together very neatly and very nicely. But if you’re talking about significant shifts in how a category is done, the iPhone was a significant shift in how the category was done. The Fold is still an interesting device. I actually have a Fold right now in front of me. The 7 that you highly recommended to me that we both got, the Z Fold 7. I think they do amazing devices. I don’t think they normally are the most innovative players. Then, when they come to innovation, it comes from technology edges. Obviously, they have Samsung Display, there’s a bunch of other things. They had the ability to do foldable screens in-house themselves. Bertrand Schmitt I don’t disagree with you. I think there is an interesting situation where some companies have some strengths, another one has some strengths. My worry with Apple is that this was not demonstrated with the Vision Pro. The Vision Pro was a hot pot of technologies barely integrated together, with use cases absolutely not well-defined and certainly not something that makes sense for most of us. There is a question of has Apple lost it? While Samsung actually keeps doing their own stuff, that, yes, might be more minor improvements, but at least they are doing it. Because it looks like Apple is missing the train on even the minor improvements. By the way, you might not be aware, but Samsung launched its Vision Pro competitor. Interestingly enough, it might be a better product in some ways, being much lighter and much more comfortable. Nuno Goncalves Pedro We should play around with that and report back to our listeners. Of Start-ups and VCs Moving to venture capital and the startup ecosystem and what’s happening there, I think it is very much a bifurcated environment, and it’s bifurcated for both VCs and for startups. If you’re a startup in the AI space, and you have the hottest team since sliced bread, and you can create FOMO at the speed of light, you can raise ridiculous rounds. Five hundred million at the $3 billion, or $4 billion, or $5 billion valuation, and you still haven’t really even started. First round, you can raise 500 million. That’s back to the whole discussion on Bubble and where are we, et cetera. Some of these companies might actually become huge, some of them might not. But definitely, we are seeing really the haves and have-nots on the startup ecosystem with incredible teams raising a lot of money very, very early on or mid-stage if they’ve already existed for a while, and then the rest not being able to raise. We see a lot of non-necessarily AI sectors, some of the areas of SaaS that don’t necessarily have AI in it, or fintech, or the consumer space that are really, really struggling. If you don’t have an AI story for your startup right now, it’s extremely difficult to raise money unless your numbers are just the best numbers ever. That’s, I think, the first part of the element of bifurcation that we’re seeing today. The second element of bifurcation that we’re seeing today in terms of fundraising is for VCs themselves, and really propelled by the large VC firms raising more and more capital in recent orbits, announcing 15 billion across funds raised. Lightspeed, I think, had made an announcement a couple of weeks ago as well. They’ve raised a bunch of money as well. The big guys are all raising a lot of money. At some point in time, the question some of you might ask is, “These VCs are redeploying more and more money if they have a couple of billion for a VC fund. How does that look like? Is that still VC?” My perspective, I’ve shared before in some of our previous episodes, is that that’s no longer venture capital. At that point in time, we’re talking about something else. Private equity hedge funds, if you want to call them, maybe funds that are really driven by growth investment or late-stage investment. If you have a couple of billion under management, you’re not going to make your returns by writing a $3 million check in a series seed and leading that round.  That has implications for everyone in the ecosystem. It has implications for smaller funds that obviously have a lot more difficulty in raising capital. It’s difficult to differentiate. Last but not least, also for startups that really continue searching for that capital that is out there. Andreessen Horowitz, for example, runs Speedrun, which is a great program for companies around consumer in particular. Initially, it was a lot for gaming. But at some point in time, Andreessen Horowitz could decide that they don’t want to invest more in you. They just put money from Speedrun, which is obviously a very small check compared to the very large checks they could write mid to late stage and that will have an effect on you as a startup. What happens at that point in time if Andreessen Horowitz is not backing you up in later stages? More than that, what happens if I can’t get these big funds interested in me? Are the small funds still valuable to me? Punchline, my view is yes. Obviously, we’re a smaller fund, so there’s parochial interest in what I’m saying. Small funds can still create a ton of value for you, also in terms of credibility, ability to accompany you in those first stages of investment, and the ability to bring other larger investors later down the road as well. There’s definitely a big movement happening in terms of the fundraising for VC funds, which we shouldn’t neglect, which is the big guys are raising a lot more capital and are therefore emptying the market to smaller funds that are having more and more difficult raising at this point in time. We had discussed that there would be a need for concentration in the industry, that micro funds would need to concentrate, and we didn’t have the space for so many micro funds as we had around. But the way it’s happening is extremely dramatic at this moment in time. I think it will continue through 2026. Bertrand Schmitt Remember a few years ago, with the rise of AI, there was more and more of the question about, “What’s the point of SaaS at this stage?” Because SaaS was around for 15 years. Basically, how do you come up with something new that was not already tested, validated by the market? How do you bring something new? We say this was reinforced to the power of 10. If your product is not clearly built from the ground up for a new use case enabled by AI, anyone could then might have built your product 5, 10 years ago, and therefore, why now has no clear answer, and it’s a big problem. I’m still surprised myself to still see some entrepreneurs where you talk to them about AI because you don’t see them in the deck, and they explain to you, “It’s not yet there,” and you’re like, “What’s wrong with you guys?” Fine. Do whatever you want. Do a small business and whatever, but don’t think you can come up pitch and raise without an AI story. The second category is people who come with an AI story, but you can feel very quickly, I guess you saw that many times, Nuno, where just a story layered on top with little credibility. It’s not better. It’s not enough to just have a story. Your business needs to be radically built differently or radically proposing some brand-new use cases that were impossible to solve 5 years ago. Nuno Goncalves Pedro To stack up on that, absolutely in agreement. If you’re just adding to the story, and it’s an afterthought, and you’re just trying to make the story somehow gel, once you go into one or two layers of due diligence, your investors will very quickly realise that you’re not really AI-first or dramatically AI-enabled or whatever. It’s just you’re sort of stacking something on top of another thesis. It needs to make sense from the product onwards. It’s not just, let’s just put it together with chewing gum, and magically, people will give you money. It was true also if we remember the good old crypto blockchain days, where everyone’s investing in crypto. A lot of stories that didn’t make much sense. In that sense, it’s not very different. I would go one step further. I think in the world of the VC winter that we’re a little bit in, where it’s more and more difficult if you’re a smaller fund to raise your fund at this moment in time, there’s a lot of sources of distinctiveness still talked about, like proprietary networks, access to deal flow, fast track record, all that stuff that really, really matters. But our bet continues at Chamaeleon continues being that you need to be AI-first as a VC fund yourself. You need to have core advantages in using not only readily-available AI tools or third-party available AI tools, data sources, technology stacks, but actually building your own stack over time, which is what we did with Mantis at Chamaeleon. Again, just to reinforce that, I think we’re at the beginning of that stage. We, Chamaeleon, are ahead of the game, but we think that the rest of the market will have to move towards that as well. Still, to be honest, very surprising to me to see that many significant large players are doing very little still around some of these spaces. They have data scientists. They’re running some tools. They’re running some analysis and all that stuff, but it’s still, again, back to the point I was making for startups, all glued up with chewing gum. It doesn’t all come together nicely, which it does need to from a platform standpoint. Bertrand Schmitt It’s quite surprising. I agree with you that some VC funds might think that they can do business as usual in that brand-new world. It’s difficult to believe. Nuno Goncalves Pedro Maybe moving a little bit toward the capital formation piece. We already discussed the M&A space really accelerating. We’ve also discussed the IPO market and some predictions on that. Secondaries, there’s obviously a lot of liquidity coming from secondaries from mid to late stage. I think it will continue throughout the rest of 2026. A lot of activity in buying, selling in secondaries as some asset managers are becoming more distressed, as some very high net worth individuals and family offices are becoming more distressed as well, at the same time, where there’s a lot of opportunities to potentially arbitrage around some investments. I believe a lot of money will be made and lost this year by decisions made this year, just to be very, very clear in terms of equity, purchases, et cetera. Exciting year ahead of us. Definitely a very, very interesting market ahead of us. Secondaries, M&A, growth, and late-stage investing, also, early-stage investing will continue just for those that were wondering. Last but not least, the public markets, the IPO market as well. Bertrand Schmitt One of the big questions for the IPO market would be, will SpaceX go public? Would it be good for the startup ecosystem? Because suddenly that they go public, it would be to raise money. If they raise money, will there be any money left for anybody else? That would be an interesting test of the market. For sure, it would be proof that market are risk on financing a new IPO like this one. Or as you said, maybe there is no IPO, and it’s a merger with Tesla. Time will tell. Nuno Goncalves Pedro Regulatory & Geopolitical Headwinds… and the Wars Moving maybe to our topic of regulation and geopolitical headwinds, as we’re seeing … definitely not tailwinds. The Google antitrust verdict and, obviously, the remedies are expected to come forward now, and a lot of people are saying, “There are some risks of structural separation.” What do you think? Is it cool, but nothing will happen in the end dramatically? Alphabet or Google? I’m not sure, actually. It’s Google LLC. I think that’s the case. It’s The United States versus Google LLC. Bertrand Schmitt I’m not sure. Personally, I’m not a big fan. I think there needs to be a better way to manage some anticompetitive behavior. I’m not a big fan. There was this temptation to do that for Microsoft 25 years ago. Look at what happened. No one needed to buy Microsoft to leave space for others. I see the same with Google, and I guess they are happy to not be the number 1 in AI today, but to have an open AI in front of them. Even if they are doing a great job, by the way, to move forward and go faster and faster. Personally, quite impressed now with some of what they have released. Gemini 3 is doing great from my perspective. I’m not a big fan of this. I think to be clear, it’s important that bigger companies don’t behave anticompetitively, but at the same time, we need to find the right approach where it’s not about breaking these companies, and it’s also not about forbidding them to do acquisitions. Because then you end up with what NVIDIA just did with a $20 billion acquihire IP licensing type of acquisition, because they didn’t want to have the uncertainties. They didn’t want to wait 1–2 years in order to acquire the people and the technology, so they organised it in a different way. But I don’t like that. I think they should be able to acquire companies without facing so much uncertainty. To be clear, it’s not new. Uncertainty when you are Google, NVIDIA, or others, it happens. It has happened for a decade plus, 2 decades. I think there needs to be, for sure, some safety valves. At the same time, we want an efficient capital market. An efficient capital market need companies that can acquire other companies. If you don’t do that efficiently, it will be worse for the entrepreneurs, it will be worse for the investors, it will be worse for everybody. I think we have not reached a good equilibrium from my perspective. We need more efficient acquisition process. And at the same time, we need to also enforce faster anticompetitive behavior. Because what you talk about concerning Google, this is a case that was what? That is 10 years old. You see what I mean? This is way too long. If you’re a startup, you are dead by then. It’s like the story of Netscape facing Microsoft. They were dead long after the fact. I think we need a different approach. I’m not sure the best answer. I’m not sure we’ll get a better approach. There are probably too many vested interest. My hope is that it will get better with this current administration because, certainly, the past administration was very anti acquisition and efficient markets. Nuno Goncalves Pedro We’ve talked about the European Union AI Act a bunch of times, so I don’t want to spend too many cycles on that. The only effect that I would say is we are seeing in very slow motion the splitting of the Internet. I once had Tim Berners-Lee, by the way, shouting at me that we were going to break the Internet when we were applying for the .mobi top-level domain. I was part of that consortium that eventually did get the .mobi top-level domain, and I had him shouting at us. But, apparently, this is going to split the Internet, Tim. So in case you’re listening. Because it will create all these different rules. If your data is relating to consumers there, then it’s treated in a different way, and The US is… Well, obviously, we have the case of California with its own rules and laws. I don’t know. I feel we’re having a moment of siloing that goes beyond economic and geopolitical siloing. It will also apply to the digital world, and we’ll start having different landscapes around it. We’ll see how this affects global expansion of services, for example, around AI, particularly for consumer, but I don’t foresee anything dramatically positive. Recently, we had the whole deal around TikTok finally having a solution for their US problem where there’s now a US conglomerate magically that owns it. The conglomerate doesn’t magically own it, they just straight up own it for the US. But it was driven by many of these concerns around data ownership. Where’s the data? Where is it based? I think a lot of other concerns that have to do with the geopolitics of China, obviously, being the basis of ByteDance, the owner of TikTok, that still is a significant owner, by the way, in TikTok in US. Then also the interest in the economics of making money out of something as powerful as TikTok, to be honest, in The US. Just to be clear, I don’t think this was all about the best interests of consumers. It was also about money. Just follow the money. Bertrand Schmitt There are for sure, some powerful interest at play. But let’s be clear. I think one is data, as you rightfully said, but the other one is algorithm. It’s not as if China is authorising any competitor on its territory. They have blocked access to most of the Internet platforms from the US, either finding new rules or just trade blocking them. So I don’t think it’s fair competition. You don’t want some of that data in China about the US or European consumer. Three, it’s about the algorithm. If suddenly, you are a foreign power, and you can as we know in China, you better follow what’s required of you from the Chinese Communist Party. You cannot take a chance with influencing other stuff like elections in other countries. It’s fair from the US perspective. One could even argue it’s fair from a Chinese perspective to want that. I think the only one in the middle who doesn’t really know what they want is Europe because on one side, they want to benefit from American platforms, on the other end, they want to have some controls. On the other end, they don’t create the environment for startups to flourish. So in that weird situation where they have to accept some control by the big US providers and either provider of underlying infrastructure or provider of consumer business facing services. Then they try to regulate them. But I think they are misunderstanding the power relationship, and I think some of this regulation would get some blowback, at least by the current administration. Just, I believe, this morning, there was some news around X being under a criminal investigation in France. This is not going to end well for the French startup and VC ecosystem. This is not going to end well for France and Europe when you depend so much from your American friends. Nuno Goncalves Pedro Regulation will be weaponised. Regulation constraints around exports, all of this will be weaponised geopolitically, and the bigger guys will normally win. I think that’s normally what we’ve seen. Just on TikTok just to… And you guys, if you’re listening to us, just see if you see a pattern here, but obviously, 19.9% still owned by ByteDance of the TikTok entity in the US. It was initially said that 80% of the TikTok entity is owned by non-Chinese investors. Initially, people were saying US investors, and then they changed it to non-Chinese because MGX, I think, has 15% of it. MGX is based in the UAE, connected obviously to Mubadala, the Abu Dhabi sovereign wealth fund. Silver Lake is in there, I think, with 15% as well. Oracle as well with 15%. Those three are the big bucket owners together, 45%. Silver Lake having collaborated with MGX before, and I’m sure a lot of connectivity there. Then you still see a pattern in this in terms of shareholders. If you don’t, then just Google it. Dell Family Office, Vastmir Strategic Investments, which is owned by billionaire Jeff Yass, Alpha Wave Partners, obviously involved with a bunch of things like SpaceX and Klarna, Virgoli, Revolution, which is Steve Case’s, a former founder of AOL, is also in there. Meritway, which is managed by partners, I think, of Dragonair. Vinova from General Atlantic, an affiliate of General Atlantic. Also, NJJ Capital, which I believe is Xavier Nil, the French billionaire that founded Iliad. Mostly American, I think, if the math is correct. 80% non-Chinese, which was what mattered, I think, in many cases. But do see if you saw a pattern in most of those investors. I won’t say anything more than that. Maybe moving to other topics, maybe just to finalise on regulation and geopolitics. In geopolitics, we should talk about wars if we predict anything. Not that we are nasty and one want to be negative, but what the hell is going on? Will we have ending to the wars we already have ongoing or not? But before that, the struggles on the App Stores, I think, will continue both for Apple and for Google Play Store. The writing’s on the wall, the EU keeps pushing it dramatically and Apple keeps just doing stuff. I’m on the board of an App Store company. Apple just creates all these things that basically make you not really… It doesn’t work. You can’t provision then an App Store on Apple devices. On iPhones, et cetera. We’ll see how that will continue going, but I feel the writing’s on the wall. Both Apple and Google will have to open up a bit more of their platforms. I’m not sure it will have a huge impact in the medium to long term, but definitely we need to see more openness in access to apps as given by the two big platform owners, Apple and Google, out there. Bertrand Schmitt Let’s be clear. Google is way more open than Apple. We both have Android devices. You can install alternative app stores. It’s a different ballgame by very far. Nuno Goncalves Pedro Google does other nasty stuff. It’s public. You can check which board I’m a part of. You can see what that company has done towards Google over time. But to your point, yes. It is true that Google has been more open than Apple, but Google has done their own things. Just to be very clear, so I’ll just leave that caveat bracketed there for people to think about it and maybe read a little bit about it as well. Bertrand Schmitt I can say that, me, from my perspective, that path of total control that Apple has been going through on all their devices, that includes macOS, pushed me to, over the past 2, 3 years, to completely live and abandon the Apple ecosystem. I just couldn’t accept that level of control, that golden handcuff approach of the Apple ecosystem, each their own obviously, they are golden, their handcuffs, but they are still handcuffs. Personally, that pushed me way more to Linux, Android, Windows, back to Windows after all these years. I just couldn’t stand it anymore. I want to pick my devices. I want to pick what I install on them, and I don’t want to be controlled like this by just one entity for all my tech devices. For me, at some point, it was just not acceptable anymore. It’s still very warm, very golden handcuffs, but for me, they were just handcuffs at this stage. Yes, what they are doing with the App Store is very typical of that mindset. I think it’s quite sad because I think it started with good intention in some ways. “We need a new computing paradigm, we need to make things smoother and safer,” but it has really become a way to control your clients. For me, it has reached a point where it’s just way too much. Nuno Goncalves Pedro There’s obviously the great power comes great responsibility that uncle Ben told Spider-Man or Peter Parker. But there’s also with great power comes shitload of money, and control. So it’s like, “Yeah. Should we open the server? Do we want to delay opening it up?” “Yeah.” Anyway, it is what it is. Maybe let’s end on the more difficult note of the episode, which is going to be around wars. What’s our prediction? Will we have an end to the Gaza situation with Israel? Will we have an end to Ukraine and, obviously, Russia? What will happen in Iran? Those are the three big, big conflicts right now. Then, obviously, if we want to add just bonus points, what’s going to happen to Greenland, and what’s going to happen to Taiwan, and what’s going to happen to Venezuela? Let’s throw the whole basket in there. We’ve never had like… Let’s talk about all these territories and all these countries. At some point in time, I’m saying this in a light manner, but it’s obviously more tragic than it should be light, and people are dying, and there’s a lot of implications of all of that that is happening right now. Do you have any predictions, Bertrand, for this year? Bertrand Schmitt No. It’s tough to predict on an individual basis. I think on a more bigger picture basis is on one side, obviously, the rise of China on one side. You have also the rise of other countries like India, while very indirectly connected to some of these conflicts are still part of the game, buying oil from Russia, for instance. At the same time, I think overall, the US is more clear about with the sheriff in town. I think it’s good because in some ways, you cannot pay for the goods, you cannot have such a massive advantage versus nearly every other country on earth and just not be clear about who is the boss in some ways. As a result, what are the rules of the game and how it should be played? The US is not alone, obviously, you have China, you have Russia, you have India, you have Europe. You have different other countries. But at some point, it’s not good when countries are not rational and are not clear. I think I prefer the current situation where things are more clear and where you have to assume responsibilities about what you are doing. It’s time to be rational again about how the world behave. Yes, the concept of power and balance of power. I think there has been that dream, maybe mostly coming from Europe, about the end of history. I think that’s simply not the case. It’s not the end of history. It’s still about the balance of power. It has always been about the balance of power. If you are dumb enough to think it was not about that anymore, I just have a bridge to nowhere to sell you. I don’t have specific prediction, but I think it’s clear there is a new sheriff in town. There is a new doctrine about the Western Hemisphere that has been in some ways resurrected on the [inaudible 00:51:35] train, and I think we’ll see more of it. I think at this point, the biggest question is for the Europeans. What do they want to do? Because right now, their position of being a dwarf militarily while being a pretty big giant economically, I don’t think it works. Nuno Goncalves Pedro I agreed on everything that you said. I do have predictions. I’ll stick a flag on the ground just with my predictions. Bertrand Schmitt Good luck. Nuno Goncalves Pedro They are mostly positive. I do think we’ll see an end or, for the most, end to the two big conflicts, the one in Gaza and the one in Ukraine. I think Ukraine will end up in readjustment of territory and splitting between Russia and the Ukraine, but the end of hostilities, I think that we will see an end to the conflict in Gaza also with a readjustment on what that will mean for the Palestinian territories and the Palestinians in general. That I’m not sure, but I feel that there will be an end to those two big conflicts. Iran, I have no clue. I will not put a stick on the ground that I have no clue. There are so many things that could go wrong there. I’ve been reading some really interesting thoughts about even some aggressive thoughts that this might be the time to really change regimes in Iran and for the US to have a bit more of an aggressive stance. I really don’t have a perspective. Obviously, there’s a lot at stake there. Then, if we talk about the other parts, Greenland, I will not opine too much on. Maybe we’re done for now. Maybe there’ll be some other concessions to the US that weren’t already there in the ’50s. Taiwan, I won’t bet either. I’m sad to say I think it might happen at some point in time, but I’m not sure when and what would drive it. Last but not the least, Venezuela is my only really negative prediction. I feel it will continue to be a significant dictatorship as it was before managed enough by other people with the difference now that it has a tax to be paid to the US in the form of oil of some sort, etcetera, and maybe gas, maybe other things as well that it didn’t have before. That’s probably my most negative prediction for the coming year on the geopolitical side. Bertrand Schmitt Without going into detail, I would mostly agree with what you shared. At least that makes sense. But as we know, it’s not always what makes sense, but what might happen. I can tell you 100% I would not have guessed this operation against Maduro. This was so well done, well executed, and shocking at the same time that it’s… I think it shows that it’s hard to guess some of this stuff because there are certainly some new ways to wage limited war, for instance. So it’s certainly interesting, and we certainly need to get used to pretty bombastic statements. But for Venezuela, I don’t think it can be worse than what it was before. I’m probably more optimistic that gradually it can get better. Nuno Goncalves Pedro Just to put perspective on why we’re not making predictions on some of these elements, I think this is a funny story, but I was in Madeira. Actually, first time I was in Madeira, although I’m originally from Portugal. I’ve never been to the islands. Obviously, as you guys know, or some of you might know, there’s a lot of connection between Madeira and Venezuela. There’s a lot of immigration from Madeira Islands to Venezuela. One of my Uber or Bolt drivers there in Madeira was Venezuelan. Was born in Venezuela, but Portuguese descent, et cetera. He was telling me this was still last year. Late last year. Because I told him I lived in US, et cetera, and he was like, “Oh, hopefully, Trump will get Maduro out of there.” In my mind, I was like, “Dude.” No disrespect to the gentleman, but it’s like, “Okay. Mike, your perspective on geopolitics is maybe a little bit exaggerated.” And a couple of days later, we know what happened. When geopolitical decisions are better predicted by some probably very astute Uber drivers, you’re like, “Maybe I shouldn’t make a bet. I have no clue what’s going to happen, no clue what’s going to happen in Greenland, et cetera.” Anyway, a couple of predictions on that element. Bertrand Schmitt That’s why it’s so right. You have to be careful with the prediction, but it doesn’t remove the fact that I think nations and companies that have to play a global game have to understand in some ways what is the game, what are the powers in place, what could happen potentially, but also be realistic. Not be about wish and dreams, but more about, what’s the power relationship? Who has the money? Who has the means? Who has the capacity to do this or that? Because if you start that way, at least the scope of what’s possible, what’s reasonable is more and more clear more quickly. Some stuff like happened with Maduro, I would never have predicted, but for sure, if there’s one country that can do this sort of stuff, it’s the US. I’m not sure anyone has a technology and the means in terms of support infrastructure to do something like this. It’s tough to predict what will happen a year from now for any specific country, but I think that even trying to get a better understanding about the forces in play and their capacity and understanding and accepting that at some point, it’s all about real politic and relationship of power, the more your eyes would be wide open about what’s possible versus simple, wishful thinking. Nuno Goncalves Pedro Fintech, Crypto and Frontier Tech Moving maybe to our last section around fintech, crypto, and frontier tech. For me, just two very quick predictions, views of the world. I think on the frontier tech side, I won’t make a prediction. I will just tell you all to go and listen to our episodes, the one on infrastructure, which is immediately prior to this one, and the episodes that we’ve had around a couple of other topics including AI, what’s the future of your children, because I think they illustrate a lot of the points that we’re seeing and manifesting themselves over the next year and over the next 2 or 3 years as well beyond that. I feel those tomes are complete in and out of themselves, so you can just go and listen to them. Then my second comment is on crypto. I feel crypto has become of the essence, particularly under the current administration in the US, very favored. Obviously, we are now in a world where crypto is just part of the economic system, and I think we’ll see more and more of that emerging, and in some ways, crypto is becoming mainstream. Question is what blockchains will be the blockchains of the future? Obviously, there’s a bunch of bets put out there. We, ourselves, as Chamaeleon, have one investment in one of the significant bets in the space. But besides that, who’s going to win or not, we feel that we’re past the crypto winter. It’s now mainstream days, and we’ll see a lot more activity in there. Bertrand Schmitt I must say with crypto, I’m a bit confused. As you say, we are past the crypto winter. There is much less uncertainty in regul

In this episode, Nathan Wrigley talks with Ben Pines about founder-led marketing, particularly in the WordPress and SaaS spaces. Ben explains how traditional marketing tactics like SEO and paid ads are less effective due to AI-generated content, and advocates for a personal, trust-building approach where founders consistently share authentic insights. He describes how he helps founders develop a marketing system with minimal time commitment, just 1-2 hours a week, focused on genuine business sense and value, not just features. The discussion also touches on the importance of making marketing feel human and credible. Go listen...

The reception to our recent post on Code Reviews has been strong. Catch up!Amid a maelstrom of discussion on whether or not AI is killing SaaS, one of the top publicly listed SaaS companies in the world has just reported record revenues, clearing well over $1.1B in ARR for the first time with a 28% margin. As we comment on the pod, Aaron Levie is the rare public company CEO equally at home in both worlds of Silicon Valley and Wall Street/Main Street, by day helping 70% of the Fortune 500 with their Enterprise Advanced Suite, and yet by night is often found in the basements of early startups and tweeting viral insights about the future of agents.Now that both Cursor, Cloudflare, Perplexity, Anthropic and more have made Filesystems and Sandboxes and various forms of “Just Give the Agent a Box” cool (not just cool; it is now one of the single hottest areas in AI infrastructure growing 100% MoM), we find it a delightfully appropriate time to do the episode with the OG CEO who has been giving humans and computers Boxes since he was a college dropout pitching VCs at a Michael Arrington house party.Enjoy our special pod, with fan favorite returning guest/guest cohost Jeff Huber!Note: We didn't directly discuss the AI vs SaaS debate - Aaron has done many, many, many other podcasts on that, and you should read his definitive essay on it. Most commentators do not understand SaaS businesses because they have never scaled one themselves, and deeply reflected on what the true value proposition of SaaS is.We also discuss Your Company is a Filesystem:We also shoutout CTO Ben Kus' and the AI team, who talked about the technical architecture and will return for AIE WF 2026.Full Video EpisodeTimestamps* 00:00 Adapting Work for Agents* 01:29 Why Every Agent Needs a Box* 04:38 Agent Governance and Identity* 11:28 Why Coding Agents Took Off First* 21:42 Context Engineering and Search Limits* 31:29 Inside Agent Evals* 33:23 Industries and Datasets* 35:22 Building the Agent Team* 38:50 Read Write Agent Workflows* 41:54 Docs Graphs and Founder Mode* 55:38 Token FOMO Culture* 56:31 Production Function Secrets* 01:01:08 Film Roots to Box* 01:03:38 AI Future of Movies* 01:06:47 Media DevRel and EngineeringTranscriptAdapting Work for AgentsAaron Levie: Like you don't write code, you talk to an agent and it goes and does it for you, and you may be at best review it. That's even probably like, like largely not even what you're doing. What's happening is we are changing our work to make the agents effective. In that model, the agent didn't really adapt to how we work.We basically adapted to how the agent works. All of the economy has to go through that exact same evolution. Right now, it's a huge asset and an advantage for the teams that do it early and that are kinda wired into doing this ‘cause you'll see compounding returns. But that's just gonna take a while for most companies to actually go and get this deployed.swyx: Welcome to the Lane Space Pod. We're back in the chroma studio with uh, chroma, CEO, Jeff Hoover. Welcome returning guest now guest host.Aaron Levie: It's a pleasure. Wow. How'd you get upgraded to, uh, to that?swyx: Because he's like the perfect guy to be guest those for you.Aaron Levie: That makes sense actually, for We love context. We, we both really love context le we really do.We really do.swyx: Uh, and we're here with, uh, Aaron Levy. Welcome.Aaron Levie: Thank you. Good to, uh, good to be [00:01:00] here.swyx: Uh, yeah. So we've all met offline and like chatted a little bit, but like, it's always nice to get these things in person and conversation. Yeah. You just started off with so much energy. You're, you're super excited about agents.I loveAaron Levie: agents.swyx: Yeah. Open claw. Just got by, got bought by OpenAI. No, not bought, but you know, you know what I mean?Aaron Levie: Some, some, you know, acquihire. Executiveswyx: hire.Aaron Levie: Executive hire. Okay. Executive hire. Say,swyx: hey, that's my term. Okay. Um, what are you pounding the table on on agents? You have so many insightful tweets.Why Every Agent Needs a BoxAaron Levie: Well, the thing that, that we get super excited by that I think is probably, you know, should be relatively obvious is we've, we've built a platform to help enterprises manage their files and their, their corporate files and the permissions of who has access to those files and the sharing collaboration of those files.All of those files contain really, really important information for the enterprise. It might have your contracts, it might have your research materials, it might have marketing information, it might have your memos. All that data obviously has, you know, predominantly been used by humans. [00:02:00] But there's been one really interesting problem, which is that, you know, humans only really work with their files during an active engagement with them, and they kind of go away and you don't really see them for a long time.And all of a sudden, uh, with the power of AI and AI agents, all of that data becomes extremely relevant as this ongoing source of, of answers to new questions of data that will transform into, into something else that, that produces value in your organization. It, it contains the answer to the new employee that's onboarding, that needs to ramp up on a project.Um, it contains the answer to the right thing to sell a customer when you're having a conversation to them, with them contains the roadmap information that's gonna produce the next feature. So all that data. That previously we've been just sort of storing and, and you know, occasionally forgetting about, ‘cause we're only working on the new active stuff.All of that information becomes valuable to the enterprise and it's gonna become extremely valuable to end users because now they can have agents go find what they're looking for and produce new, new [00:03:00] value and new data on that information. And it's gonna become incredibly valuable to agents because agents can roam around and do a bunch of work and they're gonna need access to that data as well.And um, and you know, sometimes that will be an agent that is sort of working on behalf of, of, of you and, and effectively as you as and, and they are kind of accessing all of the same information that you have access to and, and operating as you in the system. And then sometimes there's gonna be agents that are just.Effectively autonomous and kind of run on their own and, and you're gonna collaborate and work with them kind of like you did another person. Open Claw being the most recent and maybe first real sort of, you know, kind of, you know, up updating everybody's, you know, views of this landscape version of, of what that could look like, which is, okay, I have an agent.It's on its own system, it's on its own computer, it has access to its own tools. I probably don't give it access to my entire life. I probably communicate with it like I would an assistant or a colleague and then it, it sort of has this sandbox environment. So all of that has massive implications for a platform that manage that [00:04:00] enterprise data.We think it's gonna just transform how we work with all of the enterprise content that we work with, and we just have to make sure we're building the right platform to support that.swyx: The sort of shorthand I put it is as people build agents, everybody's just realizing that every agent needs a box. Yes.And it's nice to be called box and just give everyone a box.Aaron Levie: Hey, I if I, you know, if we can make that go viral, uh, like I, I think that that terminology, I, that's theswyx: tagline. Every agentAaron Levie: needs a box. Every agent needs a box. If we can make that the headline of this, I'm fine with this. And that's the billboard I wanna like Yeah, exactly.Every agent needs a box. Um, I like it. Can we ship this? Like,swyx: okay, let's do it. Yeah.Aaron Levie: Uh, my work here is done and I got the value I needed outta this podcast Drinks.swyx: Yeah.Agent Governance and IdentityAaron Levie: But, but, um, but, but, you know, so the thing that we, we kind of think about is, um, is, you know, whether you think the number 10 x or a hundred x or whatever the number is, we're gonna have some order of magnitude more agents than people.That's inevitable. It has to happen. So then the question is, what is the infrastructure that's needed to make all those agents effective in the enterprise? Make sure that they are well governed. Make sure they're only doing [00:05:00] safe things on your information. Make sure that they're not getting exposed. The data that they shouldn't have access to.There's gonna be just incredibly spectacularly crazy security incidents that will happen with agents because you'll prompt, inject an agent and sort of find your way through the CRM system and pull out data that you shouldn't have access to. Oh, weJeff Huber: have God,Aaron Levie: right? I mean, that's just gonna happen all over the place, right?So, so then the thing is, is how do you make sure you have the right security, the permissions, the access controls, the data governance. Um, we actually don't yet exactly know in many cases how we're gonna regulate some of these agents, right? If you think about an agent in financial services, does it have the exact same financial sort of, uh, requirements that a human did?Or is it, is the risk fully on the human that was interacting or created the agent? All open questions, but no matter what, there's gonna need to be a layer that manages the, the data they have access to, the workflows that they're involved in, pulling up data from multiple systems. This is the new infrastructure opportunity in the era of agents.swyx: You have a piece on agent identities, [00:06:00] which I think was today, um, which I think a lot of breaking news, the security, security people are talking about, right? Like you basically, I, I always think of this as like, well you need the human you and then there you need the agent. YouAaron Levie: Yes.swyx: And uh, well, I don't know if it's that simple, but is box going to have an opinion on that or you're just gonna be like, well we're just the sort of the, the source layer.Yeah. Let's Okta of zero handle that.Aaron Levie: I think we're gonna have an opinion and we will work with generally wherever the contours of the market end up. Um, and the reason that we're gonna have an opinion more than other topics probably is because one of the biggest use cases for why your agent might need it, an identity is for file system access.So thus we have to kind of think about this pretty deeply. And I think, uh, unless you're like in our world thinking about this particular problem all day long, it might be, you know, like, why is this such a big deal? And the reason why it's a really big deal is because sometimes sort of say, well just give the agent an, an account on the system and it just treats, treat it like every other type of user on the system.The [00:07:00] problem is, is that I as Aaron don't really have any responsibility over anybody else's box account in our organization. I can't see the box account of any other employee that I work with. I am not liable for anything that they do. And they have, I have, I have, you know, strict privacy requirements on everything that they're able to, you know, that, that, that they work on.Agents don't have that, you know, don't have those properties. The person who creates the agent probably is gonna, for the foreseeable future, take on a lot of the liability of what that agent does. That agent doesn't deserve any privacy because, because it's, you know, it can't fully be autonomously operated and it doesn't have any legal, you know, kind of, you know, responsibility.So thus you can't just be like, oh, well I'll just create a bunch of accounts and then I'll, I'll kind of work with that agent and I'll talk to it occasionally. Like you need oversight of that. And so then the question is, how do you have a world where the agent, sometimes you have oversight of, but what if that agent goes and works with other people?That person over there is collaborating with the agent on something you shouldn't have [00:08:00] access to what they're doing. So we have all of these new boundaries that we're gonna have to figure out of, of, you know, it's really, really easy. So far we've been in, in easy mode. We've hit the easy button with ai, which is the agent just is you.And when you're in quad code and you're in cursor, and you're in Codex, you're just, the agent is you. You're offing into your services. It can do everything you can do. That's the easy mode. The hard mode is agents are kind of running on their own. People check in with them occasionally, they're doing things autonomously.How do you give them access to resources in the enterprise and not dramatically increased the security risk and the risk that you might expose the wrong thing to somebody. These are all the new problems that we have to get solved. I like the identity layer and, and identity vendors as being a solution to that, but we'll, we'll need some opinions as well because so many of the use cases are these collaborative file system use cases, which is how do I give it an agent, a subset of my data?Give it its own workspace as well. ‘cause it's gonna need to store off its own information that would be relevant for it. And how do I have the right oversight into that? [00:09:00]Jeff Huber: One thing, which, um, I think is kind interesting, think about is that you know, how humans work, right? Like I may not also just like give you access to the whole file.I might like sit next to you and like scroll to this like one part of the file and just show you that like one part and like, you know,swyx: partial file access.Jeff Huber: I'm just saying I think like our, like RA does seem to be dead, right? Like you wanna say something is dead uhhuh probably RA is dead. And uh, like the auth story to me seems like incredibly unsolved and unaddressed by like the existing state of like AI vendors.ButAaron Levie: yeah, I think, um, we're, I mean you're taking obviously really to level limit that we probably need to solve for. Yeah. And we built an access control system that was, was kind of like, you know, its own little world for, for a long time. And um, and the idea was this, it's a many to many collaboration system where I can give you any part of the file system.And it's a waterfall model. So if I give you higher up in the, in the, in the system, you get everything below. And that, that kind of created immense flexibility because I can kind of point you to any layer in the, in the tree, but then you're gonna get access to everything kind of below it. And that [00:10:00] mostly is, is working in this, in this world.But you do have to manage this issue, which is how do I create an agent that has access to some of my stuff and somebody else's stuff as well. Mm-hmm. And which parts do I get to look at as the creator of the agent? And, and these are just brand new problems? Yeah. Crazy. And humans, when there was a human there that was really easy to do.Like, like if the three of us were all sharing, there'd be a Venn diagram where we'd have an overlapping set of things we've shared, but then we'd have our own ways that we shared with each other. In an agent world, somebody needs to take responsibility for what that agent has access to and what they're working on.These are like the, some of the most probably, you know, boring problems for 98% of people on, on the internet, but they will be the problems that are the difference between can you actually have autonomous agents in an enterprise contextswyx: Yeah.Aaron Levie: That are not leaking your data constantly.swyx: No. Like, I mean, you know, I run a very, very small company for my conference and like we already have data sensitivity issues.Yes. And some of my team members cannot see Yes. Uh, the others and like, I can't imagine what it's like to run a Fortune 500 and like, you have to [00:11:00] worry about this. I'm just kinda curious, like you, you talked to a lot like, like 70, 80% of your cus uh, of the Fortune 500, your customers.Aaron Levie: Yep. 67%. Just so we're being verySEswyx: precise.So Yeah. I'm notAaron Levie: Okay. Okay.swyx: Something I'm rounding up. Yes. Round up. I'm projecting to, forAaron Levie: the government.swyx: I'm projecting to the end of the year.Aaron Levie: Okay.swyx: There you go.Aaron Levie: You do make it sound like, like we, we, well we've gotta be on this. Like we're, we're taking way too long to get to 80%. Well,swyx: no, I mean, so like. How are they approaching it?Right? Because you're, you don't have a, you don't have a final answer yet.Why Coding Agents Took Off FirstAaron Levie: Well, okay, so, so this is actually, this is the stark reality that like, unfortunately is the kinda like pouring the water on the party a little bit.swyx: Yes.Aaron Levie: We all in Silicon Valley are like, have the absolute best conditions possible for AI ever.And I think we all saw the dke, you know, kind of Dario podcast and this idea of AI coding. Why is that taken off? And, and we're not yet fully seeing it everywhere else. Well, look, if you just like enumerated the list of properties that AI coding has and then compared it to other [00:12:00] knowledge work, let's just, let's just go through a few of them.Generally speaking, you bring on a new engineer, they have access to a large swath of the code base. Like, there's like very, like you, just, like new engineer comes on, they can just go and find the, the, the stuff that they, they need to work with. It's a fully text in text out. Medium. It's only, it's just gonna be text at the end of the day.So it's like really great from a, from just a, uh, you know, kinda what the agent can work with. Obviously the models are super trained on that dataset. The labs themselves have a really strong, kind of self-reinforcing positive flywheel of why they need to do, you know, agent coding deeply. So then you get just better tooling, better services.The actual developers of the AI are daily users of the, of the thing that they're we're working on versus like the, you know, probably there's only like seven Claude Cowork legal plugin users at Anthropic any given day, but there's like a couple thousand Claude code and you know, users every single day.So just like, think about which one are they getting more feedback on. All day long. So you just go through this list. You have a, you know, everybody who's a [00:13:00] developer by definition is technical so they can go install the latest thing. We're all generally online, or at least, you know, kinda the weird ones are, and we're all talking to each other, sharing best practices, like that's like already eight differences.Versus the rest of the economy. Every other part of the economy has like, like six to seven headwinds relative to that list. You go into a company, you're a banker in financial services, you have access to like a, a tiny little subset of the total data that's gonna be relevant to do your job. And you're have to start to go and talk to a bunch of people to get the right data to do your job because Sally didn't add you to that deal room, you know, folder.And that that, you know, the information is actually in a completely different organization that you now have to go in and, and sort of run into. And it's like you have this endless list of access controls and security. As, as you talked about, you have a medium, which is not, it's not just text, right? You have, you have a zoom call that, that you're getting all of the requirements from the customer.You have a lot of in-person conversations and you're doing in-person sales and like how do you ever [00:14:00] digitize all of that information? Um, you know, I think a lot of people got upset with this idea that the code base has all the context, um, that I don't know if you follow, you know, did you follow some of that conversation that that went viral?Is like, you know, it's not that simple that, that the code base doesn't have all the knowledge, but like it's a lot, you're a lot better off than you are with other areas of knowledge work. Like you, we like, we like have documentation practices, you write specifications. Those things don't exist for like 80% of work that happens in the enterprise.That's the divide that we have, which is, which is AI coding has, has just fully, you know, where we've reached escape velocity of how powerful this stuff is, and then we're gonna have to find a way to bring that same energy and momentum, but to all these other areas of knowledge work. Where the tools aren't there, the data's not set up to be there.The access controls don't make it that easy. The context engineering is an incredibly hard problem because again, you have access control challenges, you have different data formats. You have end users that are gonna need to kind of be kind of trained through this as opposed to their adopting [00:15:00] these tools in their free time.That's where the Fortune 500 is. And so we, I think, you know, have to be prepared as an industry where we are gonna be on a multi-year march to, to be able to bring agents to the enterprise for these workflows. And I think probably the, the thing that we've learned most in coding that, that the rest of the world is not yet, I think ready for, I mean, we're, they'll, they'll have to be ready for it because it's just gonna inevitably happen is I think in coding.What, what's interesting is if you think about the practice of coding today versus two years ago. It's probably the most changed workflow in maybe the history of time from the amount of time it's changed, right? Yeah. Like, like has any, has any workflow in the entire economy changed that quickly in terms of the amount of change?I just, you know, at least in any knowledge worker workflow, there's like very rarely been an event where one piece of technology and work practice has so fundamentally, you know, changed, changed what you do. Like you don't write code, you talk to an agent and it goes and [00:16:00] does it for you, and you may be at best review it.And even that's even probably like, like largely not even what you're doing. What's happening is we are changing our work to make the agents effective. In that model, the agent didn't really adapt to how we work. We basically adapted to how the agent works. Mm-hmm. All of the economy has to go through that exact same evolution.The rest of the economy is gonna have to update its workflows to make agents effective. And to give agents the context that they need and to actually figure out what kind of prompting works and to figure out how do you ensure that the agent has the right access to information to be able to execute on its work.I, you know, this is not the panacea that people were hoping for, of the agent drops in, just automates your life. Like you have to basically re-engineer your workflow to get the most out of agents and, uh, and that, that's just gonna take, you know, multiple years across the economy. Right now it's a huge asset and an advantage for the teams that do it early and that are kinda wired into doing this.‘cause [00:17:00] you'll see compounding returns, but that's just gonna take a while for most companies to actually go and get this deployed.swyx: I love, I love pushing back. I think that. That is what a lot of technology consultants love to hear this sort of thing, right? Yeah, yeah, yeah. First to, to embrace the ai. Yes. To get to the promised land, you must pay me so much money to a hundred percent to adopt the prescribed way of, uh, conforming to the agents.Yes. And I worry that you will be eclipsed by someone else who says, no, come as you are.Aaron Levie: Yeah.swyx: And we'll meet you where you are.Aaron Levie: And, and, and and what was the thing that went viral a week ago? OpenAI probably, uh, is hiring F Dees. Yeah. Uh, to go into the enterprise. Yeah. Yeah. And then philanthropic is embedded at Goldman Sachs.Yeah. So if the labs are having to do this, if, if the labs have decided that they need to hire FDE and professional services, then I think that's a pretty clear indication that this, there's no easy mode of workflow transformation. Yeah. Yeah. So, so to your point, I think actually this is a market opportunity for, you know, new professional services and consulting [00:18:00] firms that are like Agent Build and they, and they kind of, you know, go into organizations and they figure out how to re-engineer your workflows to make them more agent ready and get your data into the right format and, you know, reconstruct your business process.So you're, you're not doing most of the work. You're telling agents how to do the work and then you're reviewing it. But I haven't seen the thing that can just drop in and, and kinda let you not go through those changes.swyx: I don't know how that kind of sales pitch goes over. Yeah. You know, you're, you're saying things like, well, in my sort of nice beautiful walled garden, here's, there's, uh, because here's this, here's this beautiful box account that has everything.Yes. And I'm like, well, most, most real life is extremely messy. Sure. And like, poorly named and there duplicate this outdated s**tAaron Levie: a hundred percent. And so No, no, a hundred percent. And so this is actually No. So, so this is, I mean, we agree that, that getting to the beautiful garden is gonna be tough.swyx: Yeah.Aaron Levie: There's also the other end of the spectrum where I, I just like, it's a technical impossibility to solve. The agent is, is truly cannot get enough context to make the right decision in, in the, in the incredibly messy land. Like there's [00:19:00] no a GI that will solve that. So, so we're gonna have to kind of land in somewhere in between, which is like we all collectively get better at.Documentation practices and, and having authoritative relatively up-to-date information and putting it in the right place like agents will, will certainly cause us to be much better organized around how we work with our information, simply because the severity of the agent pulling the wrong data will be too high and the productivity gain of that you'll miss out on by not doing this will be too high as well, that you, that your competition will just do it and they'll just have higher velocity.So, uh, and, and we, we see this a lot firsthand. So we, we build a series of agents internally that they can kind of have access to your full box account and go off and you give it a task and it can go find whatever information you're looking for and work with. And, you know, thank God for the model progress, but like, if, if you gave that task to an agent.Nine months ago, you're just gonna get lots of bogus answers because it's gonna, it's gonna say, Hey, here's, here are fi [00:20:00] five, you know, documents that all kind of smell like the right thing. And I'm gonna, but I, but you're, you're putting me on the clock. ‘cause my assistant prompt says like, you know, be pretty smart, but also try and respond to the user and it's gonna respond.And it's like, ah, it got the wrong document. And then you do that once or twice as a knowledge worker and you're just neverswyx: again,Aaron Levie: never again. You're just like done with the system.swyx: Yeah. It doesn't work.Aaron Levie: It doesn't work. And so, you know, Opus four six and Gemini three one Pro and you know, whatever the latest five 3G BT will be, like, those things are getting better and better and it's using better judgment.And this sort of like the, all of these updates to the agentic tool and search systems are, are, we're seeing, we're seeing very real progress where the agent. Kind of can, can almost smell some things a little bit fishy when it's getting, you know, we, we have this process where we, we have it go fan out, do a bunch of searches, pull up a bunch of data, and then it has to sort of do its own ranking of, you know, what are the right documents that, that it should be working with.And again, like, you know, the intelligence level of a model six months ago, [00:21:00] it'd be just throwing a dart at like, I'm just, I'm gonna grab these seven files and I, I pray, I hope that that's the right answer. And something like an opus first four five, and now four six is like, oh, it's like, no, that one doesn't seem right relative to this question because I'm seeing some signal that is making that, you know, that's contradicting the document where it would normally be in the tree and who should have access.Like it's doing all of that kind of work for you. But like, it still doesn't work if you just have a total wasteland of data. Like, it's just not, it's just not possible. Partly ‘cause a human wouldn't even be able to do it. So basically if a, if a really, really smart human. Could not do that task in five or 10 minutes for a search retrieval type task.Look, you know, your agent's not gonna be able to do it any better. You see this all day long. SoContext Engineering and Search Limitsswyx: this touches on a thing that just passionate about it was just context engineering. I, I'm just gonna let you ramble or riff on, on context engineering. If, if, if there's anything like he, he did really good work on context fraud, which has really taken over as like the term that people use and the referenceAaron Levie: a hundred percent.We, we all we think about is, is the context rob problem. [00:22:00]Jeff Huber: Yeah, there's certainly a lot of like ranking considerations. Gentech surgery think is incredibly promising. Um, yeah, I was trying to generate a question though. I think I have a question right now. Swyx.Aaron Levie: Yeah, no, but like, like I think there was this moment, um, you know, like, I don't know, two years ago before, before we knew like where the, the gotchas were gonna be in ai and I think someone was like, was like, well, infinite context windows will just solve all of these problems and ‘cause you'll just, you'll just give the context window like all the data and.It's just like, okay, I mean, maybe in 2035, like this is a viable solution. First of all, it, it would just, it would just simply cost too much. Like we just can't give the model like the 5,000 documents that might be relevant and it's gonna read them all. And I've seen enough to, to start believing in crazy stuff.So like, I'm willing to just say, sure. Like in, in 10 years from now,swyx: never say, never, never.Aaron Levie: In, in 10 years from now, we'll have infinite context windows at, at a thousandth of the price of today. Like, let's just like believe that that's possible, but Right. We're in reality today. So today we have a context engineering [00:23:00] problem, which is, I got, I got, you know, 200,000 tokens that I can work with, or prob, I don't even know what the latest graph is before, like massive degradation.16. Okay. I have 60,000 tokens that I get to work with where I'm gonna get accurate information. That's not a lot of tokens for a corpus of 10 million documents that a knowledge worker might have across all of the teams and all the projects and all the people they work with. I have, I have 10 million documents.Which, you know, maybe is times five pages per document or something like that. I'm at 50 million pages of information and I have 60,000 tokens. Like, holy s**t. Yeah. This is like, how do I bridge the 50 million pages of information with, you know, the couple hundred that I get to work with in that, in that token window.Yeah. This is like, this is like such an interesting problem and that's why actually so much work is actually like, just like search systems and the databases and that layer has to just get so locked in, but models getting better and importantly [00:24:00] knowing when they've done a search, they found the wrong thing, they go back, they check their work, they, they find a way to balance sort of appeasing the user versus double checking.We have this one, we have this one test case where we ask the agent to go find. 10 pieces of information.swyx: Is this the complex work eval?Aaron Levie: Uh, this is actually not in the eval. This is, this is sort of just like we have a bunch of different, we have a bunch of internal benchmark kind of scenarios. Every time we, we update our agent, we have one, which is, I ask it to find all of our office addresses, and I give it the list of 10 offices that we have.And there's not one document that has this, maybe there should be, that would be a great example of the kind of thing that like maybe over time companies start to, you know, have these sort of like, what are the canonical, you know, kind of key areas of knowledge that we need to have. We don't seem to have this one document that says, here are all of our offices.We have a bunch of documents that have like, here's the New York office and whatever. So you task this agent and you, you get, you say, I need the addresses for these 10 offices. Okay. And by the way, if you do this on any, you know, [00:25:00] public chat model, the same outcome is gonna happen. But for a different kind of query, you give it, you say, I need these 10 addresses.How many times should the agent go and do its search before it decides whether or not, there's just no answer to this question. Often, and especially the, the, let's say lower tier models, it'll come back and it'll give you six of the 10 addresses. And it'll, and I'll just say I couldn't find the otherswyx: four.It, it doesn't know what It doesn't know. ItAaron Levie: doesn't know what It doesn't know. Yeah. So the model is just like, like when should it stop? When should it stop doing? Like should it, should it do that task for literally an hour and just keep cranking through? Maybe I actually made up an office location and it doesn't know that I made it up and I didn't even know that I made it up.Like, should it just keep, re should it read every single file in your entire box account until it, until it should exhaust every single piece of information.swyx: Expensive.Aaron Levie: These are the new problems that we have. So, you know, something like, let's say a new opus model is sort of like, okay, I'm gonna try these types of queries.I didn't get exactly what I wanted. I'm gonna try again. I'm gonna, at [00:26:00] some point I'm gonna stop searching. ‘cause I've determined that that no amount of searching is gonna solve this problem. I'm just not able to do it. And that judgment is like a really new thing that the model needs to be able to have.It's like, when should it give up on a task? ‘cause, ‘cause you just don't, it's a can't find the thing. That's the real world of knowledge, work problems. And this is the stuff that the coding agents don't have to deal with. Because they, it just doesn't like, like you're not usually asking it about, you're, you're always creating net new information coming right outta the model for the most part.Obviously it has to know about your code base and your specs and your documentation, but, but when you deploy an agent on all of your data that now you have all of these new problems that you're dealing withJeff Huber: our, uh, follow follow-up research to context ride is actually on a genetic search. Ah. Um, and we've like right, sort of stress tested like frontier models and their ability to search.Um, and they're not actually that good at searching. Right. Uh, so you're sort of highlighting this like explore, exploit.swyx: You're just say, Debbie, Donna say everything doesn't work. Like,Aaron Levie: well,Jeff Huber: somebody has to be,Aaron Levie: um, can I just throw out one more thing? Yeah. That is different from coding and, and the rest [00:27:00] of the knowledge work that I, I failed to mention.So one other kind of key point is, is that, you know, at the end of the day. Whether you believe we're in a slop apocalypse or, or whatever. At the end of the day, if you, if you build a working product at the end of, if you, if you've built a working solution that is ultimately what the customer is paying for, like whether I have a lot of slop, a little slop or whatever, I'm sure there's lots of code bases we could go into in enterprise software companies where it's like just crazy slop that humans did over a 20 year period, but the end customer just gets this little interface.They can, they can type into it, it does its thing. Knowledge work, uh, doesn't have that property. If I have an AI model, go generate a contract and I generate a contract 20 times and, you know, all 20 times it's just 3% different and like that I, that, that kind of lop introduces all new kinds of risk for my organization that the code version of that LOP didn't, didn't introduce.These are, and so like, so how do you constrain these models to just the part that you want [00:28:00] them to work on and just do the thing that you want them to do? And, and, you know, in engineering, we don't, you can't be disbarred as an engineer, but you could be disbarred as a lawyer. Like you can do the wrong medical thing In healthcare, you, there's no, there's no equivalent to that of engineering.Like, doswyx: you want there to be, because I've considered softwareJeff Huber: engineer. What's that? Civil engineering there is, right? NotAaron Levie: software civil engineer. Sure. Oh yeah, for sure. But like in any of our companies, you like, you know, you'll be forgiven if you took down the site and, and we, we will do a rollback and you'll, you'll be in a meeting, but you have not been disbarred as an engineer.We don't, we don't change your, you know, your computer science, uh, blameJeff Huber: degree, this postmortem.Aaron Levie: Yeah, exactly. Exactly. So, so, uh, now maybe we collectively as an industry need to figure out like, what are you liable for? Not legally, but like in a, in a management sense, uh, of these agents. All sorts of interesting problems that, that, that, uh, that have to come out.But in knowledge work, that's the real hostile environments that we're operating in. Hmm.swyx: I do think like, uh, a lot of the last year's, 2025 story was the rise of coding agents and I think [00:29:00] 2026 story is definitely knowledge work agents. Yes. A hundredAaron Levie: percent.swyx: Right. Like that would, and I think open claw core work are just the beginning.Yes. Like it's, the next one's gonna just gonna be absolute craziness.Aaron Levie: It it is. And, and, uh, and it's gonna be, I mean, again, like this is gonna be this, this wave where we, we are gonna try and bring as many of the practices from coding because that, that will clearly be the forefront, which is tell an agent to go do something and has an access to a set of resources.You need to be responsible for reviewing it at the end of the process. That to me is the, is the kind of template that I just think goes across knowledge, work and odd. Cowork is a great example. Open Closet's a great example. You can kind of, sort of see what Codex could become over time. These are some, some really interesting kind of platforms that are emerging.swyx: Okay. Um, I wanted to, we touched on evals a little bit. You had, you had the report that you're gonna go bring up and then I was gonna go into like, uh, boxes, evals, but uh, go ahead. Talk about your genetic search thing.Jeff Huber: Yeah. Mostly I think kinda a few of the insights. It's like number one frontier model is not good at search.Humans have this [00:30:00] natural explore, exploit trade off where we kinda understand like when to stop doing something. Also, humans are pretty good at like forgetting actually, and like pruning their own context, whereas agents are not, and actually an agent in their kind of context history, if they knew something was bad and they even, you could see in the trace the reason you trace, Hey, that probably wasn't a good idea.If it's still in the trace, still in the context, they'll still do it again. Uhhuh. Uh, and so like, I think pruning is also gonna be like, really, it's already becoming a thing, right? But like, letting self prune the con windowsswyx: be a big deal. Yeah. So, so don't leave the mistake. Don't leave the mistake in there.Cut out the mistake but tell it that you made a mistake in the past and so it doesn't repeat it.Jeff Huber: Yeah. But like cut it out so it doesn't get like distracted by it again. ‘cause really, you know, what is so, so it will repeat its mistake just because it's been, it's inswyx: theJeff Huber: context. It'sAaron Levie: in the context so much.That's a few shot example. Even if it, yeah.Jeff Huber: It's like oh thisAaron Levie: is a great thing to go try even ifJeff Huber: it didn't work.Aaron Levie: Yeah,Jeff Huber: exactly.Aaron Levie: SoJeff Huber: there's like a bunch of stuff there. JustAaron Levie: Groundhogs Day inside these models. Yeah. I'm gonna go keep doing the same wrongJeff Huber: thing. Covering sense. I feel like, you know, some creator analogy you're trying like fit a manifold in latent space, which kind is doing break program synthesis, which is kinda one we think about we're doing right.Like, you know, certain [00:31:00] facts might be like sort of overly pitting it. There are certain, you know, sec sectors of latent space and so like plug clean space. Yeah. And, uh, andswyx: so we have a bell, our editor as a bell every time you say that. SoJeff Huber: you have, you have to like remove those, likeswyx: you shoulda a gong like TPN or something.IfJeff Huber: we gong, you either remove those links to like kinda give it the freedom, kind of do what you need to do. So, but yeah. We'll, we'll release more soon. That'sAaron Levie: awesome.Jeff Huber: That'll, that'll be cool.swyx: We're a cerebral podcast that people listen to us and, and sort of think really deep. So yeah, we try to keep it subtle.Okay. We try to keep it.Aaron Levie: Okay, fine.Inside Agent Evalsswyx: Um, you, you guys do, you guys do have EVs, you talked about your, your office thing, but, uh, you've been also promoting APEX agents and complex work. Uh, yeah, whatever you, wherever you wanna take this just Yeah. How youAaron Levie: Apex is, is obviously me, core's, uh, uh, kind of, um, agent eval.We, we supported that by sort of. Opening up some data for them around how we kind of see these, um, data workspaces in, in the, you know, kind of regular economy. So how do lawyers have a workspace? How do investment bankers have a workspace? What kind of data goes into those? And so we, [00:32:00] we partner with them on their, their apex eval.Our own, um, eval is, it's actually relatively straightforward. We have a, a set of, of documents in a, in a range of industries. We give the agent previously did this as a one shot test of just purely the model. And then we just realized we, we need to, based on where everything's going, it's just gotta be more agentic.So now it's a bit more of a test of both our harness and the model. And we have a rubric of a set of things that has to get right and we score it. Um, and you're just seeing, you know, these incredible jumps in almost every single model in its own family of, you know, opus four, um, you know, sonnet four six versus sonnet four five.swyx: Yeah. We have this up on screen.Aaron Levie: Okay, cool. So some, you're seeing it somewhere like. I, I forget the to, it was like 15 point jump, I think on the main, on the overall,swyx: yes.Aaron Levie: And it's just like, you know, these incredible leaps that, that are starting to happen. Um,swyx: and OP doesn't know any, like any, it's completely held out from op.Aaron Levie: This is not in any, there's no public data which has, you know, Ben benefits and this is just a private eval that we [00:33:00] do, and then we just happen to show it to, to the world. Hmm. So you can't, you can't train against it. And I think it's just as representative of. It's obviously reasoning capabilities, what it's doing at, at, you know, kind of test time, compute capabilities, thinking levels, all like the context rot issues.So many interesting, you know, kind of, uh, uh, capabilities that are, that are now improvingswyx: one sector that you have. That's interesting.Industries and Datasetsswyx: Uh, people are roughly familiar with healthcare and legal, but you have public sector in there.Aaron Levie: Yeah.swyx: Uh, what's that? Like, what, what, what is that?Aaron Levie: Yeah, and, and we actually test against, I dunno, maybe 10 industries.We, we end up usually just cutting a few that we think have interesting gains. All extras, won a lot of like government type documents. Um,swyx: what is that? What is it? Government type documents?Aaron Levie: Government filings. Like a taxswyx: return, likeAaron Levie: a probably not tax returns. It would be more of what would go the government be using, uh, as data.So, okay. Um, so think about research that, that type of, of, of data sets. And then we have financial services for things like data rooms and what would be in an investment prospectus. Uhhuh,swyx: that one you can dog food.Aaron Levie: Yeah, exactly. Exactly. Yes. Yes. [00:34:00] So, uh, so we, we run the models, um, in now, you know, more of an agent mode, but, but still with, with kinda limited capacity and just try and see like on a, like, for like basis, what are the improvements?And, and again, we just continue to be blown away by. How, how good these models are getting.swyx: Yeah, I mean, I think every serious AI company needs something like that where like, well, this is the work we do. Here's our company eval. Yeah. And if you don't have it, well, you're not a serious AI company.Aaron Levie: There's two dimensions, right?So there's, there's like, how are the models improving? And so which models should you either recommend a customer use, which one should you adopt? But then every single day, we're making changes to our agents. And you need to knowswyx: if you regressed,Aaron Levie: if you know. Yeah. You know, I've been fully convinced that the whole agent observability and eval space is gonna be a massive space.Um, super excited for what Braintrust is doing, excited for, you know, Lang Smith, all the things. And I think what you're going to, I mean, this is like every enter like literally every enterprise right now. It's like the AI companies are the customers of these tools. Every enterprise will have this. Yeah, you'll just [00:35:00] have to have an eval.Of all of your work and like, we'll, you'll have an eval of your RFP generation, you'll have an eval of your sales material creation. You'll have an eval of your, uh, invoice processing. And, and as you, you know, buy or use new agentic systems, you are gonna need to know like, what's the quality of your, of your pipeline.swyx: Yeah.Aaron Levie: Um, so huge, huge market with agent evals.swyx: Yeah.Building the Agent Teamswyx: And, and you know, I'm gonna shout out your, your team a bit, uh, your CTO, Ben, uh, did a great talk with us last year. Awesome. And he's gonna come back again. Oh, cool. For World's Fair.Aaron Levie: Yep.swyx: Just talk about your team, like brag a little bit. I think I, I think people take these eval numbers in pretty charts for granted, but No, there, I mean, there's, there's lots of really smart people at work during all this.Aaron Levie: Biggest shout out, uh, is we have a, we have a couple folks at Dya, uh, Sidarth, uh, that, that kind of run this. They're like a, you know, kind of tag tag team duo on our evals, Ben, our CTO, heavily involved Yasha, head of ai, uh, you know, a bunch of folks. And, um, evals is one part of the story. And then just like the full, you know, kind of AI.An agent team [00:36:00] is, uh, is a, is a pretty, you know, is core to this whole effort. So there's probably, I don't know, like maybe a few dozen people that are like the epicenter. And then you just have like layers and layers of, of kind of concentric circles of okay, then there's a search team that supports them and an infrastructure team that supports them.And it's starting to ripple through the entire company. But there's that kind of core agent team, um, that's a pretty, pretty close, uh, close knit group.swyx: The search team is separate from the infra team.Aaron Levie: I mean, we have like every, every layer of the stack we have to kind of do, except for just pure public cloud.Um, but um, you know, we, we store, I don't even know what our public numbers are in, you know, but like, you can just think about it as like a lot of data is, is stored in box. And so we have, and you have every layer of the, of the stack of, you know, how do you manage the data, the file system, the metadata system, the search system, just all of those components.And then they all are having to understand that now you've got this new customer. Which is the agent, and they've been building for two types of customers in the past. They've been building for users and they've been building for like applications. [00:37:00] And now you've got this new agent user, and it comes in with a difference of it, of property sometimes, like, hey, maybe sometimes we should do embeddings, an embedding based, you know, kind of search versus, you know, your, your typical semantic search.Like, it's just like you have to build the, the capabilities to support all of this. And we're testing stuff, throwing things away, something doesn't work and, and not relevant. It's like just, you know, total chaos. But all of those teams are supporting the agent team that is kind of coming up with its requirements of what, what do we need?swyx: Yeah. No, uh, we just came from, uh, fireside chat where you did, and you, you talked about how you're doing this. It's, it's kind of like an internal startup. Yeah. Within the broader company. The broader company's like 3000 people. Yeah. But you know, there's, there's a, this is a core team of like, well, here's the innovation center.Aaron Levie: Yeah.swyx: And like that every company kind of is run this way.Aaron Levie: Yeah. I wanna be sensitive. I don't call it the innovation center. Yeah. Only because I think everybody has to do innovation. Um, there, there's a part of the, the, the company that is, is sort of do or die for the agent wave.swyx: Yeah.Aaron Levie: And it only happens to be more of my focus simply because it's existential that [00:38:00] we get it right.swyx: Yeah.Aaron Levie: All of the supporting systems are necessary. All of the surrounding adjacent capabilities are necessary. Like the only reason we get to be a platform where you'd run an agent is because we have a security feature or a compliance feature, or a governance feature that, that some team is working on.But that's not gonna be the make or break of, of whether we get agents right. Like that already exists and we need to keep innovating there. I don't know what the right, exact precise number is, but it's not a thousand people and it's not 10 people. There's a number of people that are like the, the kind of like, you know, startup within the company that are the make or break on everything related to AI agents, you know, leveraging our platform and letting you work with your data.And that's where I spend a lot of my time, and Ben and Yosh and Diego and Teri, you know, these are just, you know, people that, that, you know, kind of across the team. Are working.swyx: Yeah. Amazing.Read Write Agent WorkflowsJeff Huber: How do you, how do you think about, I mean, you talked a lot about like kinda read workflows over your box data. Yep.Right. You know, gen search questions, queries, et cetera. But like, what about like, write or like authoring workflows?Aaron Levie: Yes. I've [00:39:00] already probably revealed too much actually now that I think about it. So, um, I've talked about whatever,Jeff Huber: whatever you can.Aaron Levie: Okay. It's just us. It's just us. Yeah. Okay. Of course, of course.So I, I guess I would just, uh, I'll make it a little bit conceptual, uh, because again, I've already, I've already said things that are not even ga but, but we've, we've kinda like danced around it publicly, so I, yeah, yeah. Okay. Just like, hopefully nobody watches this, um, episode. No.swyx: It's tidbits for the Heidi engaged to go figure out like what exactly, um, you know, is, is your sort of line of thinking.Sure. They can connect the dots.Aaron Levie: Yeah. So, so I would say that, that, uh, we, you know, as a, as a place where you have your enterprise content, there's a use case where I want to, you know, have an agent read that data and answer questions for me. And then there's a use case where I want the agent to create something.And use the file system to create something or store off data that it's working on, or be able to have, you know, various files that it's writing to about the work it's doing. So we do see it as a total read write. The harder problem has so far been the read only because, because again, you have that kind of like 10 [00:40:00] million to one ratio problem, whereas rights are a lot of, that's just gonna come from the model and, and we just like, we'll just put it in the file system and kinda use it.So it's a little bit of a technically easier problem, but the only part that's like, not necessarily technically hard, it is just like it's not yet perfected in the state of the ecosystem is, you know, building a beautiful PowerPoint presentation. It's still a hard problem for these models. Like, like we still, you know, like, like these formats are just, we're not built for.They'reswyx: working on it.Aaron Levie: They're, they're working on it. Everybody's working on it.swyx: Every launch is like, well, we do PowerPoint now.Aaron Levie: We're getting, yeah, getting a lot, getting a lot of better each time. But then you'll do this thing where you'll ask the update one slide and all of a sudden, like the fonts will be just like a little bit different, you know, on two of the slides, or it moved, you know, some shape over to the left a little bit.And again, these are the kind of things that, like in code, obviously you could really care about if you really care about, you know, how beautiful is the code, but at the end, user doesn't notice all those problems and file creation, the end user instantly sees it. You're [00:41:00] like, ah, like paragraph three, like, you literally just changed the font on me.Like it's a totally different font and like midway through the document. Mm-hmm. Those are the kind of things that you run into a lot of in the, in the content creation side. So, mm-hmm. We are gonna have native agents. That do all of those things, they'll be powered by the leading kind of models and labs.But the thing that I think is, is probably gonna be a much bigger idea over time is any agent on any system, again, using Box as a file system for its work, and in that kind of scenario, we don't necessarily care what it's putting in the file system. It could put its memory files, it could put its, you know, specification, you know, documents.It could put, you know, whatever its markdown files are, or it could, you know, generate PDFs. It's just like, it's a workspace that is, is sort of sandboxed off for its work. People can collaborate into it, it can share with other people. And, and so we, we were thinking a lot about what's the right, you know, kind of way to, to deliver that at scale.Docs Graphs and Founder Modeswyx: I wanted to come into sort of the sort of AI transformation or AI sort of, uh, operations things. [00:42:00] Um, one of the tweets that you, that you wanted to talk about, this is just me going through your tweets, by the way. Oh, okay. I mean, like, this is, you readAaron Levie: one by one,swyx: you're the, you're the easiest guest to prep for because you, you already have like, this is the, this is what I'm interested in.I'm like, okay, well, areAaron Levie: we gonna get to like, like February, January or something? Where are we in the, in the timelines? How far back are we going?swyx: Can you, can you describe boxes? A set of skills? Right? Like that, that's like, that's like one of the extremes of like, well if you, you just turn everything into a markdown file.Yeah. Then your agent can run your company. Uh, like you just have to write, find the right sequence of words toAaron Levie: Yes.swyx: To do it.Aaron Levie: Sorry, isthatswyx: the question? So I think the question is like, what if we documented everything? Yes. The way that you exactly said like,Aaron Levie: yes.swyx: Um, let's get all the Fortune five hundreds, uh, prepared for agents.Yes. And like, you know, everything's in golden and, and nicely filed away and everything. Yes. What's missing? Like, what's left, right? LikeAaron Levie: Yeah.swyx: You've, you've run your company for a decade. LikeAaron Levie: Yeah. I think the challenge is that, that that information changes a week later. And because something happened in the market for that [00:43:00] customer, or us as a company that now has to go get updated, and so these systems are living and breathing and they have to experience reality and updates to reality, which right now is probably gonna be humans, you know, kinda giving those, giving them the updates.And, you know, there is this piece about context graphs as as, uh, that kinda went very viral. Yeah. And I, I, I was like a, i, I, I thought it was super provocative. I agreed with many parts of it. I disagree with a few parts around. You know, it's not gonna be as easy as as just if we just had the agent traces, then we can finally do that work because there's just like, there's so much more other stuff that that's happening that, that we haven't been able to capture and digitize.And I think they actually represented that in the piece to be clear. But like there's just a lot of work, you know, that that has to, you just can't have only skills files, you know, for your company because it's just gonna be like, there's gonna be a lot of other stuff that happens. Yeah. Change over time.Yeah. Most companies are practically apprenticeships.swyx: Most companies are practically apprenticeships. LikeJeff Huber: every new employee who joins the team, [00:44:00] like you span one to three months. Like ramping them up.Aaron Levie: Yes. AllJeff Huber: that tat knowledgeAaron Levie: isJeff Huber: not written down.Aaron Levie: Yes.Jeff Huber: But like, it would have to be if you wanted to like give it to an Asian.Right. And so like that seems to me like to beAaron Levie: one is I think you're gonna see again a premium on companies that can document this. Mm-hmm. Much. There'll be a huge premium on that because, because you know, can you shorten that three month ramp cycle to a two week ramp cycle? That's an instant productivity gain.Can you re dramatically reduce rework in the organization because you've documented where all the stuff is and where the answers are. Can you make your average employee as good as your 90th percentile employee because you've captured the knowledge that's sort of in the heads of, of those top employees and make that available.So like you can see some very clear productivity benefits. Mm-hmm. If you had a company culture of making sure you know your information was captured, digitized, put in a format that was agent ready and then made available to agents to work with, and then you just, again, have this reality of like add a 10,000 person [00:45:00] company.Mapping that to the, you know, access structure of the company is just a hard problem. Is like, is like, yeah, well, you just, not every piece of information that's digitized can be shared to everybody. And so now you have to organize that in a way that actually works. There was a pretty good piece, um, this, this, uh, this piece called your company as a file is a file system.I, did you see that one?swyx: Nope.Aaron Levie: Uh, yes. You saw it. Yeah. And, and, uh, I actually be curious your thoughts on it. Um, like, like an interesting kind of like, we, we agree with it because, because that's how we see the world and, uh,swyx: okay. We, we have it up on screen. Oh,Aaron Levie: okay. Yeah. But, but it's all about basically like, you know, we've already, we, we, we already organized in this kind of like, you know, permission structure way.Uh, and, and these are the kind of, you know, natural ways that, that agents can now work with data. So it's kind of like this, this, you know, kind of interesting metaphor, but I do think companies will have to start to think about how they start to digitize more, more of that data. What was your take?Jeff Huber: Yeah, I mean, like the company's probably like an acid compliant file system.Aaron Levie: Uh,Jeff Huber: yeah. Which I'm guessing boxes, right? So, yeah. Yes.swyx: Yeah. [00:46:00]Jeff Huber: Which you have a great piece on, but,swyx: uh, yeah. Well, uh, I, I, my, my, my direction is a little bit like, I wanna rewind a little bit to the graph word you said that there, that's a magic trigger word for us. I always ask what's your take on knowledge graphs?Yeah. Uh, ‘cause every, especially at every data database person, I just wanna see what they think. There's been knowledge graphs, hype cycles, and you've seen it all. So.Aaron Levie: Hmm. I actually am not the expert in knowledge graphs, so, so that you might need toswyx: research, you don't need to be an expert. Yeah. I think it's just like, well, how, how seriously do people take it?Yeah. Like, is is, is there a lot of potential in the, in the HOVI?Aaron Levie: Uh, well, can I, can I, uh, understand first if it's, um, is this a loaded question in the sense of are you super pro, super con, super anti medium? Iswyx: see pro, I see pros and cons. Okay. Uh, but I, I think your opinion should be independent of mine.Aaron Levie: Yeah. No, no, totally. Yeah. I just want to see what I'm stepping into.swyx: No, I know. It's a, and it's a huge trigger word for a lot of people out Yeah. In our audience. And they're, they're trying to figure out why is that? Because whyAaron Levie: is this such aswyx: hot item for them? Because a lot of people get graph religion.And they're like, everything's a graph. Of course you have to represent it as a graph. Well, [00:47:00] how do you solve your knowledge? Um, changing over time? Well, it's a graph.Aaron Levie: Yeah.swyx: And, and I think there, there's that line of work and then there's, there's a lot of people who are like, well, you don't need it. And both are right.Aaron Levie: Yeah. And what do the people who say you don't need it, what are theyswyx: arguing for Mark down files. Oh, sure, sure. Simplicity.Aaron Levie: Yeah.swyx: Versus it's, it's structure versus less structure. Right. That's, that's all what it is. I do.Aaron Levie: I think the tricky thing is, um, is, is again, when this gets met with real humans, they're just going to their computer.They're just working with some people on Slack or teams. They're just sharing some data through a collaborative file system and Google Docs or Box or whatever. I certainly like the vision of most, most knowledge graph, you know, kind of futuristic kind of ways of thinking about it. Uh, it's just like, you know, it's 2026.We haven't seen it yet. Kind of play out as as, I mean, I remember. Do you remember the, um, in like, actually I don't, I don't even know how old you guys are, but I'll for, for to show my age. I remember 17 years ago, everybody thought enterprises would just run on [00:48:00] Wikis. Yeah. And, uh, confluence and, and not even, I mean, confluence actually took off for engineering for sure.Like unquestionably. But like, this was like everything would be in the w. And I think based on our, uh, our, uh, general style of, of, of what we were building, like we were just like, I don't know, people just like wanna workspace. They're gonna collaborate with other people.swyx: Exactly. Yeah. So you were, you were anti-knowledge graph.Aaron Levie: Not anti, not anti. Soswyx: not nonAaron Levie: I'm not, I'm not anti. ‘cause I think, I think your search system, I just think these are two systems that probably, but like, I'm, I'm not in any religious war. I don't want to be in anybody's YouTube comments on this. There's not a fight for me.swyx: We, we love YouTube comments. We're, we're, we're get into comments.Aaron Levie: Okay. Uh, but like, but I, I, it's mostly just a virtue of what we built. Yeah. And we just continued down that path. Yeah.swyx: Yeah.Aaron Levie: And, um, and that, that was what we pursued. But I'm not, this is not a, you know, kind of, this is not a, uh, it'sswyx: not existential for you. Great.Aaron Levie: We're happy to plug into somebody else's graph.We're happy to feed data into it. We're happy for [00:49:00] agents to, to talk to multiple systems. Not, not our fight.swyx: Yeah.Aaron Levie: But I need your answer. Yeah. Graphs or nerd Snipes is very effective nerd.swyx: See this is, this is one, one opinion and then I've,Jeff Huber: and I think that the actual graph structure is emergent in the mind of the agent.Ah, in the same way it is in the mind of the human. And that's a more powerful graph ‘cause it actually involved over time.swyx: So don't tell me how to graph. I'll, I'll figure it out myself. Exactly. Okay. All right. AndJeff Huber: what's yours?swyx: I like the, the Wiki approach. Uh, my, I'm actually

DescriptionIn this episode, Dave "CAC" Kellogg and Ray "Growth" Rike go point-counterpoint on two high-profile articles making waves across Wall Street and Silicon Valley: Citrini's provocative February 2025 report, The 2028 Global Intelligence Crisis, and Citadel's rebuttal, The 2026 Global Intelligence Crisis.Dave and Ray unpack whether AI is truly triggering an unprecedented economic collapse or whether Citrini's dark simulation is, as one economist put it, just "a scary bedtime story." They dig into the SaaS private credit contagion theory, the historic parallels of labor displacement, the role of government regulation, and why this particular AI scare hits closer to home than any previous tech disruption. As always, the brothers bring the receipts, including nearly 20 sources and 20 hours of research - so you don't have to.Full Episode Summary:Dave Kellogg and Ray Rike open by framing the episode as a tale of two AI futures: Citrini's alarming speculative simulation versus Citadel's data-driven rebuttal.The Citrini Case (Bear Case): Published February 22nd, Citrini's report simulates a scenario in which rapid AI agent adoption triggers a global intelligence crisis by mid-2028 featuring 10.2% unemployment and a 38% drop in the S&P 500. The report argues AI is categorically different from prior technology waves because it displaces cognitive workers, who represent roughly 75% of U.S. labor income.Citrini further warns that SaaS, already accounting for 23% - 25% of the $3 trillion U.S. private credit market could become the chip in the windshield that cracks the broader financial system, with ripple effects into insurance and the broader economy. Dave and Ray note that Citrini's word choices ran 3.4-to-1 negative, and flag that the firm may hold short positions — characterizing the piece as well-crafted "bear porn."The Citadel Rebuttal (Bull Case): Two days later, Citadel, a $65B AUM asset manager with 35 years of credibility responded with a data-driven defense. Software engineering jobs are up since January 2024, AI CapEx is 2% of GDP and AI-adjacent commodity pricing is up 65%. Citadel argues AI follows historical S-curve adoption patterns, that "recursive capability doesn't equal recursive adoption," and that technology has always complemented rather than replaced labor - pointing to Microsoft Office as a historical analogue.Dave and Ray's Take: Both hosts find Citadel more credible, but acknowledge real displacement risks ahead. Their key insight: the reason this particular AI scare is generating 10x more fear than past labor disruptions (auto workers, telephone operators, elevator operators) is that this time it's us — white-collar knowledge workers facing displacement. Ray adds that blue-collar jobs (truck drivers, Uber drivers, warehouse workers) face equal or greater long-term risk from AI plus robotics, but those disruptions don't generate the same visceral fear in the media and investor class. Both agree the timing of adoption is the biggest unknown. Long-term, history favors the Citadel view. Short-term, the transition could be painful.On Government Response: Dave and Ray agree that political and regulatory intervention is inevitable if unemployment spikes materially, whether through labor protections, AI regulation, or fiscal stimulus.On Economists' Reactions: Real economists, including Noah Smith (Noahpinion) and Wharton's Jeremy Siegel, largely dismissed the Citrini piece, wi Siegel arguing that productivity gains generate new income and demand, Smith calling it a "scary bedtime story." Dave's takeaway for operators: let the Metrics Brothers do the 20 hours of reading so you don't have to.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Send a textThe Wireless Way: Unpacking Enterprise Tech, AI, and Expense Management StrategiesIn this episode, Chris Whitaker hosts Hyoun Park, a market strategist with over two decades of experience in enterprise technology, to explore the evolving landscape of wireless expenses, AI integration, and operational efficiency. This interview offers actionable insights into managing complex enterprise mobility environments, leveraging AI responsibly, and aligning technology strategies with business outcomes.How telecom and wireless expense management have evolved from basic billing to strategic business tools in 2026.The impact of AI on telecom expense parsing, user democratization, and operational transparency.The significance of contract enforcement, governance, and compliance in long-term expense optimization.The debate between BYOD and corporate-owned devices, and the security and cost implications involved.Strategies for cross-selling IT services and expanding customer relationships over time.The overlooked importance of managing apps and hardware together in digital employee workflows.How companies can leverage actionable data for efficiency, effectiveness, and sustainability initiatives.Timestamps:00:00 - Introduction to Hyoun Park's background and expertise 01:45 - Hyoun's diverse career journey from music to tech and mobility 04:05 - The intersection of classical performance and enterprise technology 06:49 - Evolution of telecom expense management (TEM) and wireless expense management (WIM) in 2026 08:47 - Broader perspective: managing SaaS, cloud, and hardware expenses collectively 09:30 - Increase in demand for wireless expense management due to device proliferation and security concerns 12:51 - Cross-selling opportunities: expanding from wireless to broader IT services 14:09 - How to approach CIOs and CFOs with expense management solutions 16:32 - BYOD vs. corporate-owned device strategies and security considerations 20:31 - How AI is transforming expense parsing, democratizing telecom, and assisting end users 23:57 - Common pitfalls companies face when evaluating AI-driven operational tools 25:03 - The probabilistic nature of AI and importance of data governance and testing 26:45 - Overhyped vs. undervalued aspects of AI in business contexts 29:17 - Beyond cost savings: features and strategic advantages of expense management platforms 32:53 - Actionable data and the importance of real-time insights for operational efficiency 36:49 - The significance of managing apps and devices in tandem for digital employee workflows 38:22 - How Calero integrates mobile and SaaS management into a unified platform for better control 39:01 - Final thoughts: embracing technology to build strategic, efficient, and sustainable enterprisesResources & Links: Calero - Telecom and Mobility Management PlatformHyoun Park - LinkedIn“This is The Wireless Way—where mobility, IoT, and innovation drive real business outcomes.” Support the showCheck out my website https://thewirelessway.net/ use the contact button to send request and feedback.

Should marketing focus on brand or demand?That question has sparked more debate in boardrooms than almost any other marketing topic. But what if the premise is wrong?In this episode of Content Amplified, Benjamin Ard sits down with Filippa Noghani — global marketing leader, former first marketing hire at multiple startups, and builder of international teams across the U.S., Europe, and Latin America — to unpack how brand and demand actually work together.Filippa has built marketing functions from the ground up in SaaS, fintech, and IT consulting. She's led global teams. She's navigated seed-stage uncertainty and billion-dollar enterprises. And through experience, wins, and failures, she's learned one critical lesson: brand and demand are not competing forces. They are coordinated levers.This conversation breaks down how to structure teams, align marketing to revenue, use conversion signals wisely, and invest in both long-term brand equity and short-term pipeline — without falling into false trade-offs.If you're tired of the “brand vs. demand” debate, this episode will help you reframe it.What you'll learn in this episode:Why separating brand and demand too rigidly can hurt performanceHow brand credibility directly improves demand conversionThe difference between go-to-market content and broader brand positioningHow to structure global marketing teams around revenue contributionWhy opportunities — not just MQLs — should anchor KPIsHow to evaluate signals and shut off underperforming spend quicklyWhen startup-stage marketing requires different success metricsHow to align marketing and sales around shared opportunity goalsAbout Filippa NoghaniFilippa Noghani is a global marketing leader with over 20 years of experience building marketing functions from the ground up across SaaS, fintech, and IT consulting organizations.Originally from Sweden and based in New York for nearly two decades, Filippa began her career in marketing and graphic arts before moving into high-growth startups as a first marketing hire. She has led marketing through seed and Series A stages and later scaled global teams at larger organizations, including Vituso and SoftServe.Her expertise spans brand strategy, growth marketing, go-to-market execution, and revenue alignment across distributed international teams. Today, she leads global marketing initiatives focused on driving measurable opportunity contribution while strengthening brand presence in competitive B2B markets.Connect with Filippa:LinkedIn: Filippa NoghaniWebsite: Filippa.ioText us what you think about this episode!

In this episode, Christian Lund, Co-Founder of Templafy, reveals how the company built an AI-powered instruction and orchestration layer that helps over 800 enterprise customers — including KPMG, IKEA, and BDO — generate millions of compliant, on-brand business documents 100x faster. Christian shares why the real defensibility in AI isn't the model itself, but the mid-layer that tells the model exactly what to do. Christian breaks down how Templafy turns a simple 8-word user prompt into a 30-page AI instruction book, how their orchestration layer ensures consistent, high-quality outputs across millions of documents, and why enterprises that tried to build AI solutions internally ended up coming back to purpose-built tools. He also shares his honest take on whether AI is a force for good, what skills knowledge workers need to survive, and what he's teaching his three kids about working in an AI-first world. Key Topics Covered - How Templafy's AI instruction layer turns 8-word prompts into 30-page agent briefs - Why the orchestration mid-layer between users and AI models is the most defensible position in enterprise tech - How a Big Four accounting firm became Templafy's very first customer - The transition from rules-based automation to AI-first document generation with agents - Why enterprises took surprisingly long to move from AI toys to enterprise-grade tools - How Templafy integrates with Microsoft 365, Salesforce, and Copilot without getting swallowed by the SaaSpocalypse - The only 2 skills knowledge workers need to stay relevant: setting direction and validating output - Why brand and thought leadership are more important than ever for SaaS companies in 2026 - How BDO Canada saved $1.65 million in one year using Templafy's document automation - Christian's investor perspective on VC moonshots vs. real businesses that generate EBITDA **Episode Timestamps** 00:00 - Introduction and what problem Templafy solves 02:01 - The origin story: from consultants with no product to enterprise SaaS 04:18 - Why finance, law, and pharma became the core customer segment 05:41 - How a Big Four firm became the first customer during the cloud transition 09:02 - What makes a company good at adopting new technology 11:00 - How Templafy sits on top of Microsoft 365, Salesforce, and Copilot 11:37 - Surviving the SaaSpocalypse and finding the new world order 17:08 - Growth in the AI era and why enterprise demand took longer than expected 21:16 - Inside the boardroom: where Templafy fits in the AI landscape 23:31 - The recipe vs. cookbook analogy: how instruction books power AI agents 28:38 - How to become defensible when every company has the same AI models 31:58 - Why humans are more important than ever in enterprise sales 35:11 - The only 2 skills left for knowledge workers 35:52 - Educating children in the age of AI 40:01 - Christian's journey from CEO to CPO to CMO to co-founder 41:17 - Why brand and trust are hyper important in 2026 45:11 - B2B vs. B2C: Templafy's enterprise focus and how it compares to Gamma 49:21 - Christian evaluates the podcast's business model as an investor 54:57 - Is AI a force for good? Christian's honest answer 57:32 - Why do you do what you do? Christian's Socials: LinkedIn — https://www.linkedin.com/in/christianlundcph/ Partner Links Book Enterprise Training — https://www.upscaile.com/ Subscribe to our free newsletter — https://www.theaireport.ai/subscribe-theaireport-youtube

My guest today is John Arnold. John is probably the most famous energy trader of all time and certainly the most successful. One of the things John talks about is cultivating the best seat in your industry – the seat with the best perspective, the most information, the best systems..  John has been closely watching China's convergence in robotics, AI, and EVs, and shares his perspective from his recent trip to the country. We talk about the state of energy markets today – the misaligned goals and incentives, the NIMBYism that prevents building in America, and what he actually thinks about the wave of nuclear energy startups that everyone seems excited about.  John is also one of the most innovative philanthropists working today, applying that same analytical rigor to diagnosing structural failures across America — in healthcare, criminal justice, education, and beyond For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠Ramp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ramp's mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠ to sign up for free and get a $250 welcome bonus. ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Vanta. Trusted by thousands of businesses, Vanta continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Visit vanta.com/invest.  ----- This episode is brought to you by ⁠WorkOS⁠. WorkOS is a developer platform that enables SaaS companies to quickly add enterprise features to their applications. Visit ⁠WorkOS.com⁠ to transform your application into an enterprise-ready solution in minutes, not months. ----- This episode is brought to you by Rogo. Rogo is an AI-powered platform that automates accounts payable workflows, enabling finance teams to process invoices faster and with greater accuracy. Learn more at Rogo.ai/invest. ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps (00:00:00) Welcome to Invest Like The Best (00:02:43) Episode Intro (00:03:43) Learnings from John's Trip to China (00:06:28) The EV Industry in China (00:08:43) How Subsidies Create Intense Competition (00:10:54) US-China Relationship (00:12:42) The Cost of Greatness (00:14:52) Creating the Best Seat in the Market (00:19:30) Baseball Card Arbitrage (00:23:03) Trading Natural Gas Futures (00:24:59) Energy Market Making Explained (00:27:11) Why Energy is Exciting Again (00:31:14) Meeting the Increased Demand for Energy (00:32:53) Why Policy is the Biggest Threat to Progress (00:36:28) Fixing Energy Infrastructure in the US (00:39:29) Advanced Nuclear Technology (00:42:05) The Prospects of Energy Startups (00:43:44) Input Costs in Solar & Batteries (00:47:54) Geothermal Energy: The Most Exciting Sector (00:50:57) Housing Reform in the US (00:53:39) The Role of Philanthropic Foundations (00:57:00) Reforming the Criminal Justice System (01:03:48) Social Outcomes Downstream of Education (01:07:20) Misaligned Incentives in the Healthcare System (01:12:08) Journalism as a Public Good (01:14:17) The Kindest Thing

Dan Nathan interviews veteran tech investor Dan Benton about how tech investing has changed since Benton's 1991 “20 rules” at Goldman Sachs and why he's releasing new “2026 rules,” alongside launching a Substack. Benton contrasts a pre-internet, sell-side, information-advantage era with today's commoditized data, retail tools, and faster markets, arguing investors now differentiate by identifying secular themes and sticking with them. He emphasizes tech as “the market,” the need to respect the Fed, and that momentum in tech is driven by multi-year estimate trajectories, revenue acceleration, and operating leverage, with valuation often secondary until growth decelerates. They discuss stock-based compensation distorting earnings quality, rotations within AI beneficiaries, crowding and risk-off selloffs, and uncertainties around hyperscaler CapEx and OpenAI's private-market marks. The conversation covers SaaS disruption risk, Tesla and SpaceX “selling the future,” China's advantages, and why markets are faster but not smarter. Links Rules For Tech Investing (1999 Edition) Follow Dan's SubStack: substack.com/@danbenton —FOLLOW USYouTube: @RiskReversalMediaInstagram: @riskreversalmediaTwitter: @RiskReversalLinkedIn: RiskReversal Media

I walk through a complete 30-step playbook for building a modern SaaS company using AI agents, media, and sub-niche positioning. The core argument is that SaaS is evolving rather than dying, and the builders who win are the ones who combine a focused workflow product with a media flywheel and agent-powered execution. Drawing on my experience advising TikTok, Reddit, and building three venture-backed companies, I lay out a step-by-step framework any solo builder or small team can follow from niche selection through to becoming the default execution layer in their market. I'm hosting a free workshop so you can build your business in the age of AI. Sign up here: https://startup-ideas-pod.link/build-with-ai-2026 Timestamps 00:00 – Intro 01:18 – Step 1: Start with a sub-niche inside a big market 02:21 – Step 2-5: Map Workflow end to end 06:37 – Step 6-7: Create scroll-stopping content 10:15 – Steps 8–9: Double down on organic and run paid ads on winners 11:11 – Step 10: Capture emails from day one 11:47 – Steps 11–13: Manually perform the workflow and document every step 13:40 – Steps 14–16: Turn mechanical tasks into agent workflows and connect to real tools 14:47 – Step 17: Add orchestration, retries, and verifications 16:32 – Steps 18–19: Store user preferences and launch with high-touch onboarding 18:20 – Steps 20–21: Publish measurable proof and move to per-task pricing 21:21 – Steps 22–23: Outcome pricing and compounding value 22:07 – Steps 24–27: Expand workflows, build switching costs, create case studies 23:25 – Steps 28–30: Hire from the niche, reinvest profits, become the default layer 24:08 – Closing thoughts Key Points Start in a specific sub-niche, not a broad market — that is where sustainable cash flow lives, not VC competition. The future of SaaS starts as a service business: manually performing the workflow is how I learn what to automate. Media is a core business function, not an afterthought — content creation runs in parallel with product development from day one. Mechanical tasks are AI's strongest suit; separating judgment tasks from mechanical tasks is the key architectural decision. Per-task and outcome-based pricing is replacing per-seat models, and indie builders have a structural advantage in making that shift. Orchestration — coordinating agents, validating outputs, and resolving issues — is the new interface layer and the highest-value position to own. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

In this episode of the Niche Pursuits podcast, Jared sits down with Jamie I.F. for a brutally honest look at the Helpful Content Update and how a ~40% traffic and revenue drop torpedoed a $1.55M site deal mid-sale. He shares what it felt like watching peak months near $100K turn into a much smaller baseline, and why he stopped chasing an SEO recovery and chose focus instead. Jamie explains how a single customer saying they'd pay $2,500/month for an "affiliate finder" feature led him to spin it into affiliatefinder.ai, then grow with cold outreach (including ~1,000 emails) and paid ads. They cover metrics, pricing, 150 signups/week goals, and affiliate revenue.   Sponsor: Quiet LightGet a free, confidential valuation at https://quietlight.com/! Links & ResourcesCheck how AffiliateFinder works: https://affiliatefinder.ai/ Discover Answer Socrate and how it can help you: https://answersocrates.com/ Launch your SaaS affiliate program using Endorsely: https://www.endorsely.com/ Learn more about GainsApp: https://gainsapp.com/ Visit Jamie's free affiliate tracker for SaaS startups: https://increasing.com/ Watch Jamie's first interview: https://www.youtube.com/watch?v=7umFJyotZrY   Be sure to get more content like this in the Niche Pursuits Newsletter Right Here: https://www.nichepursuits.com/newsletter  Want a Faster and Easier Way to Build Internal Links?  Get $15 off Link Whisper with Discount Code "Podcast" on the Checkout Screen: https://www.nichepursuits.com/linkwhisper  Get SEO Consulting from the Niche Pursuits Podcast Host, Jared Bauman: https://www.nichepursuits.com/201creative 

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Would you like access to our advanced agency training for FREE? https://www.agencymastery360.com/training Most agency owners don't fail because they're bad at delivery. They fail because they underprice, overcomplicate, and build businesses that trap them instead of freeing them. Today's featured guest unpacks the type of life he envisioned when he set out to start an agency, it took to scale from charging $2,500 a month to closing $45,000/month retainers, surviving a market collapse, and making the counterintuitive decision to split one agency into two. Eli Rubel is the founder of Matter Made, a B2B SaaS marketing agency, and No Boring Design, a premium design studio serving high-growth tech companies. He entered the agency world in 2019 after burning out on the venture-backed SaaS model, despite a previous exit. What drew him to agencies wasn't prestige or scale; it was a desire to take control over his time, lifestyle, income, and location. Agencies, when built correctly, offered the fastest path to freedom without sacrificing ambition. Over the next few years, Eli scaled MatterMade aggressively, navigated a brutal tech downturn, and rebuilt his business with sharper positioning, stronger pricing, and clearer operational boundaries. In this episode, we discussed: Why hiking prices was the right choice early one How and why he decided to create his second agency The reason that shared services failed fast Subscribe Apple | Spotify | iHeart Radio Sponsors and Resources E2M Solutions: Today's episode of the Smart Agency Masterclass is sponsored by E2M Solutions, a web design, and development agency that has provided white-label services for the past 10 years to agencies all over the world. Check out e2msolutions.com/smartagency and get 10% off for the first three months of service. Toggl: Agencies could be losing 15–30% of their profit every year without seeing it. The usual suspects are time tracking, messy manual timesheets, scope creep, untracked revisions, and all those "quick" client requests that never get billed. That's why Toggl created the Agency Profit Heist, a fast, interactive way to uncover exactly where your margins are leaking. Start your investigation now at toggl.com/smartagency and use the code SMARTAGENCY10 at checkout for a 10% off annual plans. Why Agencies Beat Venture-Backed SaaS (If You Want Freedom) After years in venture-backed SaaS, chasing growth at all costs, Eli was done with a model he realized was grinding him down. The pressure, the lack of control, and the delayed payoff didn't align with what he actually wanted: family, flexibility, and financial independence. Agencies offered speed to cash and autonomy, which SaaS didn't. Instead of swinging for a hypothetical future exit, Eli chose a business model that paid well now and let him design his life intentionally. It was a shift he made with eyes wide open and clear expectations. The "best" business model depends on what you want your life to look like. For Eli, agencies weren't a step down. They were a strategic upgrade. Hiking His Prices Relying on Capacity and Confidence Eli's agency launched at $2,500 a month, not because that was the "right" price, but because he backed into a simple income goal. Sixteen clients at $2,500 got him to $40,000 a month. On paper, it worked. In reality, it broke fast. As soon as clients started saying "yes" too quickly, Eli knew something was off. The work was heavy, margins were thin, and building a team at that price point wasn't sustainable. Instead of obsessing over competitive pricing, he leaned into price sensitivity testing. Every time the team hit capacity, prices went up. If prospects said no, it didn't matter, they couldn't take on more work anyway. If prospects said yes, it justified hiring and scaling. Over three years, pricing climbed from $2,500 to $45,000 per month. What he learned was that underpricing doesn't just hurt margins. It traps you in constant hiring, delivery stress, and low-leverage work. Raising prices isn't greedy, it's operational discipline. What Actually Changes When You Raise Prices Eli didn't wake up one day and charge $45,000 for the same work he was doing at $2,500. Early on, the offering was vague: "We'll help with demand gen." Strategy was loose, scope was unclear, and the team was tiny. As pricing increased, the delivery model matured into a defined pod structure with paid media, design, strategy, and leadership baked in. However, once his agency hit around $15,000 per month, the services didn't change much after that. What changed was credibility. Case studies stacked up. Results became undeniable. Sales conversations shifted from "this is a great deal" to "this is what it costs to remove risk." Eli was upfront with prospects: MatterMade would be $10,000–$15,000 more per month than competitors, and nothing about the deliverables would look different. The difference was the track record. For buyers who weren't cash-sensitive, that pitch landed hard. They weren't paying for tasks. They were paying for certainty. Why Splitting One Agency into Two Was the Right Move At its peak in 2021, MatterMade was flying high, with $4.2M in EBITDA, tech clients everywhere, and acquisition talks underway. Then the tech market collapsed. Almost overnight, VC-backed clients cut agencies, froze spending, and hunkered down. They went from crushing it to losing nearly $200,000 a month. Eli held on too long, assuming it was temporary, and paid dearly for it. During the restructuring, Eli noticed something interesting: design had become a bottleneck across tech companies. Designers were laid off, but the need for creative work didn't disappear. So he spun up No Boring Design as a separate entity, fast. New brand, new site, launched in a weekend. Within months, it was profitable. Separating the businesses allowed each to have crystal-clear positioning. MatterMade stayed focused on growth marketing. No Boring Design became a premium creative solution for companies stuck in hiring freezes. Trying to keep design tucked inside the marketing agency would have slowed everything down. Separation created speed, clarity, and growth. Why Shared Services Across Agencies Sound Smart and Fail Fast One of Eli's biggest mistakes came after the split. He tried to create a shared management company to handle leadership, recruiting, and operations across multiple agencies. On paper, it looked efficient. In practice, it was chaos. Each agency had subtle but important differences in how it worked. SOPs drifted. Leaders got stretched thin. The "squeaky wheel" agency got attention while others suffered. Eventually, Eli unwound the entire structure. The hard truth: unless your companies operate almost identically, shared services create more friction than savings. Clarity beats efficiency. Do You Want to Transform Your Agency from a Liability to an Asset? Looking to dig deeper into your agency's potential? Check out our Agency Blueprint. Designed for agency owners like you, our Agency Blueprint helps you uncover growth opportunities, tackle obstacles, and craft a customized blueprint for your agency's success.

Phillip and Brian get deep on a week when everything felt a little unhinged: Shopify's AI sidekick started building custom apps, Iran allegedly took out AWS data centers mid-Claude-outage, and the McDonald's CEO went mega-viral just days after Phillip prophesied it. Underneath the chaos, a throughline emerges: the things we've used to measure value (view counts, credit card rewards, third-party apps, and AI contracts) are quietly expiring. Culture is first. Then comes commerce. This SKU Is Delicious Key takeaways: Shopify Sidekick can now build one-off apps on demand, raising real questions about the future of third-party SaaS. AI geopolitics is here: data centers are now strategic infrastructure, and the "human in the loop" question has military stakes. Meta's move to invoicing ends years of free credit card rewards for brands running paid social,  — and that party's been winding down anyway. MrBeast's long-form view counts are down 50% YoY, even with heavy paid promotion; the algorithm has shifted to interest-based, not subscriber-based. Media buyers optimizing for CPMs are chasing non-real traffic. — Rrecovering a sense of propriety is the only way back. In-Show Mentions: How MrBeast Dominated 2025 Using Advertising Phillip's Big Arch burger virality prediction Get on the list for the Future Commerce x Shoptalk After Party Associated Links: Check out Future Commerce on YouTube Check out Future Commerce Plus for exclusive content and save on merch and print Subscribe to Insiders and The Senses to read more about what we are witnessing in the commerce world Listen to our other episodes of Future Commerce Have any questions or comments about the show? Let us know on futurecommerce.com, or reach out to us on Twitter, Facebook, Instagram, or LinkedIn. We love hearing from our listeners! Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Sales is full of advice — but most teams only learn the real lessons the hard way.In this special episode of Revenue Leaders, we break down 5 brutal sales lessons most teams learn too late — from cold calling myths to sales conversations, proposals, and building systems that actually win clients.You'll hear practical insights on:• Why cold calling isn't actually dead• How organizations start winning more clients consistently• Why most sales conversations fail before they begin• How teams leave money on the table after winning an account• What separates average proposals from winning dealsIf you work in B2B sales, SaaS, professional services, or revenue leadership, this episode will challenge common sales assumptions and help you build a more effective sales process.⭐ Unlock free resources (templates, frameworks & prompts):⁠⁠⁠⁠⁠https://coachpilot.beehiiv.com/⁠⁠⁠⁠⁠Join the community & access 157+ templates, frameworks and mega AI prompts used by top revenue teams.Watch Full Episode on YouTube:⁠⁠⁠⁠⁠⁠https://www.youtube.com/@revenueleaders⁠⁠⁠⁠⁠⁠Follow us:⁠⁠⁠⁠⁠⁠https://www.instagram.com/davidfastuca/⁠⁠⁠⁠⁠

On the podcast: how Tinder's ML-powered paywalls drove millions in new revenue, the art of selling features à la carte without killing subscription revenue, and why Tinder Select flopped despite users saying they'd pay for it.This conversation is shorter than usual and will be featured in RevenueCat's State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:

For more thoughts, clips, and updates, follow Avetis Antaplyan on Instagram: ⁠⁠⁠⁠https://www.instagram.com/avetisantaplyan⁠⁠⁠In this episode of The Tech Leader's Playbook, Avetis Antaplyan sits down with Pranav Lal, Head of Business Technology at Gusto and former Enterprise Systems Leader at Slack, Eventbrite, Ethos, and OneTrust, to unpack what it really takes to build enterprise-grade systems inside hyper growth companies.Drawing from three pre-IPO to IPO journeys, Pranav shares hard-earned lessons about scaling from 500 to 5,000+ employees, why lead-to-cash is a company's “financial nervous system,” and how IPO readiness shifts the focus from shiny tools to provable controls and governance.The conversation dives deep into the reality behind AI hype — why AI can 10x velocity but cannot fix broken architecture, why SaaS isn't dead (but static SaaS is), and why giving AI agents “god mode” access is a dangerous mistake. Pranav also explores the evolving role of middle management, the shift toward outcome-based SaaS pricing, and how leaders must balance speed with architectural integrity.With insights on radical candor, trust-building after failed transformations, and how to protect team energy in high-pressure environments, this episode delivers a masterclass in modern technical leadership — where judgment, clarity, and guardrails matter more than ever.TakeawaysYou cannot outsource thinking. If you do, you inherit the mess.Scaling from 500 to 5,000 employees shifts from speed-driven execution to governance and ownership clarity.Lead-to-cash is the company's financial nervous system. Errors create revenue leakage and audit risk.IPO readiness is about provable controls, not new tools.Moving from MVP to enterprise-grade means building trust under stress, including uptime, recovery, and auditability.AI increases velocity, but without guardrails it creates chaos.AI cannot repair weak architecture or poor technical fundamentals.SaaS is evolving, not disappearing. Static SaaS is being replaced by dynamic and agent-driven systems.Clear communication is now a critical engineering skill.Middle managers must evolve into hands-on architects and AI orchestrators.Trust is rebuilt through consistency and quick wins.Strong leaders reduce ambiguity, protect team energy, and simplify complexity.Chapters00:00 Intro and Core Thesis01:00 Pranav's Background and IPO Experience01:28 Scaling from 500 to 5,000 Employees03:14 Why Lead-to-Cash Matters04:31 IPO Readiness and Compliance06:05 MVP Versus Enterprise-Grade Systems08:10 AI Hype Versus Reality12:07 Rebuilding Trust After Failed Transformations13:50 The Risk of Outsourcing Thinking17:44 Technical Skill Is Not Enough20:07 The Shift in Engineering Identity24:17 Is SaaS Dead25:46 The Future of SaaS Pricing26:57 The Danger of AI With Full Access28:34 Advice for Engineers in the AI Era36:06 Balancing Speed With Architecture41:16 Hiring for Ownership and Judgment43:15 Radical Candor and Leadership Growth46:35 The Billboard Advice47:02 Final Leadership PrinciplesPranav Lal's Social Media Link:https://www.linkedin.com/in/pranavl/Resources and Links:⁠⁠⁠⁠https://www.hireclout.com⁠⁠⁠⁠⁠⁠⁠⁠https://www.podcast.hireclout.com⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/hirefasthireright⁠

Get 90 days of Fellow free at Fellow.ai/coo In this episode, Michael Koenig speaks with Greg Keller, co-founder and CTO of JumpCloud, about identity access management and why it's becoming one of the most important operational systems in the age of AI. Greg explains how traditional identity systems were designed for office-based companies running Microsoft infrastructure and why that model broke as companies moved to SaaS, cloud infrastructure, and remote work. The discussion then turns to the next big shift: the rise of AI agents and synthetic identities inside organizations. As companies deploy more AI tools, the number of machine identities may soon outnumber human employees. Managing what those systems can access will become a critical security and operational challenge.   Topics Covered What a CTO actually does Greg explains the different types of CTO roles and how technology leaders help companies anticipate where the market is headed. Identity Access Management explained simply IAM answers three core questions inside every company: Who are you? What can you access? How is that access managed?   Why the old IT model broke Traditional identity systems were built for on-premise offices and Microsoft infrastructure. Modern companies now operate across: SaaS applications cloud infrastructure remote work environments multiple operating systems How JumpCloud approaches identity JumpCloud was built to manage identity across devices, applications, and infrastructure regardless of platform. Where Okta fits in the ecosystem Okta helped modernize browser-based authentication through Single Sign-On, while JumpCloud focuses on broader identity infrastructure.   AI, Security, and Synthetic Identities Why COOs should push AI adoption Greg argues AI adoption is no longer optional. Companies must encourage teams to improve productivity and efficiency using AI.   The rise of synthetic identities AI agents, bots, APIs, and service accounts are becoming new actors inside companies that require identity governance.   Bots may soon outnumber employees Organizations will soon manage more machine identities than human ones.   AI as a potential insider threat AI systems can become security risks if they are granted excessive permissions or misinterpret policies.   The API key governance problem Many AI integrations rely on API keys, which are often poorly managed and can create hidden security risks.   Key Takeaway As companies adopt AI, identity access management becomes the control layer that determines what both humans and machines are allowed to do inside the organization. The companies that manage identity well will move faster and operate more securely.   Links: Michael on LinkedIn: https://linkedin.com/in/michael-koenig514 Greg on LinkedIn: https://www.linkedin.com/in/gregorykeller/ JumpCloud: https://jumpcloud.com/ Between Two COO's: https://betweentwocoos.com Episode Link: https://betweentwocoos.com/ai-agents-identity-access-greg-keller

Our HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. She's worked on a diverse range of products – leading the product teams through discovery, prototyping, testing and delivery. Lily also founded ProductTank Bristol and runs ProductCamp in Bristol and Bath. Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

Stefano Puntoni, Marketing Professor at the Wharton School and Co-Director of the Wharton Human-AI Research Program, explains how artificial intelligence is pressuring SaaS margins, lowering barriers to entry, reshaping pricing models, and marking a potential inflection point for enterprise software markets. Hosted on Acast. See acast.com/privacy for more information.

With content getting cheaper and noise getting higher, which parts of the old playbooks still hold up, and which ones break?Marketing-led growth keeps getting pricier, and “more content” is no longer a moat. So you end up staring at the same fork in the road Stijn calls out here, keep leaning on sales, or let the product do more of the heavy lifting. In this episode, Kalungi founder Stijn Hendrikse sits down with Wes Bush (author of Product-Led Growth) to talk about where product-led growth and sales-led growth actually meet, and why most B2B teams land in the middle. You'll hear what “try before you buy” really means in 2026 (and what happens when you don't offer it), how to think about getting users to value fast, and where friction still belongs. In this episode, you'll learn:You cannot skip the MVP stage in SaaS.Product-market fit definitions have evolved over time.AI is accelerating the achievement of product-market fit.Understanding your business model is crucial for growth.Different go-to-market strategies suit different business models.Product-led growth relies on the product being the main sales driver.Marketing-led growth focuses on educating potential customers.Sales-led growth requires building trust and credibility.Alignment between go-to-market strategies and business models is essential.AI tools are becoming indispensable in marketing and sales.After watching, you'll have a clearer way to decide what mix fits your business, and what to change first when the product has to carry more of the growth. 

A story about destroying your own work—and creating what lastsThis episode is for sales-led SaaS founders who suspect their product is slowly becoming a custom shop—and don't know how to stop it.Bassem Hamdy, CEO and Co-Founder of Briq, has spent 25 years in construction technology—three software revolutions, three companies.He says Briq found product market fit every 24 months. Each time meant tearing something down to build the next version.Each time, the same thing triggered the rebuild — the company had started solving for individual customers instead of the market.And this inspired me to invite Bassem to my podcast. We explore why the instinct to please your biggest customers creates exactly the kind of fragility that kills companies. Bassem shares hard lessons about killing a product he spent two years building, the moment his QA team exposed how far the company had drifted, and why domain expertise—not platform size—determines who wins in vertical AI.We also zoom in on two of the 10 traits that define remarkable software companies: – Acknowledge you cannot please everyone – Master the art of curiosityBassem's journey proves that remarkable companies refound themselves before the market forces them to.Here's one of Bassem's quotes that captures what happens when a company starts drifting:"Software is like jello. You slap that thing, it's going to shake the hell out of it. So the moment you inject that code, that's client specific, you're pooched."By listening to this episode, you'll learn:Why saying yes to customers can turn your product into something nobody else wantsWhen to check whether your team is building a product or managing client ticketsWhy deep domain expertise matters more than platform size in the age of AIHow one metric—revenue per employee—changes every decision a CEO makesFor more information about the guest from this week: Guest: Bassem Hamdy, CEO and Co-Founder of Briq Website: briq.com

In this episode of LERMA/'s Loud and Clear podcast, host Francisco “Pancho” Cardenas speaks with Lindsay Davis, founder and CEO of One Bee Consulting and founder and CEO of FemTech Association Asia. Lindsay shares her path from multicultural advertising in Dallas to luxury and international leadership in London, then relocating to Singapore in early 2020, where she discovered FemTech while moderating panels and reading Invisible Women. She describes FemTech as “female technology”—apps, SaaS, medical devices, wearables, and services spanning women's health across life stages, and emphasizes Asia as a large but still untapped market.The conversation outlines major barriers holding women's health back: it has been under-researched, underserved, and underfunded; stigma remains high (including a cited figure that 52% of women in Southeast Asia are uncomfortable discussing health needs openly due to fear of judgment or shame); awareness is low (42% don't use FemTech due to lack of awareness and understanding); and funding gaps persist (2.3% of total VC funding goes to women-founded companies, and only about 24% of VC decision makers in Southeast Asia are women). Lindsay also raises systemic content censorship, where women's health content is treated as risky or sexual—leading to downranking, shadowbans, and rejected ads—sharing examples like a breastfeeding support app removed for “nudity” and restrictions on terms such as “vaginal cancer,” with 95% of founders reporting content suppression.A central theme is how marketing and advertising can play a stronger role in education and normalization. Lindsay urges agencies and brands to start in-house by improving benefits, ERGs, and workplace support (including maternity return), and by offering inclusive health education programs. She argues advertising shapes culture and can drive health literacy through advocacy, PR, and more inclusive briefs that reduce gender bias. She suggests large agencies press major healthcare and pharma clients on their women's health strategies, while smaller agencies can support FemTech startups through affordable, fractional or retained marketing models aligned to early-stage budgets. Lindsay notes that in Asia many startups scale via corporate partnerships, and her association has grown into a cross-country network spanning 10 Asian markets, funded through corporate engagements and programming aimed at building awareness, trust, and access in women's health.Useful Links:Linkedin. Instagram.Web FemTech Linkedin Femtech Instagram Femtech UN report. Guest: ⁠⁠⁠⁠Lindsay Davis, Award-Winning Founder-FemTech Association Asia I Strategic Partnerships I Community Building I Customer Experience I Milken Institute I UN ESCAP I UNFPA I Tatler Front & Female Award I Board Advisor I Moderator/SpeakerProducers:⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠Victor Cornejo Tell Me More Studios⁠⁠⁠⁠⁠⁠ & ⁠⁠⁠⁠⁠Pranav Kumar at LERMA/⁠⁠⁠⁠⁠Host: ⁠⁠⁠⁠⁠⁠Francisco Cardenas, Executive Director, Brand Integration at LERMA/⁠⁠⁠⁠

OneCrew is building end-to-end operational software for asphalt and concrete contractors—a segment caught between Procore's general contractor focus and ServiceTitan's field services model. After leaving Bain & Company and Google, Ari Bleemer and his co-founder Max identified that self-performing specialty contractors who handle everything from estimating to payment collection had no purpose-built platform. In this episode, Ari shares how they've spent four and a half years building trust in an industry skeptical of software promises, why they resisted the urge to expand horizontally across multiple construction trades, and what they learned about sustainable vertical SaaS growth.Topics Discussed:How the middle segment of construction—self-performing contractors who run the full project lifecycle—remains structurally underservedBuilding trust in a market burned by consultants promising custom software for $10,000 that never worksWhy every employee at OneCrew, regardless of function, goes through industry-specific onboarding to learn paving terminology and contractor workflowsThe strategic decision to delay expansion into adjacent verticals despite having configurable product architectureHow sustained market presence compounds credibility faster than any go-to-market tacticGTM Lessons For B2B Founders:Map the white space between dominant platforms: OneCrew identified that Procore owns general contractors coordinating multiple trades, while ServiceTitan and others own single-visit field services. The gap: specialty contractors executing complete projects—estimating, proposing, executing, and collecting payment. Ari describes it as "the entire middle of the industry where you have a lot of self perform contractors, specialty contractors, trade contractors, subcontractors...that are actually running a process from start to end." Map your market by understanding what established platforms actually serve versus claim to serve, then target the operational workflows that fall through the cracks.Use "niche" skepticism as market validation: When VCs, friends, and family question if your market is too narrow, you've likely found defensible positioning. Ari's test: "Have you been on a sidewalk today? Have you driven on a road today? Have you been in a parking lot today?" The paving industry powers daily infrastructure but gets zero attention from horizontal software players or large AI companies. Founders should seek markets where usage is ubiquitous but mindshare and software investment are minimal—that's where you build sustainable moats.Make product fluency a company-wide competency: OneCrew requires every hire—engineers, sales, operations—to learn paving industry terminology, contractor pain points, and workflow nuances during onboarding. This isn't just sales training; it's embedding industry context into product decisions, customer conversations, and roadmap prioritization. The payoff: "Contractors come up to us and say like, it feels like you guys actually get it, which there's no better compliment for us." In vertical SaaS, domain expertise distributed across the entire company drives faster iteration cycles and deeper customer trust than any single "industry expert" hire.//Sponsors:Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.ioThe Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co//Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

What if the biggest bottleneck in your commerce strategy isn't the strategy itself, but the time it takes your team to actually perform the actions to execute it?Agility requires not just having the right insights, but also the operational capacity to act on them at the speed the market demands.Today, we're going to talk about a critical bottleneck many brands face: the delay between data-driven insight and real-world execution. Commerce teams are often drowning in data but struggle with the manual, time-consuming work of implementing changes, whether it's updating product pages or optimizing media spend. This has led to a major shift, where brands are looking beyond traditional agency models and toward a new paradigm of 'agentic AI'—using automated agents to handle execution, freeing up human experts to focus on what they do best: strategy.We are here at eTail Palm Springs, and to help me discuss this topic, I'd like to welcome, Himanshu Jain, Co-Founder and Head of Product, and Bill Schneider, VP Product Marketing at CommerceIQ. About Bill Schneider and Himanshu Jain Himanshu Jain is the Cofounder and Head of Product at CommerceIQ, a Series D agentic AI company based in the Bay Area. CommerceIQ is a leader in retail technology, having raised $200M from SoftBank and Insights Partners, and serving 10 of the top 12 CPG brands globally. He builds vertical AI and autonomous agent platforms that help the world's largest consumer brands win across ecommerce and omnichannel retail. Over the past decade, he has repeatedly taken AI products from zero to product–market fit, scaling them into multi-million-dollar businesses across retail media, pricing, supply chain, and digital shelf. With deep roots in machine learning, SaaS and enterprise strategy, he operates at the intersection of advanced AI systems and measurable commercial impact. Himanshu Jain is the Cofounder and Head of Product at CommerceIQ, a Series D agentic AI company based in the Bay Area. CommerceIQ is a leader in retail technology, having raised $200M from SoftBank and Insights Partners, and serving 10 of the top 12 CPG brands globally. He builds vertical AI and autonomous agent platforms that help the world's largest consumer brands win across ecommerce and omnichannel retail. Over the past decade, he has repeatedly taken AI products from zero to product–market fit, scaling them into multi-million-dollar businesses across retail media, pricing, supply chain, and digital shelf. With deep roots in machine learning, SaaS and enterprise strategy, he operates at the intersection of advanced AI systems and measurable commercial impact. Bill Schneider and Himanshu Jain on LinkedIn: https://www.linkedin.com/in/bill-schneider-b32a6a/ Resources CommerceIQ: www.commerceiq.ai The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703 Drive your customers to new horizons at the premier retail event of the year for Retail and Brand marketers. Learn more at CRMC 2026, June 1-3. https://aglbrnd.co/r/d15ec37a537c0d74 Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716ba Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

In this episode the hosts break down a one-year-old “digital wellness” SaaS porn-blocking app doing ~$100K in profit from a single YouTube video—and debate whether it's worth $600K or just a $30K rebuild with better marketing.Business Listing – https://flippa.com/12197961-1-porn-blocker-app-ios-windows-b2c-saas-196k-gross-161k-net-604-subs-10k-mrr-0-57-dispute-all-from-a-single-traffic-source-huge-untapped-growthWelcome to Acquisitions Anonymous – the #1 podcast for small business M&A. Every week, we break down businesses for sale and talk about buying, operating, and growing them.Looking to build a professional website in minutes? Try Wix: https://wix.pxf.io/c/6898629/3115214/25616?trafcat=templateHubSpot is the backbone for how businesses scale without chaos. Try them out here: https://go.try-hubspot.com/OeG9Vr

Tod Sacerdoti is the CEO and co-founder of Pipedream, which recently sold to Workday. Tod is also a general partner at Flex Capital, where he's invested in over 400 companies including Chime, Vercel, Replit, CodeRabbit, Mercury, and many others. He previously founded BrightRoll, a programmatic video advertising platform that sold to Yahoo for $640 million in 2014. In this episode of Summation, Tod and Auren discuss:Why seed investing has the highest annualized returns of any venture asset classFirst-gen AI companies being the most vulnerable to AI disruptionQSBS and why it's the most important tax benefit nobody talks aboutThe founder code and what happens when people break itYou can find Auren Hoffman on X at @auren and Tod Sacerdoti on X at @tod

Building software is supposed to take years of coding, endless stress, and a long grind to profitability. Omar wanted to test that belief. After a decade running WebinarNinja, he set out to answer one bold question: can you build a real SaaS product in just 7 days using nothing but AI? In this episode, Omar shares his experiment to create a fully functional, ready‑to‑sell app powered entirely by AI. This is a very special kind of episode. You'll get to follow along as the process unfolded day by day, something that's never been done before on the show. Omar walks through the planning, the tools he used, the testing, and the problems he ran into along the way. You'll hear what worked, what didn't, and why clarity and focus matter more than speed. It's an inside look at an experiment designed to give you both inspiration and practical takeaways. Hit play at the top of the page and experience Omar's 7‑day AI SaaS experiment. The lessons inside could reshape how you think about building your next software idea. MBA2749 Can You Build A Profitable SaaS In 7 Days With Just AI? My Experiment With Proof!See Nicky AI in action - watch the demo on YouTube now! Guest CollaboratorChris Ashby - Telescope.design Founder of Telescope, guiding AI‑driven startups with impactful design and strategy. Tools Mentioned Leap OpenAI Stripe GitHub Cursor Wispr Flow Mux ChatGPT Windsurf Lovable Watch the episodes on YouTube: https://lm.fm/GgRPPHiSUBSCRIBEYouTube | Apple Podcast | Spotify | Podcast Feed Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.