AI makes bad product marketing look finished. That’s the part I don’t trust. A competitive brief can sound current while leaning on an old source. Positioning can sound sharp even when the logic underneath is a guess. A battlecard can look complete and still fail the rep who
Boris Cherny
- Ship with minimal scaffolding and let the model choose tools and order of operations, rather than boxing it into rigid workflows…
- Watch how people hack your product for purposes it wasn't designed for; that latent demand, like data scientists using a terminal…
- Bet on the more general model over time instead of fine-tuning or tiny models, since scaffolding gains of 10-20% often vanish…
What happens when you hand your opportunity solution tree to an AI? Vistaly rebuilt its entire product to find out—and the agents were the easy part. In this episode of Just Now Possible, Teresa Torres talks with Matt O'Connell (Co-Founder and CEO), CP Dehli (Co-Founder), and Steve Klein…
Linear CEO @karrisaarinen: "Making products produces two things: the product, and the learning. The effort you put into building and designing things teaches you something about what the problem is, what the customers want. We're in this time now that there's this danger of
Bending the universe in your favor
- Know what you want from your career and your next role, and ask for it clearly, framed around how the role solves a real problem…
- Time promotion conversations to the company's talent calendar and pitch concrete org-level gaps you can fill, such as an org…
- Lean into your zone of genius by auditing your calendar, grouping activities by energy, and deliberately protecting time for the…
Building Rhea's Factory: How AI-Designed Enzymes Could Finally Solve Plastic Recycling
“Listen to this episode on: Spotify | Apple Podcasts Only 10% of the plastic we manufacture gets recycled. We've been trying to solve this for a hundred years using the same mechanical and chemical tools that created the problem. What if biology—specifically, engineered enzymes—is the missing piece? In”
TBM 437: Tokens, Hours, Points, and Other Curious Proxies
John Cutler examines the sudden enthusiasm for measuring "return on tokens" as AI usage grows inside companies. He argues that vendors and executives eager for clean numbers are reaching for yet another proxy, much like…
Brian Balfour: 10 lessons on career, growth, and life
- Building a great product is necessary but not sufficient; durable winners separate themselves by building strong distribution…
- New distribution platforms tend to follow a cycle: competitive consensus, identifying a moat, opening a third-party ecosystem…
- Being early to a new platform matters because late adopters face shrinking windows, since platform cycles appear to be getting…
How Perplexity builds product
Lenny Rachitsky interviews Johnny Ho, co-founder and head of product at Perplexity, about how a fast-growing AI search company builds product with a very small team. Perplexity uses AI to answer its own operational…
Conversations with Claude: Can You Conduct a Content Audit?
Teresa Torres introduces a new series, Conversations with Claude, showing how she uses Claude Code for real work. Her first example is a content audit of Product Talk, which she delegated to Claude with a task file and…
I am an idiot
Julie Zhuo's short essay, titled "I am an idiot," reflects on intellectual humility in an era when AI systems can seem to know more than we do. The piece is framed as personal notes rather than a formal argument, using…
Predicting the Future - All Things Product Podcast with Teresa Torres & Petra Wille
Teresa Torres and Petra Wille argue that confident predictions about AI-driven change are often wrong, and that betting everything on one forecast is risky. Humans are poor at forecasting, and early adopters' experience…
Inside the expert network training every frontier AI model
- Post-training, not pre-training, now drives most model gains, so high-quality expert data targeting specific capability gaps is…
- The labeling market has shifted from cheap generalist labor to domain experts, so the right supply is credentialed specialists…
- Access to a trusted audience is the real moat in human data; owning an audience removes customer acquisition costs compared with…
Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history
- Eric Simons says deep technology bets can take years to find their market; his team stayed alive by bootstrapping and keeping…
- Simons advises treating spending as a default no until you see real customer pull, and buying software with the goal of cutting…
- Simons notes that when a launch unexpectedly takes off, pricing and infrastructure often break first; Bolt rolled out upgrade…
What I Learned from the Recent Wave of Package Hacks (And Is Cowork Immune?)
Teresa Torres recounts how a worm known as Mini Shai-Hulud, which spread through popular JavaScript packages in May, pushed her to rethink the security of her AI-assisted building. She explains that most malware follows…
$46B of hard truths from Ben Horowitz: Why founders fail and why you need to run toward fear (a16z co-founder)
- Hesitation is usually the most destructive leadership mistake; when both options look bad, make an explicit decision rather than…
- Leaders add real value only when they make decisions most people disagree with; if everyone agrees, the leader added nothing.
- Success is built from a long chain of small, hard decisions, and each good choice sets up the next, so keep making the next one.
Humanizing product development
- Make new R&D or incubation teams feel core to the company mission and share their wins, so the rest of the organization doesn't…
- For algorithm-heavy products, decide explicitly what the algorithm owns versus what people own, and design interfaces that let…
- Treat operational control as a first-order product requirement when a marketplace needs day-to-day human adjustments like weather…
Team Autonomy and AI
Marty Cagan argues that product teams often conflate empowerment and autonomy, and that the two should be considered separately. Empowerment means a team can choose how to solve a problem, while autonomy means it can…
The HP AI Workstation
Marty Cagan's first published article, from a 1986 HP Journal issue, is a technical overview of Hewlett-Packard's internal AI Workstation research program and its first product, a Common Lisp development environment. It…
TBM 428: Yes, Robot. Yes, Boss?
John Cutler reflects on the growing role of AI in product and team work, framing it as something that can play several supporting roles: a scribe that captures notes, a thought partner that challenges ideas, a tool that…
INSPIRED in the Generative AI Era
Marty Cagan introduces a re-recorded audio edition of INSPIRED and reflects on how the book has held up since its 2007 and 2017 editions. He argues its focus on underlying principles rather than current process is why…
25 proven tactics to accelerate AI adoption at your company
Lenny Rachitsky and Peter Yang distill tactics from AI-forward companies like Shopify, Ramp, Zapier, Duolingo, Intercom, and Whoop on driving employee AI adoption. The core argument is that the main barrier is…
How should you monetize your AI features?
Lenny Rachitsky and Palle Broe analyze how 44 application-layer tech incumbents monetize AI features, comparing direct and indirect strategies. They argue direct monetization (add-ons, standalone products, or plan…
The bespoke software revolution? I'm not buying it.
Jason Fried argues against the idea that AI will spark a bespoke software revolution where everyone builds their own custom tools. He notes that custom software already exists and is usually bloated because clients pay…