Every two weeks, we dive into the vast ocean of product content online, both free and paid. We sift through it all to bring you the crème de la crème. Our round-up includes carefully curated links and concise excerpts from top content.
This week’s highlights feature:
Top 4 Long-Form Articles/Podcasts
Top 3 Tweets
Top 3 LinkedIn Posts or Short Videos
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Top Long-Form Content
What we liked: It’s rare to see a foundational figure publicly revise his own canon, and the lessons land hard in an AI world. Viability risk is exploding with AI costs, and competitors now move faster than ever.
Choice quote: “A much more important “why?” and what I should have emphasized is “why are people using – or not using – our product?””
Your AI Product Costs More Than It Should. This Prompt Shows You Exactly Where.
What we liked: A prompt for identifying opportunities to reduce cost when the AI features underneath aren’t netting the revenue you expect.
Choice quote: “A product that costs $0 to serve 71 users costs roughly $0 to serve 200. That math is the moat.”
Inside the AI Stack of an $8.3B AI Company’s Product Team
What we liked: A look inside an AI-native product organization with its concrete blueprint for making a whole team more productive with AI, not just individuals. The four governing rules for the repo are easy to steal, and “agents are the majority user” is a shift every PM building for developers should take seriously.
Choice quote: “The new party foul is flooding your coworker’s context window.”
Your company needs a pricing constitution.
What we liked: It’s a timely, practical fix for a problem AI-speed shipping is making worse, with principles that PMs and founders can adopt nearly as-is. The “three biggest reasons someone chooses each plan” test is a great gut check for any pricing page.
Choice quote: “Every time you monetize an input, you give customers a reason to ration the exact behavior that leads them toward value.”
Top Tweets
The Cord That Beat $45 Billion of Robots
What we liked: A memorable historical story that lands a sharp point for product and engineering leaders. When output gets cheap, the value moves to checking whether it works, and mandates that measure teams on volume are starving that step.
Choice quote: “When code costs nothing to write, reading it becomes the most expensive thing a company does.”
What we liked: It’s easy to try tomorrow, and it offers a clear diagnostic. An empty solution-space trash can mean the team isn’t comparing options. An empty problem-space trash can may signal an innovation gap or a top-down culture. The “zombie opportunities” ritual for retiring problems the org keeps resurfacing is a nice bonus.
Choice quote: “An empty solution-discovery trash can is a clear red flag: it means the team isn’t comparing and contrasting multiple options.”
Frontier Models vs. 105 Planted Bugs
What we liked: The results from a homegrown benchmark comparing frontier models on their ability to find planted bugs in real repositories.
Choice quote: “Anthropic is back in the game.”
Top LinkedIn Posts & Short Videos
5 Ways I’ve Put Product Discovery on Auto-Pilot With AI (and What I Haven’t)
What we liked: Specific, immediately usable AI-assisted discovery setup paired with a clear line on what not to hand off. The point about keeping synthesis human to protect your own product sense is one many teams will learn the hard way.
Choice quote: “Synthesis is more than insights. It’s building your own product sense by connecting the dots.”
What we liked: It names a very current AI-era trap: bad inputs produce plausible-looking results instead of visible failures. It closes with three practical fixes: get real users in early, deliberately test edge cases, and focus on the details that determine whether users get value.
Choice quote: “Poor inputs don’t necessarily generate obvious errors. They can generate something that looks plausible but isn’t very good.”
What we liked: A crisp explanation of where the moat moved once engineering stopped being the rare input. The “kill 80% of it by noon” standard is a useful gut check for AI-first teams drowning in prototypes.
Choice quote: “Without taste, speed just means you build the wrong thing faster.”
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