
The Vibe Coding Stall: Why Your AI-Assisted Code Never Ships
AI-assisted code works in demos. It stalls in production. Here's why the gap exists and how to close it.
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This is where long-form thinking lives: practical essays on strategy, prioritization, and how strong PM leaders improve over time.

AI-assisted code works in demos. It stalls in production. Here's why the gap exists and how to close it.
Read articleProduct leader & founder, Product Manager Hub

AI-assisted code works in demos. It stalls in production. Here's why the gap exists and how to close it.
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MCP isn't a technical detail—it's a strategic decision about whether your AI product can evolve independently of your model vendor. Here's how to think about it.
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Anthropic's internal analytics went from 21% to 95% accuracy with zero model improvement. What that means for where AI moats actually live—and why you're fighting for the wrong layer.
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Speed and feature parity are the trap. The moat moves toward embedded domain knowledge and workflow depth before foundation models commodify the gap.
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When AI accelerates your team, bottlenecks don't disappear—they migrate. Where they surface reveals exactly what your organization doesn't yet know how to do. Here's how to read the signal and fix the gap.
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Retention looks fine—DAU up, sessions steady—but users do their real thinking in ChatGPT and Claude, not your product. Here's what that split means.
Read articleMost PMs think AI means more strategy time. It's the opposite: the gap between PMs who talk product and those who ship is widening fast.
Read articleYou promote your best PM to director and lose the one person who actually ships. The Director Trap—and how to avoid it.
Read articleYour product team just shipped a new AI feature. Forty-eight hours later, OpenAI shipped a better model. Who won?
Read article12 articles — new essays publish here as the library grows.
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If an essay named a stall you're in, tell me where you're stuck. I'll tell you if I can help close the gap from demo to done.