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GROWTH SHARES WHAT'S WORKING
💺 Seat-based models break down when AI does the work.
Parse notes
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💺 Seat-based models break down when AI does the work.
Learn how to navigate the tension between self-serve and enterprise monetization, and how to start thinking about outcome-based value.
Most AI narratives break down under closer data: code-gen tools are rebounding, job trends are mixed, early valuations don't predict much, and data centers are scaling at extraordinary speed. The real lesson is not to overreact to noisy data or tidy storylines.
Google's TPU push threatens Nvidia's dominance, and Google's consumer reach challenges OpenAI, though ChatGPT's large user base still gives it a strong moat. OpenAI must adopt advertising to protect that position and compete with Google's scale.
Stakeholders support product teams by sharing context, framing clear problems, and enabling access to customers and data. This lets teams quickly test and deliver solutions that drive real business results while also managing essential operational tasks.
The AI boom may be a bubble fueled by extreme valuations and harsh work culture, where many workers risk years of effort for equity that could end up worthless. The real takeaway is to value people now, because when the frenzy ends, the memories we make with each other matter more than the outcomes.
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Most teams ask "Which tool is best?" The better question: "Which approach gets us from idea to collaboration fastest?" Miro's AI prototyping landscape guide [9] provides a requirement question set, decision framework, and evaluation scorecard so you can pick the tools
Airtable acquired DeepSky because it could turn unclear problems into structured, trustworthy decisions, something most AI tools skip. Its reasoning system and polished outputs paired naturally with Airtable's workflow tools, completing the path from problem to action.
Marily Nika's workflow chains AI tools together to turn ideas into full product visions in minutes, using structured debates and rapid “tool hopping” to find better answers. Her message is simple: PMs who master AI will far outperform those who do not.
Micromanagement can be useful when a project is complex or demands strong taste, but it is harmful when driven by insecurity. The key is to communicate clearly so your involvement feels intentional and supportive, not controlling.
Mid-range exits often feel great for founders but disappointing for later investors, creating tension when a company gets acquisition offers in the $150–$300M range. The best defense is smart fundraising, early secondary liquidity, and clear alignment with investors from the start.
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Knowing how to use AI tools is now a real career advantage.
AI agents make high-value but historically unaffordable work suddenly scalable.