AI as Your New Strategic Thought Partner, Jeremy Utley (Stanford)
Stanford's Utley shows why treating AI as a teammate, not a tool, changes the quality of strategic thinking you get out of it.
Open youtube.com →4 questions founders actually ask, each with a straight answer and the resources worth your time.
Founders treat AI less like a search engine and more like a smart colleague they can think out loud with: they paste in their strategy doc, pricing plan, or investor update and ask it to poke holes, list risks, and argue the other side before they commit. Because the default behavior of ChatGPT or Claude is to be agreeable, the trick is explicitly asking for criticism ('challenge my assumptions', 'tell me why this fails') and giving it real context about your business. Used this way, AI becomes a cheap, always-available second opinion that sharpens decisions instead of just producing text.
Stanford's Utley shows why treating AI as a teammate, not a tool, changes the quality of strategic thinking you get out of it.
Open youtube.com →First-person, very fresh walkthrough of using AI as a sparring partner, devil's advocacy, blind-spot hunting, and voice-thinking, with concrete examples.
Open wondertools.substack.com →A real operator demos turning Claude into a research and thinking assistant over 1,500 of his own notes, thinking-partner use at its most concrete (YouTube version linked in the post).
Open every.to →The clearest judgment guide on when leaning on AI for decisions helps and when it quietly hurts, essential calibration before you trust its feedback.
Open oneusefulthing.org →Most founders don't have anyone who will tell them the uncomfortable truth for free at 11pm, AI can play that role if you set it up right. Founders use it to rehearse board meetings and fundraises (asking it to fire the hardest investor questions at them), to simulate a 'personal board of advisors' with different personas, and to run devil's-advocate passes on big decisions so the first pushback they hear isn't in the actual boardroom. The payoff is that you walk into high-stakes conversations having already heard the worst objections.
Gives you a copy-paste system prompt that turns ChatGPT/Claude into a 'challenge first, support second' devil's advocate, tested on real business decisions.
Open aimaker.substack.com →A step-by-step method for designing an AI 'board' with distinct seats, an inverter to challenge assumptions, a simplifier, a builder, and when to invoke each.
Open mehtacognition.substack.com →A chief of staff compares Claude, ChatGPT, Gemini, and Copilot as thought partners for anticipating tough board questions on a real quarterly deck.
Open sectionai.com →Solo founders use AI as a stand-in for the co-founder or first hires they don't have: Claude or ChatGPT becomes their developer, marketer, lawyer-adjacent reviewer, customer-support drafter, and sysadmin, available around the clock for the price of a subscription. The pattern that works is collaboration, not delegation, you stay the judge of quality in areas you know, and use AI to get to 'good enough' fast in areas you don't. Coding tools like Claude Code have pushed this furthest, letting one person ship what previously took a small team.
A bootstrapped SaaS founder shows exactly how he uses ChatGPT and Claude to cover coding, marketing, support, and sysadmin gaps, honest about where it works and where it doesn't.
Open thebootstrappedfounder.com →Hour-by-hour breakdown of one operator running multiple AI coding agents in parallel, the most concrete picture of one person doing a team's output.
Open every.to →The definitive long-form conversation with the most famous solo founder alive on building and running multiple profitable AI products entirely alone, a genuine classic.
Open youtube.com →A practical six-step playbook mapping which AI tools cover which gap, discovery, prototyping, production, marketing, sales, for a founder flying solo.
Open aakashgupta.medium.com →An AI-native startup builds AI into how the company itself runs, not just the product, so that agents and automation do work that used to require whole departments, and every new hire is a generalist who multiplies output rather than a specialist who adds headcount. The results are startling: Gamma reached $100M in revenue with about 30 people, and a wave of one-to-three-person companies have hit millions in revenue or even acquisition. The emerging benchmark is 'more millions in revenue than employees', and it's changing how much money founders need to raise and how many people they need to hire.
The defining write-up of the tiny-teams movement, with real operating tactics from Gamma, Gumloop, Bolt.new, and other companies with more millions in ARR than employees.
Open latent.space →A YC partner's playbook for making AI the operating system of your company from day one, the clearest definition of 'AI-native' for early-stage founders.
Open youtube.com →The canonical tiny-team case study, told first-person by the co-founder: $100M ARR, 50M users, ~30 people, profitable.
Open youtube.com →Three named, verifiable solo founders, including Base44's $80M exit, showing the one-person, AI-scaled company is already real, not a prediction.
Open forbes.com →