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Max Schoening: Why agency beats skills as AI flattens craft

Through Notion's prototyping playground, designers ship code in the terminal; the first 10% of every project is now free, exposing who has agency.

Max SchoeningguestLenny Rachitskyhost
May 2, 20261h 27mWatch on YouTube ↗

CHAPTERS

  1. Max Schoening’s “merged roles” perspective on the AI-era product team

    Lenny introduces Max’s unusual background across PM, design leadership, engineering, and founding, teeing up why he has a credible view on roles collapsing in the AI era. Max frames the conversation around how teams build products when prototyping and coding get dramatically easier.

  2. Notion’s origin story: moving AI interface design from Figma to an LLM-friendly code playground

    Max explains how Notion’s early AI work (especially chat interfaces) exposed the limits of static Figma mocks. Inspired by Bret Victor’s critique of static prototypes, they created a small “playground” codebase optimized for one-shot LLM edits to make prototyping feel like “chatting,” not “terminal fear.”

  3. How much designers/PMs are shipping—and why production deploys aren’t the point

    Lenny asks how much non-engineers ship today and where it’s heading. Max argues the value isn’t designers deploying code; it’s designing in the same medium that becomes the real product, while remaining wary of “vibe coding” that doesn’t improve reliability or quality.

  4. The strategic balance: coding vs. higher-level product thinking (agent loops over CSS tweaks)

    Max reframes the “should PMs/designers code?” debate: he cares less about shipping and more about understanding agentic systems. He’d prefer a PM/designer who can design “agent loops” over one who only tweaks UI via tools, because agent loops require working in the material—currently code.

  5. Agency: the core trait for thriving when skills are “on demand” via AI

    Max claims AI reduces “skill issue” excuses: even with skills at your fingertips, agency determines outcomes. People who see the world as malleable and who ignore rigid role definitions adapt faster than those clinging to what a PM/designer/engineer “is.”

  6. High-agency examples at Notion: ‘drive it like it’s stolen’

    Max shares concrete Notion examples where people reshape their job boundaries to create impact. He highlights recruiting, proactively filling organizational gaps, and leveling up from docs to prototypes as demonstrations of agency.

  7. What we risk losing as roles merge: specialists, craft, and ‘factory-grade’ engineering

    Lenny asks what’s lost when disciplines blend. Max warns that without care, teams may lose specialists and the rigor needed to scale reliably—likening today’s software discourse to celebrating prototypes while neglecting manufacturing-grade precision.

  8. How to develop agency: making, tinkering, and the realization that ‘you can just do things’

    Max’s advice is to start with making, not politicking inside org charts. Tinkering—whether software, furniture, or cooking—builds the muscle of changing reality, eventually creating the insight that the world is built by people no smarter than you.

  9. Malleable software: owning your computing life (and why AI makes it newly accessible)

    Max defines malleable software as tools serving users’ interests more than corporate constraints—like rearranging your living room rather than living in a fixed kitchen. AI helps people build personal tools, but Max argues the real win requires platforms designed for communal, adaptable software with modern collaboration and security.

  10. Design philosophy via Dieter Rams: usefulness before beauty, and why malleability exposes utility

    Lenny references a pinned Dieter Rams clip where Rams dismisses museum-like furniture as impractical. Max ties the humor and critique to a utilitarian design philosophy: great design is first useful, and the ability to tweak/adapt objects reveals whether they actually serve real life.

  11. The “SaaSpocalypse” debate: SaaS won’t vanish, but tools will become more general and agent-friendly

    Max argues the ‘apocalypse’ is overstated: people don’t want to maintain software stacks, and “as-a-service” primarily buys maintenance and specialists. AI may push a return to more general-purpose tools (’90s-style), while still leaving room for specialized products with deep domain rigor.

  12. How product building changed: ‘the first 10% is free,’ demos over memos, and iteration as default

    Max says AI makes early execution almost effortless: prototypes and “janky demos” replace heavy PRDs, enabling rapid parallel exploration. Teams can now send many agent-driven experiments and converge based on concrete artifacts rather than documents.

  13. What’s next: modality, speed, and the ROI era (token spend, verifiability loops, and cheaper models)

    Max explores near-future shifts: whether direct manipulation returns as inference becomes instant, and whether “good enough” intelligence will matter more than frontier smarts for most work. He anticipates rising scrutiny on ROI and a move toward smaller/cheaper models or in-house approaches if the frontier gap doesn’t widen.

  14. Shipping fast without losing quality: ‘shots on goal,’ consolidation, and building ‘obviously good’ products

    Max describes how mature companies become precious and risk-averse, so leaders must push for more attempts while staying focused on quality. He emphasizes iterative correctness, consolidating divergent “automation primitives,” and aiming for products that are unmistakably great rather than bloated with features.

  15. Taste, product superpowers, and closing corners: jobs-to-be-done, UBI hot take, AGI plans, contrarian/failure lessons

    Max defines taste as a predictive mental model shaped by repetition and feedback, then zooms out to what makes products win: a tiny “superpower core.” He also covers jobs-to-be-done as a user-honesty check, his provocative view on UBI, what he’d do with AGI, and lessons from failures and contrarian views on exclusivity.

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