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Build for the Current Model, Prototype for the Next

Elicit max capability from today's model while pre-building the products the next model will unlock

Clear-Goal Ambiguity Cut

Because general LLMs can do anything, a sharp key-user + problem + use-case triad is what rules approaches out

Strategy3 steps

Code Quality Doesn't Equal Product Success

Solve the real problem for real users; architecture and code quality are nearly orthogonal to success

Leadership4 steps

Conway's Law Reorg: Go Functional Before You Go AI

Restructure engineering into one functional org before expecting company-wide AI or technical depth

Deadlines as P-Zero

Have few deadlines, but make each one a P0 that nothing else can touch — and cut scope to hit it

Leadership4 steps

Drive AI Adoption By Using It Yourself On A Real Problem

Executives using the tool daily on their own real problems beats any top-down mandate or think-piece

Communication3 steps

Emotional Discovery: Feel Bad Like the Customer

On customer calls, dig until you feel the exact emotion the customer wants to avoid, then build to remove it

Growth Team as a Rigor Forcing Function

Hire a growth leader early — the second-order effect is that it exposes everything you haven't measured.

Influence4 steps

Interview as Discovery: Be the Solution to Their Burning Problem

Treat a job interview like product discovery — find the hiring manager's burning problem and position yourself as its solution

Mission-Above-Product Prioritization

Route every cross-org tradeoff through a single shared mission so decisions are fast and everyone stands behind them

Model Introspection Harness Repair

When an AI agent misbehaves, ask it why — its explanation reveals the harness gap to fix

Self-Mastery4 steps

Optimize for Learning: The Impedance-Match Career Test

Choose roles by where you'll learn most and whether the mission truly matches how humans are wired.

Question the Base Assumption Before Build-or-Buy

Before building OR buying a tool, ask whether the process needs to exist at all

Ride the AI Value Wave

Treat today's AI capability as the worst it will ever be and expand where it's most efficacious

Ship-in-Research-Preview Speed Loop

Cut idea-to-user time from months to a week by branding launches as previews and pre-wiring the launch chain

Entrepreneurship3 steps

Start Small, Don't Boil the Ocean

Narrow scope to the achievable thing in front of you, then build momentum on top of it

Systematized Creativity by Extremes

Build the most extreme version along one attribute, feel it, repeat in the opposite direction, then find where they meet

Systems-First Scaling (One to 100)

Once you have product-market fit, go slow to go fast: build the systems before you hyperscale.

Productivity4 steps

The 100%-or-Nothing Automation Rule

An automation that works 95% of the time isn't an automation — push it to 100% or don't rely on it

Productivity4 steps

The 10% Working-Version Rule

Have a testable working version by the time 10% of your time budget elapses, not at the halfway point

The AI Startup Moat: Data Flywheel + Crafted Workflow

Defensibility for AI apps comes from a proprietary data flywheel and a deeply crafted vertical workflow.

Marketing3 steps

The Double Triangle: PM as Go-To-Market Discipline

Sit the PM between two triangles — build (eng/product/design) and sell (sales/marketing/PM) — and originate the customer's language

Leadership6 steps

The Five PM Archetypes

Hire and compose product teams by five distinct thinking styles, not one generic ideal PM.

Strategy3 steps

The Middle-Manager Reporting Veto

Automatically say no to customization features that ease manager reporting at the cost of IC workflow

The Painful-Mistake Growth-Mindset Interview

Screen only for growth mindset by asking for the most painful mistake and what changed because of it.

Communication3 steps

The Say-Do-Said Loop

Say you'll do the thing, say you're doing it, say you did it — to align, adjust, and close the loop.

The Six-Month Autonomy Razor

If you're still telling a hire what to do six months in, you hired the wrong person.

Productivity3 steps

Three-Legged Model Evaluation

Judge a model-harness combo with heavy usage, a trusted five-person taste panel, and ~10 sharp evals