DALL-E

Autonomy at the VP Level

Place decision autonomy at the VP layer — not the leaves, not the top — to maximize thinking without producing chaos.

Barrels-and-Ammunition Team Design

Staff each team from the gap, not from a fixed PM/EM/designer template

Break Into AI PM With a Prototype Portfolio

Build a foundation, then ship prototypes that pre-answer the hiring manager's core questions.

Centralized vs. Decentralized Org Choice

Pick your org model from your product strategy: speed (Amazon) or unified experience (Apple), and accept its cost.

Productivity4 steps

Chop-It-Up AI Collaboration Loop

Don't hand AI one giant spec — specify a little, review a little, repeat in tight loops.

Complement-the-Frontier Model Strategy

Don't rebuild foundation models — train small specialty models that attack their weaknesses in speed, cost, and niche tasks.

Productivity5 steps

Context Is All You Need Prompting

Treat the model as a brilliant stranger with zero context, and supply what a colleague would already know.

Leadership6 steps

Criticism Triage Under Public Controversy

Separate valid criticism from power-shift noise by going and being your own user.

Entrepreneurship4 steps

Dogfood-Driven Realism

Be the end user, use your product intensely daily, and never ship anything that isn't useful to you.

Innovation3 steps

Don't Default to the Chatbot: Choosing the Right AI Interface

Reject the intuitive AI copy; ask what problem your business actually needs solved.

Communication4 steps

Evals as Articulating Success

An eval is just a clear spec of ideal behavior — the shared language of AI product work

Communication4 steps

Explain-It-to-Prove-You-Understand-It

Force yourself and others to explain decisions; if you can't articulate it, you probably don't understand it.

Self-Mastery4 steps

Fall-On-Your-Face Taste Calibration

Deliberately push AI past its limits in a safe environment to build a gut feel for what it can do.

Fault-Tolerant User Interfaces

Design your UI to match the real hit-rate of your machine learning, not a fantasy of 100% accuracy.

Innovation3 steps

Finding High-Leverage AI Ideas

Give AI work a metric, run hackathons, and study what makes AI products feel magical.

Productivity5 steps

Flow-Preserving AI Assistance Design

Design AI suggestions around the user's flow state: no panel switches, no waiting, ephemeral by default

High Agency, High Urgency Hiring Filter

Hire for two traits only — people who see a problem and go, and people who go now.

High-Ceiling Market Test

Attack markets with a high ceiling and easy switching; incumbents win only where there's little left to build.

Innovation6 steps

Human-in-the-Loop Algorithm Design

Decide explicitly what the algorithm owns, what the human owns, and how the handoff works.

Knowledge-Work End-State Idea Generation

Pick an area of knowledge work and reason forward to its end state as AI matures — then build for that.

Mindset3 steps

Measure in Hundreds

If your unit of measurement is one hundred attempts, five failures means you have effectively tried zero times.

Innovation5 steps

Persona-Framing for AI Product Behavior

Pick a human metaphor for your AI, then derive its behavioral guardrails from that role

Marketing4 steps

Recall vs. Discovery Interface Split

Match interface density to user intent: dense grids for recall, low-density sound-rich feeds for discovery.

Innovation7 steps

Research-to-Product Graduation

Move an incubated moonshot from the research lab to a product team without killing it or trapping the researchers

Run Toward the Hard Use Cases

Don't disable high-stakes uses to avoid downside — engineer them to be great

Separating Change-Aversion from Real Problems in a Redesign

After a redesign, split 'upset because it changed' from 'upset because it's worse' before you react.

Innovation5 steps

Ship-to-Learn: The Emergent-Product Loop

When product properties are emergent, launching is how you discover them

Influence5 steps

Take Your Own Shoes Off

Empathy fails at the removal step, not the entry step — drop your agenda before entering theirs.

The 60/30/10 Portfolio Capacity Split

Allocate team capacity across incremental wins, operations, and audacious bets before priorities compete

The Better Tool, Same Problems Lens

Every model leap gets normalised within months — build for the boring future, not the euphoric one.

The Cannonball / Lead Bullet Portfolio

Allocate growth energy between a few fundamental rebuilds and many small experiments — by product stage.

The Constrained-Resource Headcount Test

When the bottleneck isn't people, each new hire is a net productivity loss unless they uplevel everyone.

The Galvanizing Activation Metric

The activation number's job is organizational momentum, not statistical precision.

Innovation3 steps

The IKEA Effect for AI Products: Leave Knobs and Levers

Don't automate everything away — give users enough control to feel ownership.

The Marginal User Method

Find the user on the cusp of converting, then go watch the worst-case version of them.

The Maximally Accelerated Question

A forcing question that separates critical path from what can wait

The Organ-Rejection Test for Innovation Teams

Three conditions that stop the core org from rejecting your new-bets team like a foreign body.

The Platform Encroachment Test

Build where the platform's mission says it will never go — the general layer is not yours to own.

The Proxy Goal Ladder

Every metric you chase is a proxy — climb the ladder to the mission before you optimise it.

Communication5 steps

The Teach-Me-Something-In-One-Minute Interview

A 60-second timed teaching exercise scored on completeness, complexity, and clarity

Strategy3 steps

The Three Flavors of AI Product Management

Map any AI PM role into one of three types to target the right skills and job.

Productivity4 steps

Think It, Build It, Ship It, Tweak It

Four product phases where spend rises stage by stage — so you must retire risk before the money starts.

Mindset3 steps

Three-Model Triangulation

Apply three different mental models to a problem; agreement across them sharply raises your odds of being right.

Two-Day Work-Test Hire

Bring finalists on-site for two days to do a real end-to-end project — it screens skill and fit at once.

Productivity5 steps

Two-Mode Prioritization for AI Products

Prioritize backward from model magic AND forward from customer needs

Self-Mastery3 steps

Waiting vs. Wandering: The IC PM Operating Model

Bring energy, wander into the unknown while others wait, and amplify signal with AI.