GitHub Copilot

Adapt the Model, Don't Build One

Post-training is the new pre-training — steer an off-the-shelf model to your outcome instead of pre-training your own

Mindset4 steps

Agency Over Title: The Force-Multiplier Mindset

Ignore role boundaries — use AI tools to execute your own ideas end to end

AI as Your Learning Engine

Stop only asking AI to do work for you — spend your spare hours making it train you

Innovation6 steps

Alpha Co-Creation Loop

Pick the users who are already pushing the boundary, build with them in a shared channel, ship only when they're thrilled.

Strategy2 steps

Benefit = (Volume × Quality) / Time

Measure AI-building impact as experimentation volume times quality, divided by time to launch

Build Infrastructure, Not Features

Ask 'what has to be true so anyone could build this in an hour?' and build that instead.

Build Only Where You Can Be Best (Model Sourcing)

Build in-house only where your unique data or position lets you beat the frontier; otherwise buy

Peak Performance3 steps

Calories Per Hour: Intensity Over Hours

Get more done per minute instead of working more minutes, then go home.

Cannibalize Your Own Product Every 6-12 Months

Make your current product look silly on a fixed cadence instead of only shipping what users ask for

Leadership3 steps

Champion-Led Agent Adoption

Roll out new AI tooling by letting a few excited early adopters pave the way for the team.

Choose the Hard Path

When choosing between options, pick the harder one because it wins whether or not it works out.

Self-Mastery5 steps

Choose Your Abstraction Layer Deliberately

Delegate the work you don't enjoy to a higher abstraction; keep the parts that make you good and happy.

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.

Connect-Users-to-Value Journey Staffing

Growth's job is to connect users to your product's value — so staff teams around each stage of the user journey.

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.

Context Loading (Additional Information)

Front-load all relevant task information — and put it at the top for caching

Criticism Triage Under Public Controversy

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

Communication4 steps

Design For Tomorrow's Majority, Not The Vocal Minority

Optimize for the far larger future user base, then manage the unhappy few with authentic listening.

Determinate vs Indeterminate Optimism (Betting Under Deep Uncertainty)

Founders need one specific plan; allocators need many bets and a discount on their own forecasts

Differentiate Above The Model, Not Around Its Gaps

Build your moat outside the LLM so your product gets better as the models get better.

Entrepreneurship4 steps

Dogfood-Driven Realism

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

Mindset2 steps

Don't Wait for the Re-Org

If you're waiting for a formal declaration to build differently, you're already too late

Entrepreneurship4 steps

Do The Five Fundamentals Harder

Startup success isn't secret knowledge — it's executing the well-known basics far past normal effort.

Driving AI Adoption Through Hard Constraints

AI transformation moves when you impose hard constraints, sort people into three groups, and fix the slowest part of the system.

Leadership3 steps

Earn The Next Role By Driving Impact In This One

Stop eyeing the next promotion; be judged on impact delivered in the job you already hold.

Ensembling (Mixture of Reasoning Experts)

Solve the same problem several ways and take the most common answer

Existing-User Retention & Resurrection Priority

As a consumer subscription matures, the biggest lever isn't new users — it's current-user retention and resurrecting the dormant.

Explore & Exploit at the Insight Level

Oscillate between finding the right mountain and climbing it — but do it insight by insight, not just at strategy level.

Extract the Chain-of-Thought, Not the Recommendation

Treat every advisor as an LLM: mine their reasoning, not their verdict, because their answer is trained on a different corpus.

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.

Fast-Thinking / Slow-Thinking Org Split

Split product org into a weekly-shipping AI group and a deliberate-infrastructure group so both speeds coexist.

Few-Shot Prompting

Show the model examples of what good looks like instead of describing it

Productivity5 steps

Flow-Preserving AI Assistance Design

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

Self-Mastery5 steps

Follow People, Not Plans

Choose jobs by who you'll learn from, not by a five-year plan or a financial bet.

Marketing5 steps

Four Criteria for Choosing a Distribution Platform (Enter and Exit)

Score a new platform on retention, monetizability, value exchange, and scale — then plan your exit before you enter.

Productivity6 steps

Friction Logging

Adopt a specific user's identity, walk your own product end-to-end, and log every point of friction.

Friction Smells: Signs Your Team Can Move Faster

The tell-tale signals that friction, not capability, is capping your team's speed

From Brick Layer To Architect

Reclaim the 10% of high-leverage architecture work by delegating the 90% of implementation to AI.

Marketing3 steps

Full-Value Free Sampling (Reverse Free Trial)

Make your free product a live, rationed taste of everything paid can do — not a walled-off basic tier.

Gamification's Three Pillars: Core Loop, Metagame, Profile

Durable habit-forming products stand on three legs: a tight core loop, a long-horizon metagame, and an accumulating profile.

Give It Your Hardest Task

Evaluate a serious AI tool on your gnarliest real problem, not a dumbed-down toy.

Innovation2 steps

Golden Samples Over Full Corpus

Curate a small set of gold examples for your AI, don't dump your whole knowledge base on it

Greedy-but-Smart Compute Allocation

Throw hundreds of dollars of inference at high-value problems — the value-to-cost ratio is absurd in your favor.

Group UX Review and Walking the Store

Taste the soup together — experience the product as a group, log issues live, then debate each one.

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.

Hills-and-Valleys: Getting Value From Probabilistic AI Tools

Be patient and explicit, start small, and learn where the model is strong vs weak

Hire for Autonomy: References, Real Work, and Default Trust

You'll be in none of the decisions that matter — so hire people you can hand autonomy to, and verify via references.

Innovation6 steps

Human-in-the-Loop Algorithm Design

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

Productivity6 steps

Internal Tools as a Product (The Crying Octopus)

Run your dev-productivity team like a product team: monthly surveys, hard metrics, and one-click paper cuts.

Entrepreneurship4 steps

Irrationally Optimistic, Uncompromisingly Realistic

Push hard toward a future you believe in while killing your own hypotheses as data arrives

Job Trials Over Interviews

Interviews don't predict performance; make the interview as close to the real job as possible.

Communication3 steps

Kind and Candid

Reframe candor as an act of kindness so you actually deliver the hard message.

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.

Marketing3 steps

Lean-Into-Organic-Sharing Virality

Don't manufacture virality — instrument where users already share, then make those exact moments 5-10x more delightful.

Live in the Future, But Not Too Far

Hold the far-future vision, but land with users where they already work today.

Measure in Hundreds

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

Meeting Armageddon

Once a year, delete every recurring meeting and forbid new ones for two weeks.

Merge With the Unreasonable

Don't try to become a visionary; find one and connect your APIs to theirs.

Mixed-Initiative Contextual Assistance

Surface AI help at the moment it's relevant instead of interrupting with notifications.

NLX: Designing the Natural-Language Interface

Conversation is an interface with real constructs — design it, don't just let the model lead

Pair Programming as a Management Tool

Two people on one computer isn't half the code, it's the fastest path to the right code.

Innovation5 steps

Persona-Framing for AI Product Behavior

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

Planning in Seasons

Replace rigid roadmaps with secular 'seasons', loose quarterly OKRs, and deliberate slack

Platform Betting Strategy by Company Stage

Late-stage companies spread chips across platforms; startups make one focused bet and go all in.

Play-First AI Fluency

Build real AI intuition by playing — invent fun side projects, use everything, and share the artifact not the doc.

Prescriptive vs. Framework Metrics

Know whether your metric is a recipe or a lens — and never misuse a recipe

Prime-Then-Parallelize AI Coding Workflow

Front-load the architecture, fan out to agents, then step back and evaluate

Problem-First AI Adoption

Start from the customer problem and ask where AI helps — never from 'what do we do with AI?'

Innovation5 steps

Product as Organism: the metabolic loop

Treat an AI product as a living system that ingests signals, tunes on rewards, and improves with every interaction

Prompt Decomposition

Make the model list the sub-problems first, then solve each before the whole

Prompt Injection Defense Stack

Stop trying to fix injection with prompts and guardrails — mitigate at the model level

Prompt Sets Are the New PRD

Communicate product ideas by building the prototype, not writing the doc — demos before memos

Communication5 steps

Reframe Metrics to Leadership's Language

Pick two or three metrics that speak the exact word your leaders keep repeating

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

Self-Criticism Loop

Get the model to critique its own answer, then implement its own critique

Strategy6 steps

Ship Fast Without Breaking Money

Reject the reliability/velocity trade-off: automated gauntlet, ramped exposure, and remediations ahead of roadmap.

Solve Before Scale

Run in a distinct 'solve' mode before you ever switch to 'scale' mode

Stickiness Over Moats

Stop chasing barriers competitors can't cross; build accumulating value they can't easily replace.

Take People With You Before You Fix Anything

A new leader's toolbox is worthless until the team agrees a problem exists — build the why first.

Influence5 steps

Take Your Own Shoes Off

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

Task Loss, Not Job Loss

Your job won't vanish — analyze it as a bundle of tasks and keep swapping the tasks AI absorbs

Tasks, Not Problems

Delegate to AI agents by handing them scoped, verifiable tasks — never open-ended problems.

The 1,000-Experiments 'What Would Need To Be True' Goal

Set an audacious experiment-volume goal — not to hit it, but to force the conversations that unlock a whole experimentation culture.

The 60/30/10 Portfolio Capacity Split

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

The Agent Foothold Onboarding

Onboard an AI agent like a new hire: environment first, easy tasks next, then scale.

Mindset4 steps

The Barbell Media Diet

Read only the up-to-the-minute and the timeless — distrust everything in the middle

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 Cold-Pattern Positivity Flip

Find the moments where users feel bad, and flip the product to reinforce progress instead of failure.

The Constrained-Resource Headcount Test

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

The Dehydrated Company Hiring Model

Only hire when a function is underwater, so headcount forces ruthless prioritization

The DevX Listening Tour

Before you build a tool, walk developers through their yesterday

The DORA Four Keys

Measure software delivery with two speed and two stability metrics that move in tandem.

The Engineer-cation

Leaders clear 3-4 days, join a team as an IC, ship one small feature to production, and log the friction.

The Enterprise AI Adoption Ladder

Three sequential stages that separate companies winning with AI from those spinning their wheels

Leadership2 steps

The Five Traits to Keep, Automate the Rest

Protect where humans shine — vision, empathy, communication, creativity, judgment — and automate everything else

The Four-Box Framework

Write your hypothesis in words before you touch data, so you can debug the idea and the measurement separately.

The Four-Step Distribution Platform Cycle

Every new growth channel opens then closes in the same four predictable steps — learn to see where you are.

Leadership7 steps

The Frictionless Seven-Step DevX Program

A start-anywhere playbook to stand up a developer-experience initiative

The Full-Stack Builder Model

Empower one builder to take an idea to market end-to-end, regardless of role or team

The Full-Stack Role Collapse

In the AI era every role needs a minimum baseline in the adjacent two — deep in one, dangerous in the rest.

The Galvanizing Activation Metric

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

Innovation6 steps

The Horizon-3 Research Team That Ships

Fund a 3-5 year research team, then bolt it to product so ideas actually reach production.

The Input-Metrics Stack for Developer Productivity

No single metric rules them all — combine per-component input metrics that ladder up to time-to-value.

Strategy6 steps

The Inverted W Planning Process

Teams propose, leaders synthesise, teams adjust, leaders resynthesise, orgs distribute with context.

The Marginal User Method

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

The Measurement Journey

Start measuring from words and people, then scale into system data — don't wait for perfect.

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 Parallel Agent Workflow

Run several AI agents at once and insert yourself only where your expertise actually matters.

Self-Mastery3 steps

The Personal Values Framework for Career Decisions

Write down what you actually care about, then reject anything that violates it, no matter how shiny.

The Platform Encroachment Test

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

The PM-Engineering Alignment Operating System

Run product and engineering as one leadership unit with clear ownership and async, iterated reviews.

The Proxy Goal Ladder

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

The Refounding Test

Ask how you'd rebuild AI-native from scratch — then decide whether your legacy asset helps or you should sell.

The Six-Week Review Operating Cadence

Short, frequent check-ins where leaders pair on problems, not catch you slacking, create velocity.

The SPACE Framework

Pick balanced developer productivity metrics across five dimensions — never rely on one.

The Superpowered Individual (Combination-of-Skills Career Moat)

Go deep in one craft, then use AI to add adjacent crafts until you become un-replaceable

Communication5 steps

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

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

The Teammate Onboarding Model for AI Agents

Adopt a coding agent the way you'd onboard a new intern — pair first, then delegate.

The Three Dimensions of an Agent

Score any 'agent' on autonomy, complexity, and natural interaction — each a spectrum

Productivity5 steps

The Top-Three Weighted DevX Survey

Force a top-three, weight by frequency, and never ask four questions at once

The Two-of-Three Inflection Test

Only build a new zero-to-one product when at least two of three inflections line up

Self-Mastery5 steps

The Weighted Decision Spreadsheet

List your options, weight your criteria to 100%, score and multiply — then let the reaction tell you the answer.

Innovation5 steps

The Zero-Ask Assistant (Copilot Design Philosophy)

If the user has to ask for it or wait for it, they won't adopt it — build assistance that infers.

Throwaway Prototyping To Discover The Product

Build disposable prototypes on real data to feel what works before writing any production code.

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.

Unblock the Review Bottleneck

The limiting factor on AI productivity is human review speed — engineer the agent to validate its own work.

Mindset4 steps

Update Your Priors: The AI Capability Arbitrage

Re-test what AI can do today and demand more of it — old scar tissue is leaving alpha on the table

Use AI As Leverage On Your PM Time

Assign the model a role, feed it more context than you could read, and iterate the prompt until it works.

Vibes Before Evals

For a genuinely new AI feature, start with open-ended vibes testing; add evals only once the use-case cluster is clear.

Win on the Platform, Not the Features

Durable products win on invisible infrastructure — reliability, reach, privacy — not on the feature list