AI PM Sprint · 28 days · ~10 min/day
10 minutes a day for 4 weeks. The fast lane to AI Product Management.
Couch-to-5K, but for AI PM. A curated on-ramp built for time-strapped professionals — pick a daily ritual, compound for four weeks, and ship a public artifact at the end.
No payment. Free with sign-up. You can switch tracks any time.
Why a sprint
Three forces, compounding daily.
Most courses fail because life gets in the way. The Sprint is engineered around the three things that actually move the needle for working PMs.
🕒 Daily ritual
One ~10-minute task. Same time, same place. Ship before standup. Designed to survive a full calendar.
🏗 Weekly capstone
Four themed arcs — Discover, Define, Build, Deploy. Each week ends with a small artifact you'd actually use at work.
📣 Public pledge
Commit publicly on Day 1, demo publicly on Day 28. The asymmetry of social commitment beats willpower every time.
The 4 weeks
Discover → Define → Build → Deploy.
The same arc you'd run on a real AI product launch — compressed into four weeks. Click any day to preview.
Week 1 Discover Get the lay of the AI land — models, capabilities, tradeoffs.
Day 02
Understand how language models process text
Understand how language models process text — the foundation of every AI product decision.
Day 01
A reference map of every major model family
A reference map of every major model family — proprietary APIs, open-weight, and specialized — and how to think about cost, capability, and tradeoffs.
Day 06
Reasoning models change the product calculus
Reasoning models change the product calculus — learn when to pay the premium and when it backfires.
Day 07
AI is no longer text-only
AI is no longer text-only — learn where vision, voice, and video create the highest-value product opportunities.
Day 04
Know the product you’re building on
Know the product you’re building on — Claude’s current capabilities, strategic positioning, and the full product surface.
Day 05
Understand OpenAI’s model strategy to compete, partner, and benchmark effectively.
Day 31
The metrics that matter for AI products
The metrics that matter for AI products — beyond accuracy, into business outcomes.
Week 2 Define Scope AI features, write the PRD, frame eval and risk.
Day 32
How to write an AI product strategy that engineers respect and executives fund.
Day 35
How to roadmap an AI product when capability changes every 90 days.
Day 18
You can’t improve what you don’t measure
You can’t improve what you don’t measure — build the evaluation infrastructure every AI product needs.
Day 14
When to adapt a model vs when to prompt better
When to adapt a model vs when to prompt better — the decision tree now includes open-weight alternatives.
Day 19
Anthropic’s commitment to slow down before AI becomes dangerous
Anthropic’s commitment to slow down before AI becomes dangerous — and why that commitment sells to enterprise buyers.
Day 41
Understand the layered safety stack that makes Claude a responsible enterprise choice.
Day 37
How to price AI products when open-source creates a zero-cost floor.
Week 3 Build Lightest hands-on — APIs, tools, RAG, Claude Code, evals.
Day 09
The API your products will be built on
The API your products will be built on — understand every parameter, plus the cost-saving features most teams miss.
Day 10
The dominant API in the ecosystem
The dominant API in the ecosystem — understand it deeply to compare, compete, and build.
Day 11
The mechanism behind every AI agent
The mechanism behind every AI agent — how models call functions and act on results.
Day 13
The most-deployed AI architecture
The most-deployed AI architecture — build the retrieval layer that makes models know your data.
Day 43
Claude Code is GA
Claude Code is GA — the agentic coding tool that turns Claude into a software engineering partner.
Day 44
Map the AI code assistant landscape
Map the AI code assistant landscape — GitHub Copilot, Cursor, Windsurf, and the battle for developer workflows.
Day 53
Master automated red-teaming tools and build the eval pipeline that catches failures before users do.
Week 4 Deploy Launch, measure, observe, comply — and ship the capstone.
Day 38
Launch strategies for AI products
Launch strategies for AI products — from developer beta to enterprise GA.
Day 52
Set goals that actually drive AI product quality
Set goals that actually drive AI product quality — from eval hygiene to agentic success metrics.
Day 24
You can’t debug what you can’t see
You can’t debug what you can’t see — build the observability stack for production AI.
Day 17
LLM inference is expensive at scale
LLM inference is expensive at scale — the 5 levers that cut costs, starting with the one most teams miss.
Day 49
The regulatory landscape is live
The regulatory landscape is live — EU AI Act enforcement has begun, US policy is shifting.
Day 45
How enterprises actually deploy Claude
How enterprises actually deploy Claude — Azure AI Foundry, AWS Bedrock, and data-in-perimeter architectures.
Day 60
Close the course, lock in your gains, and launch your AI PM career
Close the course, lock in your gains, and launch your AI PM career — starting today.
Day 28 · Graduation
Ship a public AI PM artifact and graduate.
On Day 28 you'll demo a public artifact — a PRD, an eval suite, a working prototype, a teardown — and earn a graduation badge. Pledge on Day 1, ship on Day 28.
Take the pledge →FAQ
Questions, answered.
How is this different from the 60-day course?
The Sprint is 28 of the 60 days — a curated on-ramp covering the
highest-leverage topics for working PMs. Same content, smaller scope.
You can switch to the full 60-day track any time.
Can I switch tracks?
Yes — there's a "Sprint mode" pill in the course sidebar. Toggle it on
to see only the 28 sprint days; toggle off to see all 60.
What if I miss a day?
Nothing breaks. Streaks tolerate one rest day per week, and every day
is self-contained. Pick up where you left off.
What do I demo on Day 28?
Anything public and real: a PRD for an AI feature you'd actually
ship, an eval suite for a prompt, a teardown of a competitor's AI
product, or a working prototype. We share examples on Day 27.
Do I need to code?
Light hands-on in Week 3 (APIs, RAG, evals) — but no engineering
background required. If you can read JSON, you're set.