learning paths

A quarterly-refresh playbook container for builders who already finished Foundations and now need tactical depth on what actually shipped this quarter. This path is for the velocity-anxious operator saying: "I know the basics; show me the medium-to-advanced build moves, the new tooling, and what to do this week." Work through capability-by-capability build-alongs to keep your judgment current as the frontier shifts.

A 2026-era curriculum for PMs and product builders who need to design, ship, and judge AI-powered products — built around the twelve-chapter AI Manual spine. Decide whether AI is the right answer, pick the smallest model that clears the bar, spec the prompt, gate on evals, design for uncertainty, and own cost, latency, and safety as first-class product constraints.

A seven-week path for engineers, ML practitioners, and technical founders who can build the AI feature but now have to make the product call. Learn to choose the right problem, pick the smallest model that clears the bar, write the prompt like a spec, evaluate against user value, and brief leadership on cost, latency, and safety in plain English.

A four-week path for functional leaders who now own an AI-touched surface and need to brief a board, a CEO, or a customer without slipping into either hype or paralysis. It is built for the operator who will not pick the model or write the prompt, but will absolutely own the strategic frame, the economics story, the safety posture, and the few irreversible calls underneath them.

A six-week path for designers now owning AI surfaces, where deterministic interaction instincts are no longer enough. It gives you a practical vocabulary for uncertainty, a pattern library for streaming/citations/confidence/recovery, and a way to design for hallucination as a permanent product condition. Built for teams who need to ship trustworthy AI UX without waiting to become ML experts.

A nine-stage journey for senior practitioners stepping into VP and CPO roles — and for any operator making product decisions at scale.

The next eighteen months of product surface area is being shaped by what's possible with multi-agent autonomy, not by what's possible in a single prompt. This path teaches the vocabulary, the failure modes, and the operating discipline behind agent loops, eval harnesses, tools, memory, multi-agent orchestration, and production runtime — so you can spec a system that doesn't fall over at hour six.

A four-week path for mid-to-senior PMs targeting FAANG, unicorns, and Series C+ companies — structured answers, worked examples, and real practice reps.

For anyone whiplashed by influencer cycles and unsure what to learn next. This path builds the metacognition and epistemic-hygiene skills that let you pick the compounding AI skills and ignore the churn — and it gives you a personal learning operating system that holds up across every model cycle.

A six-week sprint for founders, solopreneurs, and indie hackers who need to ship a real AI feature fast, not talk about one. The path moves from customer pain to model choice, prompt spec, evals, and failure-tolerant UX so you can launch this week and learn from live users instead of demos.

A six-week path for PMs and CSMs stepping into B2B roles where they own retention, expansion, and the customer relationship alongside the product.