Don’t just use agents.
Lead their adoption.
A hands-on curriculum for becoming the person who can explain, evaluate, improve, secure, and deploy AI coding systems across an engineering organization.
behavior
quality
infrastructure
in public
90 days, three acts
Each act ends with something demonstrable—not merely notes. Select a week to see its objectives, mental models, build brief, and proof of mastery.
Eight connected pillars
No topic lives alone. Click a pillar to explore the key ideas, why leaders care, failure modes, and a concrete practice exercise.
Build intuition, not flashcards
Tune the variables. Watch the system change. Then explain the trade-off in your own words.
Compare systems by mechanism
Product lists age quickly. Durable understanding comes from comparing planning, editing, tools, recovery, memory, and review.
Ship the platform in slices
An AI Engineering Platform for Frontend Teams. Every slice earns evidence that compounds into an adoption playbook.
Learn → build → measure → publish → reflect
Your proof is the product.
Not “I completed a course.” Instead: a working platform, a reproducible eval suite, public technical writing, shipped developer tools, and an adoption plan grounded in evidence.