Building with AI

AI is reshaping how software gets built, and managers need a working grasp of it — not just the theory, but the tools in their own hands. This section runs the full arc: the AI literacy every EM needs, what AI-assisted and AI-native engineering actually change in practice, and hands-on on-ramps to the tools themselves — Claude Code and BMAD. One of those on-ramps, LeaderOS, turns Claude Code into a second brain for the leadership job itself: a growing set of notes it keeps for you and thinks alongside you with, not just a coding helper. It closes on the hardest part, which is human: guiding a team through adoption without mandates, fear, or a quiet loss of rigor.

How it’s organized. Three tracks, take them in any order:

Foundations — understand the technology.
AI Literacy for EMs → How LLMs Work
AI-Assisted — use AI in the everyday dev workflow.
AI-Assisted Engineering → Claude Code 101 → LeaderOS
AI-Native — build with AI agents across the whole lifecycle.
AI-Native Engineering → BMAD 101

Running under all three is the people problem: Leading AI-Adopting Teams.

In this section

AI Literacy for EMsThe working mental model of modern AI tooling that every engineering manager needs — enough to make good calls, ask sharp questions, and not get sold a story. How LLMs WorkA curated path from two friendly intros to a full Stanford course — for when 'good enough to lead' isn't enough and you (or a curious engineer) want to really understand what's under the hood. AI-Assisted EngineeringCoding assistants and agents in the everyday dev workflow — what changes, what doesn't, and how to help your team get real leverage instead of faster slop. Claude Code 101A practical on-ramp for Claude Code — install it, point it at an existing repo with /init, and learn the handful of commands that matter on day one. LeaderOS: Your Second BrainTurn Claude Code into a durable thinking partner for the leadership job: how memory really works, the MCP servers worth connecting, and how to grow a folder of notes into a second brain that compounds. AI-Native EngineeringThe development lifecycle redesigned around human–AI collaboration — engineers directing and verifying agents across larger units of work, and what that demands of the team. BMAD 101A practical on-ramp for BMAD — install it into a project, meet the agent roles, and walk the planning-to-implementation flow that turns 'build me a thing' into a spec you can trust. Leading AI-Adopting TeamsChange management, trust, and team norms as your engineers adopt AI tools — moving the team forward without mandates, fear, or quiet erosion of craft.