Living system · versioned · verified against current tools
The Engineering Workflow Library
How modern AI-native engineers actually work. Not tutorials — working practice: each workflow prescribes one good way, with real commands and config, the artifacts it produces, the pitfalls, and a dated changelog. Maintained like software: versioned, changelogged, and verified against current tool releases.
A workflow is a documented way of working with AI tooling in real engineering — the practice, not the product feature. (Claude Code also ships a feature named "workflows"; the Claude Code workflow covers it inside the practice.) Guides explain topics; workflows prescribe how to work, and every one produces something you can adopt this week.
The workflows
Working with Claude Code
Run a repo where the agent does the typing and you keep the judgment — CLAUDE.md, skills, hooks, subagents, worktrees, and the new dynamic workflows feature.
Shipping an Agent SDK agent
Build and ship a Claude Agent SDK agent end-to-end — from first query() to permissions, evals, and production deployment.
MCP integration
Model capabilities as MCP servers, test them, and ship them — the how-we-work layer on top of the MCP server guide.
Context engineering in the repo
Treat context as a budget: structure repos, docs, and memory so agents act well — practice layer of the context engineering guide.
Reviewing AI-written code
Diff discipline and verification steps that keep AI-generated changes honest — trust the process, not the model.
Eval-first development
Evals as the new tests: build the harness before the feature — practice layer of the LLM evaluation guide.
Kept current, visibly
A stale workflow is worse than none. Every page carries a last verified date — the day its commands were run against current tool versions — and a dated changelog of what changed and why. When a tool release invalidates a step, the page gets updated or visibly flagged, never left to rot silently. That maintenance discipline is what the membership funds.
Adopt the workflow, then learn the system underneath it.
The workflows are free and public. The aiArch curriculum teaches the engineering underneath them — agents, evals, context, and production architecture — on a platform that is itself a production agentic system. The build is the curriculum.
See how aiArch helps senior engineers become AI-native, or compare Professional Membership pricing.
Free sample — no signup · every claim cited · full curriculum is waitlist-only