The core claim
Most engineering-minded users are stuck on one gap: “using AI” is not the same as “using AI correctly”. Treating the chat box as a souped-up search engine and the coding agent as a clairvoyant autocomplete gives you fluctuating output quality, runaway context, silent errors born of blind trust, and a personalized experience nobody on the team can reproduce. The stance: modern AI tools are engineering systems that can be configured, constrained, and automated, and configuration itself is the leverage. The same model, with or withoutCLAUDE.md, Skills, Hooks, and correct privacy settings, produces output that differs by orders of magnitude. This training pulls that “configuration and mental model” layer into the open.
The primary reference is the Anthropic Claude family (Claude.ai, Claude Cowork, Claude Code), covered in depth; other tools (OpenAI, Google, GitHub Copilot, Cursor) appear as comparisons. Tool-configuration details were verified as of 2026-05; every fast-moving item is marked with its source and as-of date.
Four learning dimensions
The dimensions are not linear. Part III (judgment) runs through all of it: on a first pass, read I → II → III → IV, but in practice, every time you learn a setting, return to III and ask “is this actually useful to me?”How to read: three routes
Different partners start from different places, so here are three reading routes.Route A: by dimension, in order (default, for systematic learning)01-1 → 01-2 → … → Part II → Part III → Part IV. Build the full mental model first, then start configuring.
Route B: by tool (for “I only use one tool”)Read 02-1 (the layer model) first to build a general frame, then jump to 02-2 (if you use Claude) or the 02-6 comparison table to find your tool, then fill in 03-3 (security and privacy) and 04-2 (writing rule files).
Route C: by pain point (for those already using it, wanting to fix something specific)“Unstable output” → 01-4 + 04-1; “not sure whether to install a Skill” → 03-1 + 03-2; “worried about data leakage” → 03-3 + Appendix B; “want to automate a repetitive flow” → 04-4 + 04-6.
Content map
Part I: Foundations
- 01-1 Why use AI tools “correctly”
- 01-2 How LLMs and agents work
- 01-3 Prompt engineering
- 01-4 Context engineering
- 01-5 Workflow engineering
- 01-6 Harness engineering
- 01-7 The 2026 AI tool landscape