See Also
In This Guide
- AI Roles & Career Paths: Map of emerging AI roles (Prompt Engineer → Harness Engineer) with career matrix and salary benchmarks
- Methodologies: TDD with Claude: Write tests first, then implement
- Workflows: Spec-First: Understand requirements before code
- Workflows: Plan-Driven: Use /plan mode for complex work
- Ultimate Guide: Mental Models: How to think about Claude interactions
Templates & Examples
- Learning Mode CLAUDE.md: Configuration template
- /learn:quiz Command: Self-testing slash command
- /learn:teach Command: Step-by-step concept explanations
- /learn:alternatives Command: Compare different approaches
- Learning Capture Hook: Automated insight logging
External Resources
- Anthropic Prompt Engineering Guide: Better prompts = better learning
- The Pragmatic Programmer: Timeless principles for deliberate practice
- AI for Engineers: AI fundamentals (ML, transformers, tokenization)
- Step by Token: 21-chapter interactive guide explaining how LLMs work mechanically, from tokenization through agents and KV cache. Free, in 8 languages. Pairs well with the prompt engineering and agents sections of this guide.
- How to Build an Agent (Thorsten Ball, Amp), builds a minimal coding agent from scratch in ~300 lines: chat loop, tool definitions, agentic loop. The most-cited walkthrough of the same mechanism documented in Architecture: The Master Loop, useful for readers who learn a mechanism better by building a toy version of it first.