Text courseintermediate47 min5 chaptersEnglish
Coding With AI: A Working Developer's Guide
A written course in five chapters for developers working in real codebases, not blank files. Where these tools genuinely help, why context decides answer quality, how to review code you did not write, how to debug and test with them, and where agentic autonomy breaks.
Instructor: HIMEXA Editorial
What you'll learn
- Tell apart the coding tasks where AI saves time from the ones where it costs time
- Assemble context that produces correct answers instead of plausible ones
- Review generated code against the mistakes models specifically make
- Debug by asking for ranked hypotheses, and generate tests that would actually fail
- Scope agentic tasks so the diff stays reviewable
Chapters
Read in order, or jump to the chapter you need. Nothing is locked — this course is free to read.
- Where AI Actually Helps in a Codebase9 min readThe gap between the demo and your Tuesday afternoon. What these tools are genuinely good at, and the categories where they reliably waste your time.
- Context Is the Whole Game10 min readAlmost every disappointing answer is a context problem, not a model problem. What to include, what to leave out, and why more is not better.
- Reviewing Code You Did Not Write9 min readGenerated code fails differently from human code. A review pass targeted at the mistakes models actually make.
- Debugging and Tests9 min readDebugging is where context discipline pays off most, and tests are where generated code is most immediately useful. Both have a specific failure mode.
- Agents, Autonomy and Where They Break10 min readTools that run commands and edit files across a repo change the risk profile. Where multi-step autonomy earns its keep, and where it quietly makes a mess.
Requirements
- You write code professionally or are working in an existing codebase
- Access to any AI coding assistant — the principles are tool-agnostic