AI for Coders

Professional software developers who already know how to code

Use Copilot, Cursor, Claude Code and ChatGPT like a senior engineer does: prompt for real constraints, review generated code like a junior's PR, debug unfamiliar systems with AI as a reasoning partner, and avoid the traps that quietly erode your own skill and your codebase's integrity.

What you'll be able to do

Write prompts that produce code you can actually merge, not a plausible first draft
Review AI-generated code for hallucinated APIs, subtle bugs, and security smells before they ship
Use AI to understand and debug unfamiliar codebases faster, without outsourcing the understanding itself
Know which refactors and review tasks are safe to delegate and which need your own judgement
Spot license and provenance risk in generated code before it becomes a legal problem
Build habits that keep you sharper over time instead of slowly de-skilling you

Modules in this track

1. Prompting for code: why 'just write it' fails

The gap between a toy example and your actual codebase, and the context a prompt needs to close it.

7 min read

2. Reviewing AI-generated code like a junior's PR

Hallucinated APIs, subtle logic bugs, and security smells — the three things a shallow read will not catch, and how to look for them anyway.

8 min read

3. Debugging and unfamiliar code: AI as reasoning partner, not oracle

Using AI to speed up understanding a codebase or tracking down a bug, without letting it hand you a confident wrong answer you accept because you're tired.

7 min read

4. AI in code review and refactoring: strong where it's mechanical

Where AI review tools genuinely catch what humans miss, where they miss what matters most, and how to use AI for refactors without losing architectural control.

7 min read

5. The traps: atrophy, over-trust, and provenance risk

Skill atrophy, confidently-wrong answers, license and IP exposure in generated code, and the habits that keep AI a genuine multiplier rather than a slow liability.

7 min read