AI coding tools are now part of the daily workflow in most teams. They make strong developers much faster and make weak fundamentals much more visible. The skill that matters is no longer typing code; it is knowing what good code looks like, giving the tool the right context, and catching its mistakes.
Use AI as a tutor, not a ghostwriter: attempt first, then ask for review, explanations, and edge cases. Never paste code you can't explain.
Claude Code, Cursor, and GitHub Copilot: giving context (rules files, relevant files, types), breaking work into small tasks, planning before coding, and iterating with tests.
The most valuable AI-era skill. Check for security holes, missing accessibility, outdated APIs, invented functions, duplicated logic, and over-engineering.
Streaming chat UIs, handling partial and failed responses, structured output, tool calling, and SDKs like the Vercel AI SDK. Know what LLMs are good and bad at.
How coding agents plan and use tools, the Model Context Protocol for connecting tools and data, and reusable skills/instructions for your team.
You use AI tools to move faster while staying fully in control of the code you ship.
Stage project
Add an AI feature to one of your apps (for example 'summarise this', smart search, or a support chat) and document how you built it with AI tools.
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