Practical AI tips for software engineers, in the order they were published. Tips often build on earlier ones — start from the beginning or jump to a category.
Set up an instruction file so the agent knows your conventions from the start.
When Copilot gets something wrong, add it to your instructions instead of just fixing it.
Think together before writing code — use plan mode to explore approach and tradeoffs.
Don’t Google cryptic errors. Paste them into chat and ask for the explanation first.
Less is more: hand-written, non-obvious rules beat auto-generated descriptions.
Copilot CLI brings agentic coding to your terminal — reads files, runs commands, makes changes.
Set up branch rulesets so Copilot reviews pull requests without anyone asking.
Package step-by-step procedures as SKILL.md files the agent loads on demand.
Project skills vs. personal skills, and how the agent discovers them.
The agent often ignores skills unless you tell it to look for them first.
Built-in tools for file editing, search, shell commands, and GitHub — no setup needed.
One open standard for connecting agents to external systems across all tools.
Chrome DevTools MCP lets the agent click, inspect, and test web UIs from your terminal.
gh, git, jq, curl work without MCP — the agent just calls –help.
Every connected server costs tokens every turn. Be selective.
Use the agent as a research assistant to understand unfamiliar code before changing anything.
One task per session. Context fills up — fresh starts beat accumulated corrections.
Git stash or commit first, so the agent’s changes are always one git diff away from a clean state.
Open a second session to re-ask the same question without baggage from earlier attempts.
Use isolated workspaces so multiple agents can work on the same repo without stepping on each other.
A provider-agnostic coding agent that works with your existing Copilot license and 75+ other providers.
Deterministic tasks deserve deterministic scripts — not AI improvisation every session.
Script output goes straight into the agent’s context window. Design it to say what happened and what to do next — not just what ran.
Hooks are shell commands that fire automatically at agent lifecycle points — before/after a tool runs, on session start, on finish. Unlike instruction files, they’re deterministic. Enforce your venv rule, run tests after edits, get a desktop notification when the agent is done.
Less syntax, more architecture. Less typing, more judgment. AI rewards good engineering — but only if you stay sharp.
The Clinejection attack showed how a malicious PR description can hijack an AI agent with CI/CD access. Know the risk before you automate.