Workflow Patterns

Think together before writing code — use plan mode to explore approach and tradeoffs.

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.

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.

Clone related repos into one parent folder, add an AGENTS.md, and start your agent there. It lazy-loads on demand — cross-system understanding with no extra token cost.

Tell the agent to run tests, type checkers, and linters after changes. Without verification tools, you’re the only feedback loop.

Before a big change, ask the agent for the plan as HTML and open it in your browser.

Voice dictation isn’t for dictating code — it’s for the prose around code that agents need. Speaking is 3× faster than typing, and the reduced friction produces richer prompts.

AI coding tools ship weekly. Spend 10 minutes scanning your tool’s changelog — the compound effect of knowing what’s available before you need it is enormous.