How do you apply AI in your coding workflow for maximum effectiveness?

Question

Accepted Answer

The leverage comes from matching AI to the **right tasks**, feeding it good context, and verifying everything it produces. The model is a fast, knowledgeable assistant with no accountability — you stay the engineer in the loop.

## High-leverage tasks

- **Boilerplate and scaffolding** — CRUD endpoints, config, DTOs, repetitive plumbing you'd type the same way every time.
- **Exploration** — "how do I do X with this library?", drafting an approach, comparing two designs before you commit.
- **Tests** — enumerating edge cases and writing the harness around a function whose contract you define.
- **Mechanical refactors** — renaming, extracting functions, converting patterns across many files.

## Low-value or risky uses

- Asking it to make a **business decision** it has no context for.
- Generating **subtle core logic** (auth, money math, concurrency) you can't fully verify.
- Pasting a vague prompt and shipping whatever comes back.

## How to actually work with it

- **Give good context** — the relevant code, the contract, constraints, and the framework versions. Output quality tracks input quality directly.
- **Iterate in small steps** — ask for one focused change, review it, then continue. Big one-shot generations are hard to verify and hard to debug.
- **Verify everything** — read the diff, run it, run the tests. Treat AI output like a junior's PR, not gospel.
- **Learn from it** — when it uses an API or pattern you don't know, ask *why*, don't just paste. The goal is to level up, not to outsource thinking.

## Why it matters

The difference between a 2x and a 0.5x outcome with AI is not the tool — it's the workflow around it. Used on the right tasks with good context and tight verification, AI removes the tedious typing and widens your exploration, so you spend your attention on design and correctness. Used carelessly, it generates plausible code you can't stand behind and quietly erodes your understanding of your own system. Effectiveness is a discipline: high-leverage tasks, small steps, real verification, and staying in the loop.