Use AI as a Teammate: A Better Developer Workflow
Résumé
Pixel shares a practical guide to using AI as a development teammate rather than a search engine. It recommends setting goal-driven tasks, asking for a plan, providing project tools and reusable agent skills, and reviewing diffs and tests to catch mistakes before shipping.
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Use AI Like a Teammate, Not a Search Engine
Most people use AI like a search engine: ask a question, get an answer, close the tab. That works for quick lookups, but it leaves most of the value on the table. The developers getting the most out of AI treat it like a teammate. Here is the approach I use after completing Anthropic's courses on AI Fluency, Claude Code and Agent Skills. 1. Give it a goal, not a prompt "Write a function that validates emails" is a prompt. "Our signup form accepts invalid emails and support is getting complaints; find where validation happens and fix it" is a goal. The second gives the AI context, a problem and a definition of done. 2. Let it plan the steps Ask for a plan before any code is written. Reviewing a five-line plan is far cheaper than reviewing a wrong 500-line change, and it surfaces misunderstandings early. 3. Give it the right tools and skills An assistant that can read your project, run tests and follow your team's conventions beats one working from a pasted snippet. Agent skills are a good way to package repeatable instructions, such as your code style or deployment checklist, so you do not re-explain them every session. 4. Review the output, do not just accept it AI can be confidently wrong. Read the diff, run the tests and check edge cases. You stay responsible for what ships. The takeaway AI does not replace your judgment, it multiplies it. The better you define the problem, the better the result. How are you using AI in your workflow: search engine or teammate? Let me know in the comments.
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