Treating AI Coding Agents Like Junior Engineers
AI coding agents are powerful but can be reckless at scale. This article argues for treating them like junior engineers, providing proper context, reasoning guidance, and safety nets to transform them from liability to productivity accelerator.
We've all heard the tale: one innocent query wipes out an entire DB table on prod.
Embarrassing, costly, and maybe recoverable.
Now imagine our AI coding agent doing the same thing.
Not just with one table, but at machine speed, across multiple services we rely on.
The issue isn't intent. It's scale.
That's why I think treating AI agents like "just tools" is risky.
I consider them more like good junior hires: fast, eager, and a bit reckless.
We wouldn't let a new engineer push to prod on day one.
We'd give them onboarding, reviews, and guardrails.
Our AI coding agent deserves the same:
1️⃣ Feed them context - give them access to docs, style guides, and constraints. The amazing Addy Osmani has a great write-up on this. Memory Bank is another practical way to preload knowledge.
2️⃣ Guide their reasoning - don't just let them guess. Sequential Thinking is a neat way to help them work step by step.
3️⃣ Build safety nets - syntax checks aren't enough. Add tests and PR rules. Gemini Code Assist style guides are a solid example of codifying standards AI can follow.
Do this right, and I think our AI coding agent shifts from liability to accelerator.
The bottom line: I don't consider them dumb - just context-hungry. Feed them well, and they'll surprise us.