AI Pair Programming: It's a Junior Dev, Not a Wizard
AI coding assistants are useful when you treat them like a fast, literal junior teammate. Give them constraints, review their output, and stop expecting architectural insight.
Software Development
Development work gets better when interfaces stay small, feedback is fast, and tooling serves the codebase instead of distracting from it.
The AI-assisted development posts here treat AI like a junior developer with useful speed and real failure modes. The goal is not novelty. The goal is better throughput without lowering standards.
Start Here
- AI Pair Programming: It’s a Junior Dev, Not a Wizard is the practical framing for coding with AI.
- AI Code Review Is Mostly Noise explains what AI review catches and what it misses.
- Running AI Locally: A Practical Guide for Teams Who Care About Control covers local-first tradeoffs.
Practical Rules
- Keep generated code behind the same review and test standards as human-written code.
- Use AI for acceleration, not for unstated architecture decisions.
- Prefer small, reviewable changes over broad rewrites.
- Make observability and rollback part of production development, not cleanup work.
Supporting Reads
- Observability-Driven Development Is Just Instrumenting Your Code
- Most AI Developer Tools Are Not Worth Adopting Yet
- AI Engineering Is Its Own Discipline Now
Failure Modes
- Treating AI-generated boilerplate as production-ready because it compiles.
- Letting tools change architecture without explicit review.
- Adopting development tools before measuring the workflow they improve.
- Replacing feedback loops with prompt rituals.
Related Hubs
References
Running AI Locally: A Practical Guide for Teams Who Care About Control
Local AI is no longer a hobby project. Here's how to set it up properly: provider abstraction, versioned models, evaluation harnesses, and cloud fallback for when local isn't enough.
AI Code Review Is Mostly Noise
I've been running AI code review on real PRs for months. It catches some real bugs. It also generates a staggering amount of useless commentary.
Observability-Driven Development Is Just Instrumenting Your Code
ODD sounds fancy. It's not. It means writing logs, metrics, and traces before you ship, not after your first outage.