The best practices for AI coding agents come down to a few habits: give clear specs, keep changes isolated and reviewable, and verify output before it ships. Most agent frustration traces back to skipping one of these—vague asks, unchecked edits, or trusting code nobody tested.
The practices that pay off, and why:
- Plan before building — best for catching wrong assumptions early, on a page you can read.
- Isolate changes — best for keeping bad edits away from working code.
- Verify with tests — best for trusting output at scale.
- Record conventions — best for consistent results across tasks.
These aren't tool-specific, but some tools build them in: a plan-first, worktree-isolated, verification-based workflow like Verdent's bakes the habits into the process instead of leaving them to discipline. Either way, the practices matter more than the brand—a great tool used carelessly still ships bad code.
The question to audit yourself with: which of these am I actually skipping? Usually it's one, and it's usually the source of your worst agent moments.
Pick the practice you skip most and add it this week. One habit, applied consistently, changes your results more than switching tools.
