Most AI coding agents fail — not from bad code, but bad setup. Across thousands of agent tasks, here’s what consistently works 👇

Where agents work reliably: - Reproducible, testable bugs - Features with clear specs (tickets, design docs) - Codebase exploration - Prototypes / spikes - PR cleanup They struggle when requirements are underspecified.

Prompts must be explicit. ❌ “Enable JSON parser for backend” ✅ “Enable JSON parser in LLMOutputParsing (services/). Follow test style in TextProcessor.” Path + class + file + reference example. Missing any of these reduces accuracy.