What’s inside
Most of a software engineer’s time is not spent writing code — it’s spent debugging and understanding why things went wrong.
AI coding assistants are helpful in coding, but concerns remain about whether they can scale to large codebases and how much hallucination limits their capability.
Coding agents share a human weakness: they can’t truly see what happened at runtime, making it hard to reason about cause and effect.
This briefing paper explores how agentic debugging plugs this gap and how it can deliver autonomous, hallucination-free root cause analysis.
