AI Can Write Code, But Understanding Why It Exists Remains a Hard Problem

As AI tools make writing code faster and cheaper, software engineers are facing a growing challenge: understanding why existing code was written in the first place. Critical context is often scattered across old commits, pull requests, incident reports, and the memories of engineers who have since left a company. Removing a seemingly redundant piece of code can pass all tests yet cause production failures hours later, because the reasoning behind it was never formally documented. Experts argue that engineering organizations already possess this historical knowledge, but it remains fragmented across disconnected tools and systems. Structuring these relationships into a connected 'engineering graph' could allow AI agents to provide safer, context-aware recommendations rather than acting on code alone.