Graph-grounded codebase reasoning

As context-heavy workflows become more common, sending full source files or unstructured text to LLMs increases token costs. Graph-grounded codebase reasoning addresses this by representing code, documentation and relationships as a structured graph, allowing agents to retrieve relevant subgraphs as context. Tools such as ⁠Graphify capture structural dependencies, helping agents identify relationships that text-based retrieval may miss.

However, graph grounding comes with trade-offs. Recent research suggests agents can sometimes perform worse with graph-based context than with simpler tools such as find and grep. We’ve placed the technique in Trial to encourage readers to explore when graph-based context improves efficiency and accuracy, building on our previous blip on code intelligence as agentic tooling.