Building custom AI agents is easier than ever. OpenAI's API, Claude's tool use, LangChain, CrewAI — the building blocks are available. So every engineering team asks: should we build our own code intelligence agent?
The answer depends on what you actually need.
Build your own when:
Buy when:
The typical "build" trajectory:
The gap between "RAG over codebase" and "actual code intelligence" is enormous. RAG gives you semantic search. Intelligence requires dependency graphs, feature clustering, call path tracing, git history analysis, and knowledge extraction.
Use commercial tools for codebase intelligence (the hard, non-differentiating infrastructure). Build custom agents on top for your specific workflows. This gives you the best of both: deep codebase understanding from a tool that's spent years building it, plus custom automation for your unique needs.
The build trap happens because building codebase intelligence is essentially paying the Understanding Tax upfront in engineering time. Buy the intelligence layer, build the custom workflows on top.
For the lightweight agent starting point, read OpenAI Swarm: Lightweight Multi-Agent Coordination.
Glue is the pre-code intelligence layer you buy so you don't have to build it. Deep codebase analysis, feature discovery, dependency graphs, and tribal knowledge extraction — battle-tested infrastructure that your custom agents can leverage through MCP.