Bringing backend predictability to multi-agent systems
I've been hearing the phrase "graph engineering" thrown around a lot lately. I originally assumed it had something to do with knowledge graphs, or maybe GraphRAG. Not quite!
I sat down with Annie Wang and asked her to break it down from the ground up: what graph engineering is, and how it gives developers control over complex AI systems.
The point that stuck with me is that graph engineering basically feels like modern backend architecture —like microservices— applied to agents. Instead of letting LLMs wander in a black-box loop and hoping for the best, you treat nodes with strict schemas and fan-out/join pipelines. It gives us back the predictability and debuggability that software engineers actually need.
(You can also follow along with the hands-on ADK Codelab). Did your mental model of "graph engineering" match up? Are you still running straight loops for your agents, or have you started breaking them into graph patterns? Let me know in the comments!