Linghua Jin

When you have a large enterprise monorepo or corpus with 1% changing every day, how do you build a data pipeline that effectively surfaces fresh insights to your coding agents continuously? Agents run ~50x faster than humans and create massive unstructured data. You cannot fit the entire thing into the agent; it requires building a view over a large unstructured corpus. CocoIndex is a context engine for agents: a new computing paradigm over evolving unstructured assets and multi-stage processing. You declare the state of your target as a function of the source; the engine keeps it in sync with minimal reprocessing, across time horizons, at scale. Demo: building context for coding agents on 100GB+ monorepos, ~1% changing daily.