CocoIndex major update: keeping AI agent context fresh across fragmented sources
smtabatabaie · x · 2026-11-06
The open-source CocoIndex project shipped a major update with 50 contributors, targeting the hard part of production agents: keeping context fresh. It identifies four failure modes — context is fragmented across a dozen systems, goes stale within hours, grows fast (Google's AI-generated share of new code went from 25% in late 2024 to 75%), and agent intent disappears when sessions end. CocoIndex takes a declarative approach: you declare target states agents read (vector index, Postgres table, knowledge graph, Snowflake table) and it keeps them in sync with every source change automatically.
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