Your Data Agents Need Context

https://a16z.com/your-data-agents-need-context/
  • Data agents fail without a dedicated context layer — not a tooling problem.
    • MIT 2025 State of AI: most agents fail due to brittle workflows, no contextual learning.
    • Gap isn’t SQL generation — agents can’t parse org-specific metric definitions.
  • Modern data stack consolidation was necessary but not sufficient for agents.
  • Context layer = entity definitions + identity resolution + tribal knowledge + governance.
    • Goes beyond semantic layers; captures implicit, conditional org knowledge.
  • Five-step build path: ingest → auto-construct → human refinement → API/MCP exposure → self-update.
  • Three market bets: data gravity platforms (Databricks/Snowflake), AI analyst co. pivots, net-new context startups.
  • Winning context layer exposes itself via API/MCP — agents consume it, don’t own it.

Jason Cui (a16z Partner, Infrastructure & AI) and Jennifer Li (a16z GP, data/AI) · 2026-03-10 · Read on a16z.com

Type Link
Added Mar 10, 2026
Modified Apr 15, 2026
💭 Thinking 30 items