TLDR Tech / Data
What data agent benchmarks do and don't tell us
AI Council showed the data/AI divide is collapsing: most vendors now position themselves as AI infrastructure layers for context retrieval, orchestration, or inference, and new systems like LanceDB are being built natively for LLM and multimodal workloads. Benchmarking is shifting too: dbt Semantic Layer tests, ADE-bench, and 90-day simulations all suggest agents perform best on well-specified, context-rich tasks and improve when stateful, cross-system context from GitHub, Slack, Notion, and dbt is available. The next major constraint is token and compute efficiency.
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