AGENTS ARE COMING FOR DATA (JUST SLOWLY)

Summary from the TLDR Data newsletter

AI agents are well suited to the boring, mechanical parts of data work, such as testing assumptions, diagnosing schema changes, maintaining context, and fixing pipelines, while proactive automated insights remain much harder because relevance and false positives are difficult to control. Data teams should prepare with strong evals, explicit business context, and low-latency infrastructure that can handle bursty, parallel agent workloads.