Researchers released TEAL, a method that lets coding agents automatically build reusable tools while answering data‑lake questions. Two helper agents suggest tools—one scans the raw data, the other watches the main agent’s steps. A tool is kept only if the main agent uses it without extra work and the answer stays consistent. The team also added TEAL‑Q to make fake questions when real ones are scarce.
Why it matters
It shows that analytics agents can become more efficient without any human‑provided labels, lowering the cost of building data‑lake tools.
