Story · arXiv

What Stops a Small Language Model From Driving a Database Agent (arXiv)

paper · Story page

Eleven days driving an open-source SQL client's agent mode with 39 local open-weight models produced 8,199 runs. Of 2,100 model-attributed losses, 1,590, or 75.7%, came from runs that had already invoked a tool, so the bottleneck sits after the call.

In plain words

  • In this study, 75.7% of failures blamed on artificial intelligence happened after it had already asked other software for help.
  • The assistants worked with databases, organized collections of stored information, by sending requests to other software.
  • Requests in the wrong format repeatedly appeared in attempts that used other software but never delivered results.
  • For developers improving these assistants, the findings point to problems between asking for help and delivering a finished answer.

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