Yadnesh Salvi

Story · arXiv

FIRE: Failure-Informed Runtime Engineering for Reliable Language-Model Agents (arXiv)

paper · Story page

A left-to-right track of small squares. At three of them a fainter path peels downward into a dead end, and a short hinged bar is swung shut across each of those three turnoffs. The main track runs past them to a single larger open square at the right.

Runtime policies are natural-language instructions and action denials the harness applies at the states that preceded observed failures, leaving weights and the user prompt untouched. Across the 87-task Terminal-Bench 2.1 suite, repeated success for GPT-5.6 Sol moves from 64.4% to 73.6%.

In plain words

  • Researchers made an artificial intelligence assistant more consistent at finishing tasks by giving it rules based on earlier mistakes.
  • When the assistant reaches a situation linked to past failures, the software gives extra instructions or blocks particular actions.
  • The approach needs no retraining of the assistant or changes to the user's request.
  • In tests, one assistant completed both tries on 73.6% of tasks, up from 64.4%, suggesting more dependable help for users.

Appeared in

Subscribe

Get the brief in your inbox

Pick daily, weekly, or both. Nothing is gated either way: every issue is on the site and in the feeds.

  • Weekdays at 8:45am IST, one lead story and 6 to 9 items.
  • Sundays, an argued synthesis rather than a recap.
  • One click to leave, and quiet days say so in the subject line.
How often

Weekdays 8:45am IST + Sundays. Unsubscribe in one click.

You're asking for The Agentic Brief by email at the cadence you picked. You can unsubscribe in one click from any issue, and your address is never sold or shared.

Subscribe by RSS →