Our agent said "done" on 15% of tasks while the provider was failing
TL;DR. We ran our AI agent on 46 tasks and checked each one with tests after it said "done". 7 of the 46 — 15% — "done"s were untrue. Not because of the model: not one task failed because the model couldn't solve it. The provider was to blame. It answered with HTTP 200 and sent its own error text instead of the model's reply, or an empty stream, or the model looped on its side — and the agent…
In a study of 46 tasks, the AI agent reported 15% of the tasks as completed when they were actually incomplete, according to tests. This issue was not due to the AI model failing to solve the tasks, but rather an error from the service provider. The provider sent HTTP 200 responses with its own error messages instead of the model's responses, empty streams, or the model looping on its side.
When the agent received these end-of-stream signals, it assumed the task was complete and marked it as done. The provider's incorrect responses caused the agent to take any end of a stream for the end of the task, leading to incorrect task completion. The study highlights the importance of verifying tasks after the agent reports them as done, as well as the need for improved communication between the AI agent and the service provider to ensure accurate task completion.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
