autonomous task execution

Autonomous task execution is the far end of the agent spectrum: you state a goal once, and the agent carries it all the way to completion on its own — planning the steps, calling tools, handling results, and only coming back when the job is done or it is truly stuck. Rather than approving each move, you delegate the whole outcome and let it run.

Achieving this leans on every other agent skill at once: planning to lay out the steps, tool use to act, memory to stay coherent over a long run, and feedback loops with error recovery to fix problems mid-flight. The longer and more open-ended the task, the more these have to hold together, because no human is watching each turn to catch a small mistake before it grows.

Full autonomy is appealing but currently the hardest thing to get right, precisely because errors compound without supervision and an agent acting freely can cause real harm. In practice most reliable systems keep autonomy bounded — clear limits, checkpoints, and a human kept in the loop for the consequential or irreversible moves.