The question: What does an agent do when it “works”?
An agent does not follow a plan, it rebuilds it every turn
An agent is given a goal, then repeats the same gesture until it gets there: it observes what it knows, decides on the next action, acts through a tool, takes stock of the result. That result becomes an input of the next turn, and the loop starts again.
What is coloured here is the goal: the only thing that does not move. Everything else piles up, turn after turn, and nobody wrote down in advance how many turns it would take.
The goal« Book a train to Lyon on Thursday morning. »It is given once. It does not change on any turn.
The context on turn 1410 tokens, re-read in fullDotted: what the 4 remaining turns will add.
01What the agent does on turn 1turn 1 of 5
- ObserveThe goal, and nothing else.
- DecideSearch for Thursday morning trains.
- ActTimetable search.
- Take stockNo direct train that morning.
What this turn showsThe agent starts from the goal alone. Nothing tells it yet what will have to be done.
What separates an agent from a workflow
Nobody wrote down in advance that it would have to try again with another payment method. In a workflow, that branch would exist in the code, foreseen by a human. Here it is decided on turn 4, by the model, on reading the refusal. That is the whole difference: a workflow is predictable and repeatable, an agent is adaptive and expensive to guarantee.
What it costs
The context is never reset: every turn re-reads everything that came before and adds its own result. The cost of an agent therefore does not grow with the number of turns, it grows faster than that. And reliability compounds: ten steps that are 95 % safe give only about 60 % success end to end.
Glossary terms
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