Agent on a Sandbox Task
An agent is just a model in a loop — and loops are where things go wrong.
Key Insight
An agent is an LLM placed in a loop: it plans, picks a tool, acts, observes the result, and repeats until the task is done. This project builds a tiny ReAct-style agent on a deterministic task and runs it across many seeds to measure how reliably it actually succeeds.
Why This Matters
A single correct answer is easy; staying on track across many steps is hard, because a small per-step error rate compounds into frequent whole-task failure — which is why agents must be judged over many runs, not on one lucky success.