The Agent Loop
The agent loop
Lesson 1 of 3
What you'll learn
- Understand what makes something an "agent" vs. a single prompt
- Trace the think → act → observe → repeat cycle
- See where the loop terminates
A single API call answers one question. An agent keeps going: it can decide to take an action, see the result, and decide what to do next. Strip away the buzzwords and an agent is a loop:
- Think — the model reads the conversation and decides what to do.
- Act — if it wants information or to change the world, it requests a tool call.
- Observe — your code runs the tool and feeds the result back.
- Repeat — until the model produces a final answer instead of a tool call.
user goal ─▶ [ think ] ─▶ wants a tool? ─yes─▶ [ run tool ] ─▶ [ observe ] ─┐
▲ │
└──────────────────────────────────────────────────────-─┘
no ─▶ final answer ─▶ done
The model never runs code itself. It asks; your program executes and reports back. That boundary is what keeps agents safe and debuggable.
Always bound the loop
A loop that never stops is a runaway agent. Cap the number of iterations so a confused model can't spin forever — a hard stop is your safety net.
The challenge implements the loop with a fake model that "decides" to use a calculator until it has an answer. Run it and watch the cycle.
The model returns either a tool request or a final answer. Run it and follow the iterations.
Next: how a real tool call is shaped, and how you dispatch it.
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