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Your agent's token bill is exploding. How do you control the cost of a multi-step agent?

Agents re-send growing context every step, so cost scales worse than linearly. The signal is knowing where the tokens go and the levers (caching, model routing, context trimming, step caps) that cut the bill.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

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These lessons teach the material this question tests, in order and from the beginning.

Agent Engineering·The single-agent loopFree14mWhat the loop actually carries between stepsEvery agent pattern is a variation on one loop, and the interesting part is not the control flow but what accumulates in the message list. Understanding that accumulation explains the cost curve, the drift, and most of what goes wrong later.Agent Engineering·Tools as an interfaceFree14mTool results are the biggest thing in your contextThe most overlooked lever in agent engineering. What comes back from a tool is usually the majority of the context and almost nobody designs it, which is why runs get expensive and lose the thread at the same time.

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