Design bounded feedback loops that act, observe, evaluate, revise, preserve useful state, and stop under explicit conditions and budgets.
Tutorials
Explore the mechanisms, tradeoffs, and implementation patterns within this AI engineering track.
The demo works. The agent books the flight, summarizes the repo, files the ticket. Then you point it at a task with one extra branch, and it calls the same…
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A goal-based agent that never terminates is not a model failure. It is a contract failure.
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An agent that acts without reasoning is not reasoning. It is guessing with a tool schema.
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You add a critique-and-revise step. The output gets longer, more confident, more padded with caveats. Your eval score does not move.
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A team adds a "reflect" step to their agent. Scores tick up a few points. Encouraged, they bolt on a memory buffer so the agent can "remember its…
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An agent that plans beautifully and then executes a stale plan into a wall is not a planning failure. It is a state failure.
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A linear agent loop is a commitment device. It commits to one trajectory, and every later step inherits the consequences of the earliest mistake.
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A vector search returns its nearest neighbors whether or not those neighbors answer the question. The pipeline reports no error, the generator receives…
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The release gate is green. Schema validation passed, the golden set passed, the benchmark score ticked up, and the guardrails logged zero trips. Two days…
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An evaluator is only as useful as the set of distinct repair actions its output can select.
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The demo works. The agent reaches a consequential step, pauses, and asks a human to approve. The human clicks approve. Then the resumed run re-executes the…
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An agent that has run forty steps and produced an answer no better than step three is not stuck. It is broken in a specific, nameable way.
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An agent processes 200 units of work over four hours, dies on unit 201, and restarts from zero. The crash is not the failure. The failure is that nothing…
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A scheduled agent that opens two pull requests for the same dependency bump is not a model problem. It is a delivery-semantics problem wearing a model…
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A prompt fix that passes the demo and fails two weeks later is not a bad prompt. It is an improvement process with no memory.
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You have seen the failure. A research agent returns a polished report, the citations look real, and the first URL you check resolves to a page that does…
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