Decoder. plain-English AI glossary

Observation

● Core

Whatever the agent perceives from the world after it acts — the feedback it reasons over next.

Think of it like

Looking up after each chess move to see how your opponent responded before planning the next one.

Example

The agent clicks “submit,” and its observation is the confirmation page — or the red error banner telling it something went wrong.

How it actually works

Observation is the perception half of the loop: tool results, screenshots, API responses, error messages — the environment’s reply to the agent’s action. Grounding each step in fresh observations is what separates an agent from a model spinning stories in a vacuum. The catch is that observations can be noisy, huge, or adversarial, and the agent has to read them correctly to act well.

For product teams

Agents are only as smart as what they can actually see after each move.

For engineers

The environment’s response to an action, fed back into context as the input for the next reasoning step.

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