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Measuring whether the AI actually helped users accomplish their goals.
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| name | task-success-metrics |
| description | Measuring whether the AI actually helped users accomplish their goals. |
Output quality doesn't guarantee task success. The AI might produce a beautiful response that doesn't actually help the user do what they came to do. Task success metrics measure the end-to-end outcome.
For each user task, define:
These can diverge:
Proactively identifying failure modes, misuse, and unintended consequences.
Managing shared context, memory, and state across multiple agents.
Coordinating text, image, voice, and tool-use modalities in a single interaction.
Helping users form warranted trust in the AI — neither overtrust nor undertrust — through deliberate confidence and source signalling.
Reading user emotional state from text signals — caps, punctuation density, repetition, latency — and adapting before the user disengages.
Designing review workflows to surface and mitigate bias in AI outputs.
