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Knowledge guide · AI assistants

What makes an AI assistant genuinely useful at work

Reliable assistants are designed as products: around users, tasks, knowledge, boundaries, feedback, and operations—not around a prompt alone.

01 · Job

Give the assistant a bounded responsibility

Define the users, tasks, permitted sources, expected output, and situations where the assistant should refuse or ask for help. A narrow assistant that performs an important job well is usually more useful than a broad assistant with unclear authority.

02 · Knowledge

Ground responses in approved sources

Identify which sources are authoritative, who owns them, how they are updated, and which users may see them. Retrieval-augmented generation can provide relevant context, but content quality, metadata, permissions, ranking, and citations determine whether that context is trustworthy.

03 · Experience

Design for uncertainty and human judgement

Show sources where evidence matters, communicate limitations, preserve conversation context carefully, and provide clear paths to correct, retry, escalate, or complete the work manually. Important decisions should not be hidden behind confident-sounding output.

04 · Evaluation

Measure behaviour before and after release

Test representative questions, difficult edge cases, permission boundaries, unsupported requests, grounding, refusal, latency, and cost. Production feedback should feed a controlled improvement process covering content, retrieval, instructions, interface, and model choices.

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