FIELD NOTES

Before you automate,
get the foundations right.

Short, practical guides to the decisions that make AI projects easier to start and maintain.

A camera operator working on a media production
A few useful ideas for the work behind the store.

Preparing your knowledge base

Start with the information customers actually need.

Gather your current product details, delivery policy, returns policy and recurring support questions. Identify which source is authoritative when documents disagree.

Remove outdated policies and duplicated answers. Give each information set an owner and a review date. A small, current knowledge base is a more useful starting point than an unreviewed document dump.

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Finding your first automation

Look for repetition with a clear decision path.

Write down the inputs, the action your team takes and the expected output. Good early candidates have repeatable steps, accessible information and a person who can review exceptions.

Begin with a contained task such as preparing supplier data or drafting a response. Keep an explicit review point for decisions that affect customers, orders or published information.

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Keeping AI content on brand

An approval process matters as much as a prompt.

Collect examples your team considers good, the terms you use and the claims you avoid. Add channel-specific guidance: length, audience, purpose and call to action.

Treat generated text as a draft. Review product facts, tone and any promotional claims before publication, then use those edits to improve the next brief.

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Discuss your project

Start with a
focused project.

Tell us which task takes up time and what you would like to improve.

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