// Field notes

Practical thinking for better workflows.

Practical guides to choosing workflows, qualifying enquiries, preparing knowledge and keeping automation dependable.

01 / Choosing your first automation

Start small. Fix a workflow people actually repeat.

A practical way to choose a first automation that has a clear owner, a measurable purpose, and manageable exceptions.

Where an AI agent helps—and where clear rules are enough.

Choose a system around the decisions a task requires, not around the most impressive label.

Measure the work saved, and the work that remains.

A practical framework for evaluating automation without turning an estimate into a promise.

How to qualify leads when you are handling every enquiry yourself

A practical approach to prioritising enquiries without excluding a company just because its size or budget is unknown.

What to prepare before an automation audit

Bring a process, representative examples and a definition of success. A large technical specification is not required.

How to prepare a knowledge base an AI assistant can use

Useful answers start with maintained sources, clear access boundaries and a reliable way to say that the answer is missing.

What should happen when an automation fails?

Design retries, approvals and manual recovery before the first workflow becomes part of everyday operations.

01 /

Start with the question you need to answer.

Choose a first workflow, decide where an AI agent belongs, or establish a useful baseline for measuring results. These guides are starting points for a conversation with the people who do the work.