Template · ZIP · 12 KB
What can we do now helper kit
Turn a conversation about current practice into an editable list of changes you can act on.
An installable helper with a starter prompt, output template and fictional practice case for reviewing one part of your business.
The first part is open below. The download adds: start with the practice case.
Free. The link shows here and lands in your inbox. Nothing else.
What's inside
- A helper that interviews you about current practice and the constraints behind it.
- An editable What we can do now template with evidence, unknowns and next actions.
- A fictional practice case and completed example to check the output.
- One experiment brief with an owner, working-time allocation and a pass condition.
Get beyond a list of suggestions
The helper asks about one part of your business. What does the customer need? What do people actually do? Which constraint made that necessary, and when did anyone last check it?
You leave with a document that separates work to remove, service to improve and things worth attempting. Each proposed change carries its evidence, unknowns and first test. A separate Do now list shows the actions supported by the inputs and access you already have.
Try the fictional reporting example first. Two small tables support a change note. They don't support a story about why the numbers changed, a revenue claim or permission to send anything to a customer.
This kit accompanies Can we go bigger?. The separate one-page starter gives you the short prompt to use in a fresh conversation.
Still to come, in the download
- Start with the practice case
Free. The link shows here and lands in your inbox. Nothing else.
Who's behind it
Matt Hertel. An engineer who has also run the company. Built and sold apps solo. Fractional CTO in startups. Every Sunday, one job start to finish, in No Manual Yet.
Every Sunday, one job start to finish. Read No Manual Yet
It goes with this issue
More to take
- What can we do now?
Leave with a useful change to test, the evidence behind it and someone responsible for the result.
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Turn settings and test notes into an evidence-labelled decision about one connected AI tool.
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Decide what access one connected AI tool needs, with evidence from its settings and a dummy-data test.