Eight units, one job each

Learning goals

List the jobs a founding team used to split; decide for each whether you do it, an agent does it, you buy it in, or it waits.

Expected outcomes

A completed Job Map and a first view of which gaps the later units must close.

Open Lesson 1

Learning goals

Explain what an agent is, how it uses tools and plans; name the tasks agents handle well and where they fail.

Expected outcomes

A ranked list of tasks to delegate now, later or never, with a reason for each.

Learning goals

Write a task an agent can carry out: goal, inputs, limits, permissions, what done looks like.

Expected outcomes

One tested task specification and a revised version after the trial run.

Learning goals

Set up the checks a co-founder would have made: source verification, a second reviewer (human or separate agent), logs.

Expected outcomes

A working checklist with a named reviewer for each recurring output.

Learning goals

Run customer-discovery interviews, fill a business model canvas and a lean canvas, set a first price, pitch in two minutes.

Expected outcomes

Both canvases with assumptions marked confirmed or not, a first price and a two-minute pitch.

Learning goals

Estimate start-up costs, choose cash or accrual records, keep receipts and books, register for tax, pay yourself.

Expected outcomes

A twelve-month money sheet, a record-keeping routine and the tax registrations your business needs.

Learning goals

Compare sole trader, partnership, limited company and corporation on liability and paperwork; know when investors need an entity.

Expected outcomes

A chosen structure with the reasons, the filings it brings, and the questions to take to a lawyer or accountant.

Learning goals

Apply GDPR basics as a small firm; meet the EU AI Act literacy duty for yourself and anyone acting for you; recognise the main security risks of LLM apps.

Expected outcomes

A completed compliance checklist, a record of your own AI literacy training, and the security risks that apply to your tools.