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AI Training

Real Use Cases & Building Your Own Agents

Built around one team's own documents and problems, using their real work rather than examples.

Carried overfrom a document supplied by the client, taken 7 September 2026 and not rewritten. Source URL not supplied.

1 x Full-Day Bespoke Session

Built around one team’s own documents and problems, using their real work rather than examples.

Summary:

A bespoke day that starts from the questions a team actually has and works through each one properly, ending with them building an agent that lives in a spreadsheet they already own. Every case uses their own material. It suits a team that has done the basics and wants to see what is genuinely possible.

Course Breakdown:

Know your use cases

  • Opening on the team’s own questions, and setting up a question and answer prompt that keeps returning to them

Quick wins

  • Turning PDF documents into Word
  • Pulling a participant list out of meetings and documents
  • Validating role and permission conflicts

Comparing spreadsheets and reconciling tickets

  • One problem solved three ways
  • Option: Copilot in Excel
  • Option: Copilot Chat
  • Option: a script
  • How to choose between them

The tender review agent

  • Using AI as a structured evaluation assistant against published criteria
  • Where the judgement must stay with a person

Human in the loop

  • Article creation with verification built into the process, and why that matters more than the output

Templates that fill themselves

  • A stakeholder deck template populated from real material

Persona-based simulator agents

  • One-shot and few-shot prompting
  • Creating a persona
  • Building a simulator to practise against

Agent workflows

  • An event creation team of agents
  • The different ways agents can support work
  • The honest limit of a built agent

The agent that lives in a spreadsheet

  • Everything already in Excel
  • Data in a table
  • A rules sheet the agent reads
  • How it works and where it slips
  • A prompt library
  • The part that rewrites its own rules

Outcome:

Participants leave with several of their own problems already solved, and with a working agent built in a tool they already have, that they can extend without help.