Upskilling & Enablement

Buying licences does not change how people work. A few enthusiasts get good at it, most try it twice and stop, and managers cannot tell what is making a difference. Generic courses explain tools in the abstract. We teach with your documents, your processes, and the tools your company has approved, so what people learn on Tuesday they use on Wednesday.

Built on your own work

Exercises use your real documents and tasks, so people practise on the things they actually do.

Different for each role

Leaders, everyday users, engineers, and risk teams each get a course that fits their job.

Adoption is measured

We track who uses what before and after, so you can see whether the training changed anything.

Skills assessment

A short survey and interviews to learn who already uses AI, how, and where people are stuck.

Role-based workshops

Half-day and full-day sessions with live exercises on your own material, led by someone who does this work.

Hands-on labs for engineers

Building and testing a working feature in your stack, with code review and pairing from our engineers.

Prompt and agent playbooks

Short written guides for your common tasks, with tested examples people can copy and adapt.

Champions network

A handful of people in each team trained to help colleagues, so support does not depend on us.

Responsible-use guidance

Clear rules on what data can go where, how to check an answer, and when to ask for a second opinion.

• Leaders and executives

  What we teach

  What AI can and cannot do today, how to judge a proposal, and the questions to ask before approving spend.

  What they can do afterwards

  Review a business case with confidence and sponsor the right projects.

• Managers and team leads

  What we teach

  Redesigning a team process around AI, setting expectations, and checking the quality of work produced with it.

  What they can do afterwards

  Pick the first tasks to change and track whether they improved.

• Everyday users

  What we teach

  Writing clear requests, checking answers against sources, and using the approved tools on their own tasks.

  What they can do afterwards

  Save time on routine work and know when not to trust an answer.

• Engineers and data teams

  What we teach

  Building retrieval features and agents, writing evaluations, and releasing changes safely.

  What they can do afterwards

  Ship and maintain an AI feature with the team’s own tools.

• Risk, legal, and compliance

  What we teach

  How these systems fail, what to review, and how the rules apply, including the EU AI Act.

  What they can do afterwards

  Review AI projects quickly and set sensible, practical controls.

1. Phase 1

   1 week

   Assess

   • Survey and interview a cross-section of the people to be trained
   • List the approved tools and the tasks where AI could help most
   • Agree how adoption will be measured

   You receive

   Skills findings, a programme outline, and baseline measures.

2. Phase 2

   2 to 3 weeks

   Design

   • Build the exercises from your own documents and processes
   • Write the playbooks for the most common tasks
   • Test the first session with a small group

   You receive

   Course materials, exercises, and playbooks.

3. Phase 3

   4 to 8 weeks

   Teach

   • Run a pilot cohort, then adjust before widening
   • Deliver workshops and labs by role
   • Hold short follow-up sessions a few weeks after each course

   You receive

   Trained cohorts and a set of working examples from their own tasks.

4. Phase 4

   Ongoing

   Embed

   • Train the champions to support their colleagues
   • Measure adoption against the baseline
   • Update the playbooks as tools and rules change

   You receive

   Adoption report, champions network, and refreshed materials.

What you keep

Materials you can reuse

Slides, exercises, and playbooks are yours to keep, edit, and use with new joiners.

Recordings where you want them

Sessions can be recorded for people who miss them, stored in your own systems.

Practice on safe data

Exercises use material you have approved. Nobody has to paste in anything sensitive.

A trained champions network

Colleagues who can answer questions and keep the habit going when the programme ends.

Clear measures

Before and after results for usage and confidence, so the value of the training is visible.

Tools we teach with

Assistants

Microsoft Copilot, ChatGPT Enterprise, Claude, Gemini, taught on whichever your company has approved

Engineering

TypeScript and Python, AI SDK, vector search, evaluation tools

Agents

Workflow and agent frameworks used in your stack

Learning delivery

In-person workshops, live online sessions, and recorded labs

Adoption tracking

Usage data from your tools, surveys, and short skills checks

Knowledge base

Your wiki or intranet, so playbooks sit where people already look

We teach on the tools your company has approved, not ours.