RDMAIC · Tailored team learning
Learn by doing. Start with your everyday work.
Prepare a presentation. Make sense of feedback. Discover a better way to handle a recurring task.
I help your team learn to use AI by working on real tasks together. The starting point is your current experience, tools and working environment. Together, we explore what could help, practise and develop approaches you can keep using.
A useful place to begin
These are starting points, not compulsory modules. Begin with one or both, and let practical experience guide the next step.
You have the material. Now make the message clear.
Work on a presentation your team actually needs: clarify the audience and purpose, develop the story, improve the explanations and turn existing material into useful slides.
A useful presentation, practical AI skills and an approach to reuse next time.
You have the comments. What are they telling you?
Explore customer comments, participant feedback or internal survey responses. Identify themes, notice differing views and discuss what may be worth acting on. Check the interpretation against the original comments.
A checked summary, possible next steps and a repeatable way to approach similar feedback.
The tasks can connect: feedback → findings → presentation. They can also stand alone.
Your team’s starting point
Some people are just starting with AI. Others use it regularly but want better results. I adapt the demonstrations, practice and support to your team’s experience and actual work.
How we work together
The programme combines hands-on sessions, practice in real work and follow-up clinics. Scope, pace and on-site or remote delivery are agreed around your team.
After agreeing the engagement, look at selected tasks, the team’s experience and approved tools. Explore relevant possibilities together.
I demonstrate, then we work together. Practise giving AI context, refining its suggestions and checking the result.
The team tries the approach in everyday work. We review what helped, what was difficult and what needs to change.
Save useful instructions, examples, templates and review steps. Try the approach on another task with less support.
Discover useful possibilities
An additional tool may help with a particular task. When there is a useful reason, we compare options on the same task and consider the result, editing effort, cost and fit with your organisation. Sometimes the better answer is a clearer instruction or template—not another tool.
Trials use approved or suitable example material. New licences, integrations and substantial implementation are agreed separately.
What stays with your team
A presentation, feedback summary or another agreed output that has been reviewed for its intended use.
Practice explaining tasks to AI, providing context, challenging suggestions and checking outputs.
Instructions, examples, templates and checks your team can adapt for the next task.
The practical test: can your team repeat the task with less support and explain what still needs checking?
Excel analysis can enter the programme when a clear need emerges; it is not the starting promise. Feedback arriving in a spreadsheet does not turn the engagement into a data-analysis project. Complex data preparation, dashboards and automation are scoped separately.
People review outputs and keep the decisions. The required material, permitted use and secure transfer method are agreed before sensitive files are shared.
Let’s find a useful starting point
Let’s discuss your team’s work, current experience and the kind of support that would be useful.
Let’s talk about your team’s work