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Prompt Engineering in Practice

Cover of the “Prompt Engineering in Practice” training

The difference between people who get value from AI and people who give up after two weeks is almost never the tool. It is how they ask.

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Who This Training Is For

  • Any team already using generative AI with uneven results
  • People who must produce text, analysis or supporting material at a constant quality
  • Teams that want reusable instructions instead of starting from scratch
  • Organizations preparing internal assistants

What Your Team Will Be Able to Do

  • Structure a request that returns the same quality every time
  • Give context and examples without writing an essay
  • Fix a bad result instead of starting over
  • Build a shared library of instructions for the team
  • Recognise when the problem is not the prompt but the task

Programme

  1. How these models work — the minimum needed to stop guessing
  2. Anatomy of a good instruction — goal, context, format, constraints and examples
  3. Iterating — how to fix a result without going back to zero
  4. Reusable instructions — turning what worked into a template for the team
  5. Working with your own documents — giving organizational context without exposing what must stay in
  6. Limits — what no prompt will fix

Learning Objectives

  • Understand how LLMs interpret and respond to prompts
  • Structure clear, effective and reusable prompts
  • Control the format, tone and depth of the outputs AI generates
  • Refine and iterate prompts strategically, spotting and correcting incomplete, wrong or hallucinated answers
  • Create a working Prompt Pack, adapted to your professional role

Format

  • In person or online
  • Adaptable duration: 4h or 8h
  • Each team leaves with its own starter library of instructions
  • Exercises on the participants’ real tasks

What Makes It Different

It is the most transversal training in the catalogue, and the one that shows results fastest.

Without method, everyone reinvents the wheel daily and results swing by the hour. With method, the team starts sharing what already works.


Does your team get different results for the same request?

Request a tailored proposal.

Prepare your team to apply AI to real work

Share the context of the organization, the profile of the participants and what the team needs to be able to do better.

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