Dimitris Maniatakos
ENΕΛ
Let's Collaborate

AI Training

Learn AI by Doing.

From your first genuinely useful prompt to an AI-supported learning platform: in my trainings you come to understand the tools, build with them, and decide for yourself how to use them responsibly.

Participants experiment, build, test, reflect and apply what they learn to their own work. For youth workers, educators, Erasmus+ organisations and teams.

Plan an AI training togetherTry the Prompt Lab

Who it is for

People who work with young people, and the people who support them.

  • Youth workers and youth leaders in local and international settings
  • Educators and trainers in non-formal and formal education
  • Staff and volunteers of youth organisations and NGOs
  • Erasmus+ organisations preparing exchanges, training courses and partnerships
  • Teams that want to use AI responsibly in their daily work
  • Training and support teams of National Agencies and youth networks

Nine learning areas

A learning journey in three chapters.

Every training draws from these nine areas. Which ones, and how deep, depends on the group, the time available and what you want to be able to do afterwards.

  1. Chapter 1

    Understand

    Talk to the tools, learn with them, judge them.

    1. Communicate effectively with AI

      You learn to ask useful questions, give the context a tool needs, and refine a prompt over several rounds instead of settling for the first answer. You practise reading responses critically: what is missing, what is invented, what needs checking. By the end, a conversation with an AI assistant feels like briefing a colleague, not pulling a lever.

      Example activity

      Rewrite a vague request from your own work into a clear brief, run it three times with improvements, and compare the results side by side.

      Try it in the Prompt Lab

    2. Learn with AI

      AI becomes a study partner: it explains a concept in three different ways, generates practice questions, gives feedback on a draft and helps you explore a topic step by step. You also learn the trap: a fluent answer is not a correct answer. We build habits for testing your understanding and verifying what the tool tells you.

      Example activity

      Pick something you need to learn for your work, design a 30-minute learning session with an assistant, and then quiz yourself without it.

    3. Develop ethical judgement in AI use

      Ethics here is a skill you practise, not a warning you read. Using realistic youth-work scenarios, you weigh privacy, consent, bias, transparency, authorship, reliability and inclusion, and you decide where a human must make the final call. You leave with positions you can explain to colleagues and young people.

      Example activity

      Work through a case: a young person shares a personal problem in a chat with an AI tool. What do you do, what does the organisation do, and what do you tell the group?

  2. Chapter 2

    Build

    Turn a real task into a working tool.

    1. Build AI agents

      An agent is an AI set up to carry out a multi-step task on its own: instructions, the tools it may use, the limits it must respect. You design one for a real job from your organisation, test it, watch where it fails, and decide what stays under human supervision. Many platforms make this possible without programming; where code is needed, we keep it small and explained.

      Example activity

      Design an agent that drafts a weekly summary of your project updates from notes you paste in, then define the three things it is never allowed to do.

    2. Create CRM systems and automations

      Contacts, notes, tasks and follow-ups scattered across inboxes and spreadsheets become one simple system that serves your project or organisation. You map the flow, set up the records, and connect small automations such as reminders or confirmation messages. Handling personal data carefully is part of the design, not an afterthought.

      Example activity

      Build a lightweight participant CRM for an Erasmus+ project: application received, documents checked, travel confirmed, with an automatic reminder for missing items.

    3. Build professional data-driven websites

      You plan and create a website that does a job: structured content, a database where the project needs one, and statistics or dashboards that mean something to the people who read them. We draw the line between a decorative demo and a working digital tool, and you learn what it takes to keep a site alive after the workshop.

      Example activity

      Prototype a project site with a participant registry and a simple dashboard of applications per country, then decide what would be needed to run it for real.

  3. Chapter 3

    Create & Facilitate

    Make things people want to play, learn from and share.

    1. Create games with AI

      From an idea and a few simple rules to a playable prototype in one session, then into the hands of real players. You use AI to speed up writing, artwork, code or balancing, while the creative decisions stay yours. Feedback from testers drives the next version.

      Example activity

      Turn an icebreaker you already use into a small digital or card game, test it with the group, and improve one rule based on what happened.

    2. Design non-formal education games and learning platforms

      Learning objectives become interactive challenges, reflection moments and a participant journey that everyone can follow. You design the experience first and the technology second, whether the result is a game for a workshop or a digital learning space for a whole project. Points and badges are optional. Meaning is not.

      Example activity

      Map one objective from your next youth exchange into a three-stage challenge with a debrief, and sketch the digital space where participants would meet it.

    3. Explore creativity with AI

      Stories, images, music, formats, prototypes and unexpected combinations: you experiment freely and find out what the tools can add to an idea that is yours. The point is personal expression and original human thinking, with AI as a fast, tireless sparring partner. Limits exist, and finding them is part of the fun.

      Example activity

      Take a story from your community and remake it three ways in an hour: as a comic, a short audio piece and a poster. Then choose the one that says what you meant.

How we learn

A flexible process, the same in every format.

Whatever the topic, a session moves through five moves. The order can loop; the last one is never skipped.

  1. Short explanation

    Just enough to know what the tool is, what it is for and where it tends to go wrong.

  2. Guided practice

    Everyone tries the same small task with support, so nobody is left behind at the first step.

  3. Small-group creation

    Groups of two to four build something for a real need they bring with them.

  4. Testing

    What was built meets real users, colleagues or the rest of the group. Feedback is collected, not defended against.

  5. Reflection and transfer

    We name what worked, what did not and why, and each participant plans the next step in their own project.

The precise modules and outputs depend on the participants, the duration and the goals of each training. A short workshop goes deep into one area. A multi-day course connects several.

My method

Explore, Try, Reflect, Apply.

The rhythm inside every one of those moves, from curiosity to capability. Not a certified system: a way of working that comes from non-formal education and from seven years of noticing what actually sticks.

  1. Explore

    What is this, really?

    Curiosity first. We look at what a tool actually does, what the group already knows, and which question is worth our time.

  2. Try

    What happens if I do this?

    Hands on the keyboard within minutes. Small experiments on real tasks from youth work, in pairs or small groups, with permission to fail.

  3. Reflect

    Where did it help, where did it fail?

    We compare results, check sources, and name what the tool invented, flattened or got right. Critical judgement is built here.

  4. Apply

    What will I do with this on Monday?

    Each participant turns the experience into something for their own context: an activity, a workflow, a rule of thumb.

Try it now

The Prompt Lab

Pick a group, a learning goal and a format. The lab assembles a context-rich prompt that you can edit, copy and use with any AI assistant.

This is a local prompt template built on this page. Nothing is sent to an AI service and no account is needed.

Who is the group?
What should they learn?
What format do you have?
Your prompt
You are helping a youth worker design a non-formal learning activity. CONTEXT- Group: Youth workers in a training course- Learning goal: Judge AI answers critically and check facts- Format: A 90-minute workshop PRINCIPLES TO RESPECT- Non-formal learning: participants learn by doing and in dialogue, then reflect on the experience.- Participants use the tools themselves. This is not a lecture about AI.- Include at least one moment where the group checks an AI output for mistakes, bias or invented facts.- Keep it inclusive: no prior technical knowledge, low-cost materials, and it must work with a few shared devices.- Safety: no personal data of participants goes into any AI tool. Prefer free tools or those the organisation already uses. WHAT I NEED FROM YOU1. A short title and a two-sentence description.2. A step-by-step plan with timing that fits the format above.3. Materials and preparation, including any prompts the participants will use.4. Three debriefing questions that connect the experience to the learning goal.5. One variation for a group with lower digital confidence and one for a more experienced group. Before you start, ask me two clarifying questions if something important is missing.

How to use it

  1. Paste the prompt into the assistant your organisation uses.
  2. Read the answer as a draft, not a result: check facts, cut what does not fit your group.
  3. Run the activity, then note what worked. That note is your next prompt.

Three ways to work together

The three engagements in detail.

For each one: who it is for, how it works and what you get.

01

AI Training for Youth Workers

Hands-on workshops where participants test tools, assess their limitations, and build activities they can use with young people.

Who it is for
Youth workers, trainers and the staff of youth organisations, networks and National Agencies who want a grounded, practical relationship with AI tools.
How it works
We start from real tasks in your daily work, try tools together, check where they fail or mislead, and turn what works into activities for young people.
What you get
A set of tested activities, a shared way of judging AI outputs, and the confidence to keep experimenting after the training ends.
About the trainings

02

AI in Erasmus+ Learning

Design and facilitation of youth learning experiences where AI supports creation, critical thinking and personal expression.

Who it is for
Partners preparing youth exchanges, training courses and other Erasmus+ Youth activities who want technology to serve the learning, not replace it.
How it works
I design sessions in which young people use AI as a tool in their own hands: to create, to question what comes out, and to tell their own story. Then I facilitate them together with your team.
What you get
Concrete products young people are proud of, such as personal portfolio websites or digital stories, and a programme partners can document and report on.
See Y-Cycle

03

Training & Project Facilitation

Non-formal education design, intercultural group facilitation and Erasmus+ coordination.

Who it is for
Organisations that need an experienced trainer or facilitator for a learning activity, or a coordinator who knows Erasmus+ from the first idea to the final report.
How it works
We clarify the learning goals, I design the programme and the group process, and I facilitate on site, adjusting to the group as it actually is rather than as planned.
What you get
A learning activity that runs well, a group that works together, and paperwork in good order.
Discuss a project

How a training is tailored

Four steps from the first call to the last debrief.

  1. We talk

    A short call about your group, how they currently use AI, and what "useful" means for your organisation.

  2. I propose a programme

    Length, learning areas and the balance of hands-on work and discussion, from a short workshop to a multi-day course.

  3. We agree the practicalities

    Tools (free and accessible options preferred), working language (English or Greek), devices, and any rules your organisation has on data.

  4. You keep the material

    Participants leave with their activity templates, their prompts and a short guide to continue on their own.

Possible outputs

What participants can take away.

Depending on the format and the goals of the group, for example:

Possible formats

  • Short workshop on one learning area
  • Multi-day training course connecting several areas
  • Tailored session for an organisation or team
  • Online series over a few weeks
  • Module inside a longer Erasmus+ training course
  • A bank of tested prompts for tasks from your own work
  • An activity for young people, tried out during the training
  • A first working prototype: an agent, a simple CRM, a game or a project site
  • A personal checklist for judging AI outputs before you rely on them
  • A clear position on where AI belongs in your organisation, and where it does not

The Youth and AI training with the Hungarian National Agency shows the approach in a real programme. The Prompt Lab lets you try a small piece of it right now.

Youth and AI case studyOpen the Prompt Lab

Plan an AI training together

Write to me with three things: who the group is, the dates you have in mind, and what you would like people to be able to do afterwards. I answer with a first proposal.

Plan an AI training together