From chatbot use to agent setup
Some participants had already used chatbots and wanted to understand what changes when agents can use tools, context and multi-step workflows.
A hands-on Agentic AI workshop for teams in Saudi Arabia that want practical automation without losing judgement, source quality or human review.
Real outputs. Six agent briefs, public and reusable.
Real governance. Source rules, refusals and human checkpoints.
Practical stack
Practical tool choices, grounded in the systems your organisation has approved.
Agentic AI tools
Use the tools your organisation has approved, with clear task boundaries.
MCP and approved integrations
Turn one live business task into a reusable workflow your team can own.
Human review checkpoints
Verify outputs, protect sensitive information, and keep the final decision human.
Workshop brief
Tell us which workflow matters most. We will shape the right audience, tool boundaries and practical outputs with your team.
AI Workshop
Download the working tool
The fastest way to make Agentic AI practical is to force the right questions early: what the agent is allowed to do, which sources it can trust, when it must refuse and who reviews the output.
Get the canvas and practical Agentic AI guidance for your team.
Case study
On 10 May 2026, a mixed group arrived at Espace Dickens with the same tension many teams feel now: AI is everywhere, but reliable agent work still feels abstract. Their pre-work showed the real need: practical tools, clearer agent setup and business use cases that could survive outside the training room.
Date
Sunday 10 May 2026
Venue
Espace Dickens, Lausanne
Room
Finance, pricing, UX, wealth advisory and engineering profiles
Output
6 anonymised agent briefs published as a public portfolio
Before the workshop
Pre-workshop input made the session sharper: the room did not need AI hype. It needed a practical bridge from personal experimentation to governed work.
Some participants had already used chatbots and wanted to understand what changes when agents can use tools, context and multi-step workflows.
The room brought finance, pricing, business analysis, wealth advisory, UX and engineering questions, which kept the session grounded in real work.
Several people wanted to compare notes with others exploring Claude, coding agents, practical AI use and what is actually applicable today.
Anonymised room profile
Self-assessments sat around the middle of the introversion-extroversion scale, so the format mixed quiet canvas work, pair thinking and concise group discussion.
The story arc
01
Before anyone designed an agent, the group named what should stay human: judgement, accountability, approvals and the final decision. That boundary made the technology feel safer and more useful.
02
Participants mapped real work into steps: gather sources, compare signals, draft a report, check assumptions, escalate uncertainty. The agent stopped being a vague assistant and became an operating role.
03
Instead of treating integrations as magic, the session showed how connected agents use approved files, APIs, SaaS tools and local context. This is where governance moved from policy language into practical architecture.
04
Each group left with an agent brief: mission, role, authorised sources, tools, output format, refusal rules, verification checklist and a first pilot path. That is the difference between AI excitement and adoption.
The workshop method
Agentic AI adoption fails when teams jump straight to tools. This format slows down the right decisions, then accelerates the build.
01
Define the decision that remains human and the responsibilities the agent is allowed to support.
02
Break one business workflow into repeatable steps, friction points, source needs and escalation moments.
03
Specify mission, tools, memory, output format, source rules, refusals and review checkpoints.
04
Make outputs separate facts, assumptions, uncertainty, citations and decisions before a pilot begins.
For your team
Your team gets a reusable structure for designing governed agents before touching production systems.
Participants understand how connected agents use files, APIs, SaaS tools and local context without hand-waving.
Each priority use case gets source rules, tool boundaries, refusal logic, human review and success criteria.
You leave with first test, owner, data needs, rollout risk and the metric that proves whether the agent matters.
Real participant outputs
These are the anonymised outputs from the Lausanne workshop. Use them as inspiration for your own pilots.
5-star Google reviews
The signal that matters most is not applause in the room. It is whether people leave clearer, more confident and ready to apply Agentic AI at work.
“Excellent atelier pour se lancer dans les agents IA !”
Henri Mockler
Google review
“Bonne maitrise, pedagogue et patient, surtout avec des novices comme moi.”
Alessandro Condemi
Google review
“George offers generous, informed guidance on agentic AI. I highly recommend his workshops.”
E Hunter
Local Guide on Google
Tell us your workflows, your data constraints and the first agent use case worth testing. We will shape the right workshop format for your team in Saudi Arabia, on-site or in a hybrid format.
Agentic AI Workshop is a facilitator-led corporate workshop for teams that need usable skills and governed workflows. Hands-on Agentic AI training for teams in Saudi Arabia: agent design, MCP workflows, governance, and pilot roadmaps delivered on-site or hybrid.
Exercises are adapted to your approved tools, real workflows, data boundaries, and the decisions that must remain under human review.
The standard format is Full day. Delivery is available on-site, hybrid, or online in Saudi Arabia, including Riyadh and Jeddah. The agenda can be adjusted for one function, a cross-functional cohort, or an executive group.
No generic AI maturity level is assumed: the pre-work aligns the examples, terminology, and exercises with the participants.
Before delivery we confirm objectives, participant maturity, and sensitive-data rules. After the session you receive the agreed workshop artefacts and practical next-step recommendations.
Markdown for LLMs and citations, PDF to share internally.