English
Format: 4 days, intensive programme Location: Autódromo Internacional do Algarve, Portimão, Portugal Target audience: High potentials, tech leads, aspiring "AI architects"
Who needs to go to Portugal?
The engineer with ambition Erik, 28. Three years into his first engineering role. Started in a legacy codebase, moved to a startup that's AI-native. Uses Claude daily for coding. Built a few internal tools. But sees senior engineers producing 10x more with agent orchestration. Wants to understand how.
His situation: Adapts fast, no old habits to unlearn. But starting to realize the gap between using AI tools and architecting with them.
What he needs: Jump from tool user to architect. Understand how to design systems that leverage agent orchestration. The next 5 years of his career depend on getting this.
The consultant making the leap
Marcus, 27. Two years into management consulting. Noticed that colleagues who understand AI architecture win the best projects. Right now he just explains AI to clients. Wants to be the one who actually builds solutions.
His situation: Competition is real. Others are learning. He sees the window closing.
What he needs: Deep competence in agent design and MCP patterns. Enough knowledge to advise clients confidently. The technical edge that differentiates him.
The product manager who codes Sofia, 29. Product manager at a fast-growing SaaS startup. Started as an engineer, moved to product. Now the whole company is asking: how do we embed AI into our product? She gets stuck between vision and feasibility.
Her situation: She needs to understand what's actually buildable before she commits to roadmaps. Can't just ask engineers.
What she needs: Real technical depth in agent architecture. Know the constraints and possibilities. Speak the language of her engineering team with credibility.
The founder's co-builder Henrik, 26. Co-founder of a SaaS startup. His co-founder handles the business side. He handles the product. Now they're at a fork: does AI become core to their product or stay peripheral?
His situation: This decision could define the next 5 years. He needs to understand agent architecture well enough to make the call himself, not just follow trends.
What he needs: Deep understanding of what's technically possible. Know how to architect for AI at scale. The ability to separate hype from building blocks.
The data person going deeper Amelia, 25. Data analyst turned data engineer. Works at a mid-sized company. Started learning AI because it seemed like the future. Now realizes she needs to understand orchestration, not just prompting.
Her situation: She could become the person who connects data to AI systems, but only if she understands the architecture.
What she needs: Bridge from data engineering to agent systems. Know how MCPs work and how to design data pipelines for AI agents. Future-proof her career.
The fund manager learning David, 28. Works at a mid-sized investment fund. Three years in. Started using Claude for research analysis. Sees that fund managers who understand AI architecture make better decisions about where to invest. Right now he's just using tools. Wants to understand the systems underneath.
His situation: The edge in investment comes from understanding what's actually buildable. He can't just rely on engineers to explain it.
What he needs: Deep technical knowledge of agent architecture and MCP systems. Enough to evaluate AI startups properly. To understand which technical visions are realistic and which are hype.
The environment
The Portimão circuit sits on a hill in the Algarve, overlooking the Atlantic. The paddock smells of racing – rubber, fuel, adrenaline. But also sardines from lunch and salt from the sea.
Four days is a long time. That's the point.
The first days are as much about landing as learning. Leaving Sweden in April, stepping off the plane into 22 degrees, and waking to the sea breeze – it does something to the body. The tension releases. The mind opens.
Evenings are spent on outdoor terraces in the old town. Grilled fish. Local wine. Conversations that continue until midnight. Relationships are built that last long after the workshop.
What we did
Day 1: Arrival & Calibration
Afternoon – Introduction
The group gathered in the conference room with a view over the track. Cars were running test laps below while we talked.
The theme: "Why are we here?"
The answer: Those who master AI orchestration will have 100x more impact than those who just use tools. The difference between a go-kart and an open-wheel car.
Evening – Dinner in Portimão old town
No agenda. Just food, wine and conversation. Participants began to get to know each other beyond LinkedIn profiles.
Day 2: Infrastructure & Guardrails
Morning – Deep dive into MCP architecture
We went through how Shopify "MCP'd everything" – connected all internal data (Slack, code, docs) to their AI models.
Practical exercise: Participants built their own MCP servers connecting simulated company systems.
Afternoon – Roast Framework
AI agents go off the rails without structure. We introduced guardrails – systems to keep agents on track.
Track – Formula Ford
First driving session. Formula Ford is the entry to open-wheel racing, with no bodywork and mechanical feedback.
The instructor: "Driving here is different. Brake points shift. Throttle response changes. You're relearning the basics."
It's the same with AI. Working processes change when the tools change.
Evening – Barbecue by the sea
Participants shared frustrations and breakthroughs from the day.
Day 3: Skill-based work & 100x output
Morning – Skills over titles
We discussed how roles are evolving: - Designers who commit code - Salespeople who build apps - Analysts who create production-ready systems
The question: What is your role when job titles matter less than what you build?
Challenge – 100x output
Participants had four hours to produce value equivalent to a month of manual work.
Erik built a complete analysis tool with dashboard, data connections and automated reports. In four hours.
Track – Formula 3
Upgrade to F3. More power. More downforce. Smaller margins.
The instructor: "The faster you go, the more you trust the aerodynamics. At 200 km/h air pressure pushes the car down harder than gravity. You don't feel it, but it keeps you on the track."
The same applies to AI infrastructure. Scale requires solid structure.
Day 4: The Open Wheel finale
Morning – Integration
Final theory session. We tied everything together: - MCP architecture (the infrastructure) - Roast Framework (guardrails) - Agent orchestration (the control) - Process Power (mindset)
The question: What do you take home?
Afternoon – Open-wheel driving
The climax. The F3 car at qualifying pace.
Driving an open-wheel car at 245 km/h on a professional circuit is visceral. Your brain processes information faster than expected. Your body reacts before your mind catches up.
That's what future work feels like. You make decisions faster than you thought possible, not because you're smarter, but because the system around you enables it.
Closing dinner
Restaurant with a view over the Atlantic. Sunset. Certificates were handed out – both for AI orchestration and for completing the racing course.
Johan raised his glass: "Four days ago I thought AI would make me irrelevant. Now I know it's the opposite. My experience is more valuable than ever – if I use it right."
Participant reflections
> "Day 1 I felt like an impostor. Day 4 I knew exactly what I was going to build when I got home." >, Erik, Business Analyst
> "The racing metaphor isn't a gimmick. It's literally the same feeling – trusting systems you don't fully understand, and discovering they carry you." >, Johan, Tech Lead
> "The best investment my company has made in my development. And I've been on many courses." >, Sara, Product Manager
Why it works
Four days of immersion
Two days would be insufficient. The brain needs time to process complex concepts, build confidence on the track, and integrate new thinking. Most breakthroughs happen on day 3, when the nervous system has settled enough to absorb patterns rather than fight the experience.
Progression as proof
Moving from Formula Ford to F3 in three days isn't just symbolic. It proves that rapid skill development is real. Most participants arrive convinced that learning architecture takes years. They leave having experienced genuine acceleration. That conviction shapes how they approach complex problems back home.
Community in difficulty
Shared struggle accelerates connection. When you're trying to nail a racing line at 200 km/h alongside someone who's equally terrified, pretense disappears. You succeed together or fail together. That creates bonds that technical work alone never generates.
The environment
Portugal in April isn't decoration. Heat relaxes the nervous system. Being near water shifts attention. Good food matters. Remove people from their normal rhythm and the brain functions differently. Fear becomes focus instead of shutdown. That shift is when real learning happens.
Expected outcomes
Typical results include: - Participants implement agent orchestration within 90 days - Productivity increases of 3–5x are common - Many return for advanced programmes
The workshop is suitable for
- High potentials who want to become the next generation of AI architects
- Tech leads who want to combine experience with new tools
- Investment managers looking to stay ahead in a changing landscape
- Management consultants three years into their career who want to accelerate
- Product leaders at fast-growing SaaS companies facing new technical realities
- Next-generation leaders in family businesses preparing to take the helm
- Anyone who wants to turbocharge their career with AI competence
- Companies that want to invest in their most promising talent
Next steps
Ready for the next level? We're planning the next round in Portimão.
Places are limited. The track won't wait.