Programme
Two intensive days, production-oriented.
October 27
Learn, understand, get hands-on
Setting the scene and ground rules.
From LLM to autonomous agent: architectures and production use cases.
VP: state of the art, Claude / MCP / agents product vision, enterprise-scale customer deployments.
Google (Gemini), Microsoft (Copilot), Mistral, OpenAI: a comparative framework.
Projects, Code, Skills, MCP: getting hands-on with the stack.
Mindflow, n8n, Make · Veo, Kling, ElevenLabs, Heygen · Lovable, Replit, Cursor.
Crystallizing key takeaways.
Scoping, objectives, tools, first system prompt in Claude Projects.
Enriching the prompt, adding Skills, test scenarios, iterating.
Filesystem, API, database and web search connectors.
Setting up tasks to run autonomously.
October 28
Industrialize, anchor in reality
Review of outputs produced autonomously.
Chaining in Mindflow / n8n / Make · documenting in GitHub · deploying via Vercel or Lovable.
ElevenLabs (voice) · Heygen (avatars) · Veo/Kling (video) · Midjourney/Flux (image) · producing a multi-format asset.
The cohort is welcomed at the premises of a major vendor (Google or Microsoft, subject to availability). Group transport included from the training venue.
Transport to the partner vendor's site.
Host vendor's premises, in-context demonstrations, discussions with the product teams.
Google (Gemini, Vertex AI, Agent Builder) or Microsoft (Copilot, AI Foundry) · agentic roadmap.
Agents deployed at scale, real-world feedback, ROI.
Official onboarding into the alumni community.