A practical, end-to-end bootcamp for building real-world generative AI applications — from concept to deployment. By day's end every participant walks away with a working GenAI app running on their own machine, ready to extend and ship to production.
An immersive, hands-on technical bootcamp designed for engineers who want to dive into the AI era. Participants learn LLM fundamentals, set up local models with Ollama and LM Studio, and build their first generative AI web application using TypeScript, the Vercel AI SDK, Next.js and Shadcn UI components.
The session covers Retrieval-Augmented Generation (RAG) and tool integration, empowering attendees to code and deploy their own GenAI apps in a single day — all running on their local machines.
A guided path from first principles to a deployed application — each block builds directly on the last.
A clear overview of the agenda, objectives and outcomes. We set the context of the AI era, align on terminology, and establish a shared understanding of how generative AI is reshaping products and engineering workflows.
Demystifies Large Language Models — how they are trained and how they generate responses. Tokens, context windows, temperature, prompting techniques and common use cases build a strong conceptual foundation.
Install and configure a local LLM with Ollama or LM Studio, run your first inference, and compare models — covering performance, privacy benefits and the trade-offs between local and cloud.
Deliverable · Working local LLM on your laptopBuild GenAI backends with TypeScript and the Vercel AI SDK. Explore SDK architecture, API patterns, streaming responses and prompt engineering while creating your first working GenAI application.
Deliverable · Hello-World GenAI app with streamingBuild a modern frontend with Next.js and shadcn/ui — project structure, reusable components, UI/UX best practices, state management, and connecting the frontend seamlessly to your AI backend.
Deliverable · Functional chat UI scaffold + stateThe fundamentals of Retrieval-Augmented Generation — embeddings, vector databases and retrieval workflows — plus tool calling and basic agentic patterns for reliable, context-aware AI applications.
A guided lab to complete your GenAI application by integrating the local LLM, RAG pipeline and tools — ending in deployment and validation of a fully working end-to-end application.
Deliverable · Deployed GenAI app, all features liveSelected participants present their applications live, showcasing different approaches and use cases. The session closes with feedback, awards and open networking to strengthen the community.
Deliverable · Recognition & community buildingThe Gen AI Bootcamp brings together engineers, technical product managers and tech leaders from across Europe to focus on building and deploying real-world generative AI applications.
Over one day you'll gain hands-on experience, explore proven architectures and workflows, and create working GenAI applications — no theory overload, just practical, deployable skills. If you want to build production-ready AI systems, master local-first and full-stack GenAI workflows, and position yourself at the forefront of AI-driven innovation, this bootcamp is for you.
Agenda, objectives and outcomes — setting the context of the AI era and aligning on shared terminology.
How LLMs are trained and generate responses — tokens, context windows, temperature, prompting and use cases.
Install Ollama / LM Studio, run first inference, compare models, weigh local vs cloud trade-offs.
SDK architecture, API patterns, streaming responses and prompt engineering — your first working GenAI app.
Modern frontend with reusable components, state management and a chat UI wired to your AI backend.
Embeddings, vector databases and retrieval workflows, plus tool calling and basic agentic patterns.
Integrate local LLM, RAG pipeline and tools, then deploy and validate a working end-to-end application.
Live participant demos, feedback, awards and open networking to close the day.
Missed the bootcamp? Catch the sessions on demand, then keep going — bring these GenAI engineering skills into your team with a corporate program, or upskill on your own with an individual training path.