Master Practical Generative AI Skills
Go from tokens to agents with the ex-Visa Chief Architect
behind Fortune 500 AI systems
September 29 - 30, 2025 | London or Online
behind Fortune 500 AI systems
September 29 - 30, 2025 | London or Online
CONFERENCE STARTS IN:
Meet The Mastermind
John Davies
After a degree in Astrophysics at UCL, John started in hardware, then moved on to assembler, C, C++, and later Java. Almost exclusively working in finance, he ran FX at Paribas and was a global chief architect at JP Morgan, BNP Paribas, and Visa. John has co-founded four successful startups since 2000, selling one of them twice to Nasdaq & LSE listed companies. After co-founding Velo Payments with the former president of VISA, John has spun off the AI company Incept5. John has co-authored several Java books and is a frequent speaker at technical and banking conferences around the world. He is married to a French wife and has three boys in their 20s.
5 Reasons to join
the Bootcamp
Learn From Industry Veteran John Davies
Ex-Chief Architect at Visa, JP Morgan and BNP Paribas
Hands-on with practical code examples
across multiple languages that you can immediately apply to your projects
Master the Critical RAG
pipeline that powers modern AI applications with company data
Generate & Control Structured Outputs (JSON, XML)
from natural language for seamless integration with existing systems
Cut Through The Hype
learn what actually works and what doesn’t in Gen-AI, learn what’s actually being used today
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5 Things You’ll Finally Feel Confident Doing
- Build and deploy multi-modal, multi-lingual AI systems using both local models (Llama, Mistral, Qwen etc.) and cloud services with optimized performance
- Design effective prompts that consistently produce high-quality, structured outputs from any LLM
- Implement complete RAG pipelines with proper chunking, embedding, and vector storage techniques
- Generate and control structured outputs (JSON, XML) from natural language for seamless integration with existing systems
- Develop agentic systems that can reason, use tools, and solve complex problems autonomously
Differentiation from other workshops at the conference
- Focused on practical implementation rather than theoretical concepts
- Covers multiple programming languages instead of being language-specific, you can work in your preferred language
- Balanced approach to both local and cloud models, not advocating for a single vendor
- Comprehensive end-to-end coverage from fundamentals to advanced topics like agentic systems
- Includes live coding and debugging sessions with take-home templates
Bootcamp Day 1
Kick-Off & Intro
- Welcome from John Davies (ex-Chief Architect at Visa, JP Morgan and BNP Paribas)
- Overview of the day: bridging AI & Gen-AI theory with live coding, deep technical dives, and real-world integration
AI Fundamentals – How Transformers & Tokenisation Really Work
- Neural networks (classic AI) vs. Generative AI & LLMs
- Deep dive into tokenisation, embeddings, transformers, and attention mechanisms
- Live demo: Running LLMs (Text, Chat, Instruction, Vision, Speech) locally, remotely, and in-cloud
Hands-On with Local, Remote & Cloud Models
- Installing and using local models (e.g., Llama, Qwen, Mistral, Gemma)
- Live coding: Encode/decode text in Python, inspect token IDs, tune parameters (batch size, context window, temperature)
- Code samples provided in C, C#, Java, TypeScript, Python and others
- Examples for local, remote, and cloud deployment
Prompt Engineering & Model Configuration
- Understanding model parameters – temperature, context windows, top-k, top-p etc.
- Techniques for effective prompt design and output control
- Live coding: Build a Python tool that outputs structured JSON for summarisation/data extraction
- Best practices for prompt debugging and iterative refinement
- Share debugging tips and optimisation hacks with fellow devs
RAG – Retrieval-Augmented Generation
- Chunking, embedding, parsing, and vector storage
- RAG optimisation strategies
- Hands-on RAG – bring your own data!
- Advanced chunking, embedding techniques, and vector DB options
Bootcamp Day 2
Summarisation, Data Extraction & Sentiment Analysis
- Reduce document size, reformat or translate content
- Extract meaning, sentiment, and key data from raw text
- Hands-on
Structured Output with LLMs
- Techniques for consistently generating structured JSON and other formats from natural language input
- Hands-on
Code Generation Techniques
- How code generation really works
- Complete, insert (fill-in-the-middle), and instruct modes
- Exploring specialist coding models
- Hands-on
Tool Calling & Model Component Protocol (MCP)
- How to call tools with LLMs
- Building and orchestrating MCPs
Agentic Systems in Action
- What are agentic systems?
- A walkthrough of a basic agentic flow
MCPs
- The MCP architecture
- Building MCP services, servers and clients
- Running MCPs on any model
Q&A & Wrap-Up
- Ask questions, share feedback, or pitch your own AI ideas
- Where to go next: further learning and project suggestions
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*incl. 10% Team Discount when buying 3 or more tickets
