ONLY UNTIL JULY 31: ✓ Save up to £525 ✓ 4-Day Special ✓ Team Discount

ONLY UNTIL JULY 31: ✓ Save up to £525 ✓ 4-Day Special ✓ Team Discount

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

EARLY BIRD SPECIALS END IN:

Take home working code in Python, Java, TypeScript, and C#
to use in your next AI project.

Deep dive intoTransformers, RAG, & Agentic Systems,
all hands-on coding

Meet The Mastermind

John Davies

After a degree in Astrophysics at UCL John started in hardware then assembler, C, C++ and later Java. Almost exclusively in finance he ran FX at Paribas 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
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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
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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, mutli-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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