New: SwirlAI on YouTube + Context Engineering Workshop
Hands-on AI engineering content, now in video form, plus a live workshop on context engineering this Friday
SwirlAI YouTube Channel is Live
I have officially launched a YouTube channel. The first four videos are already up as a free pre-course for the End-to-End AI Engineering Bootcamp.
One thing I see consistently: people jump straight into building with LLMs without a proper development environment. They run everything locally with no containerisation, hardcode API keys, and tangle frontend and backend logic together. It works until it doesn’t. When they need to collaborate, deploy, or debug, everything falls apart.
A solid development setup is not optional for AI engineers. It’s the foundation everything else builds on. These four videos walk you through it from scratch:
Part 1: Setting Up Your Development Environment Configure your development environment and LLM API keys from scratch.
Part 2: Build and Containerise Your First Chatbot Build a Streamlit-based chatbot and deploy it with Docker Compose.
Part 3: Moving the Agent Behind a FastAPI Server Extract the LLM calling logic into a FastAPI REST server and run it as a separate service.
Part 4: Containerising Backend and Frontend Split the application into separate FastAPI and Streamlit containers, each deployed independently via Docker Compose.
By the end of the four videos, you have a clean separation between frontend, backend, and LLM logic, all running in containers. This is the foundation the full bootcamp builds on.
The videos are designed to be accessible to anyone with basic programming knowledge. You don’t need to be a software engineer. If you’re a technical PM, data analyst, or someone moving into AI from an adjacent role, this is a practical starting point to understand how AI applications are built and deployed.
More videos are coming in the upcoming weeks. Subscribe to the channel so you don't miss them.
All code is available on GitHub:
The full bootcamp syllabus and registration:
Apply code LASTCHANCE15 at the check-out for 15% off.
Free Workshop: State of Context Engineering in 2026
On Friday, March 20 I’m running a 45-minute workshop about context engineering.
Most agent failures come from poor context engineering, not weak model capability. Teams overload prompts with instructions, tools, and retrieved information. The result: brittle systems that are costly and difficult to scale.
In this session, I’ll cover:
Core patterns shaping context engineering in 2026: how teams give models the right information at the right time
Tradeoffs between context strategies, compared across accuracy, latency, token cost, maintainability, and reliability
Practical application: using routing, progressive disclosure, and modular capabilities to build agents that are more efficient and reliable
If you’ve been following the recent newsletter on Agent Skills and progressive disclosure, this session connects directly to those ideas and goes broader.
Register for the webinar here: