In this two-day masterclass by Sam Newman, you’ll examine how architecture can change and adapt, not only to enable new types of AI-assisted SDLC, but also to build AI-enabled products. You’ll also explore how to architect for uncertainty - helping give you flexibility and reduce risk as the AI landscape shifts around you.

2 Days

7-8 Dec

Architecting For AI

Architecture

To be fair, the people who abuse this term are also the people who probably fall under this category. I prefer “Agentic Programming” instead. I have pushed thousands of lines of code in production using agentic programming. Code that would have taken me months to write myself now takes merely days.

In this workshop, we’ll explore agentic programming as a disciplined engineering practice, not a toy.
Using Claude Code, I’ll show how to collaborate with AI agents to produce maintainable, reviewable, and production-ready code, without surrendering architectural control, correctness, or performance.

What Claude Code, Codex and Cursor are, how they work, and how you should use them

Designing clear agent boundaries and responsibilities.

How to turn vague intent into explicit, testable instructions.

Create plans that can run for hours on end, generating and testing code as they go.

Much more (workshop contents are constantly updated as new models and tools are released)

This is not a “let the AI take the wheel” session. It’s about teaching the AI to work like a senior engineer, while you stay firmly in charge. If you believe AI coding tools are dangerous, flaky, or fundamentally incompatible with serious software engineering, then this workshop is for you.



A laptop with your favourite IDE installed

Vibe Coding for Production

Two-day training session on AI agents, MCP, and Skills facilitated by Aleksander Stensby from GritAI. This training gives you the foundation to build MCP servers and MCP Apps, reusable agent skills, and wire everything into capable autonomous agents that actually work.

This hands-on workshop will equip you with practical skills to build your own MCP servers, CLI tool wrappers, and interactive MCP Apps — and then go further by creating reusable skills that turn simple tool-calling agents into capable, autonomous systems. You'll leave with a working agent powered by tools and skills you built yourself.

Day 1: Context & Connectivity — MCP Servers, Apps & Tools

Introduction to the AI agent stack: LLMs in a loop with tools and why context is king

Core MCP concepts: Host/client/server architecture, tools, resources, and prompts

Building a working local MCP server (Python or TypeScript)

MCP Apps: Adding interactive UI components to your MCP Server

CLI tools with direct API access as an alternative and complement to MCP

Hands-on exercises: Build an MCP server, extend it with an MCP App

What skills are and why they're the missing layer in most agent setups

Skills vs. tools vs. prompts: Understanding the capability stack

The skill creator pattern: Using AI to capture and formalise skills from workflows

Workflow capture: Turning expert knowledge into reusable agent skills

Agentic loop architecture: How LLMs, tools, and skills combine across frameworks

Provider-agnostic patterns: Claude, OpenAI, Gemini and beyond

Final exercise: Building a capable agent combining MCP tools and custom skills

Basic Python or JavaScript programming knowledge

Familiarity with AI/ML concepts (helpful but not required)

Laptop with necessary development environment

This training is targeted at developers and people with a medium+ technical skill level and interest for AI.



Bring your laptop with your preferred IDE and either Python or Node installed. We recommend an AI coding agent like Claude Code, Cursor, or GitHub Copilot.
Bring your favorite sauce! You need access to an LLM provider like Anthropic, OpenAI or Azure Foundry, but you can also use Ollama if you would like to run everything locally and free. Claude Code is highly recommended and will be used for a lot of the demonstrations during the workshop.

Context and Skills Are All Your Agent Needs

Come spend two days with me and we'll build a personal finance assistant step by step. You'll ask it questions, give it tools, let it work with your data and let it take actions for you.

We'll start with the simplest possible version: calling an LLM over HTTP.

From there, we'll look at how prompts and tokens work before adding abstractions.

You'll give the assistant tools to read data and take action, and build the loop that decides when those tools should be called.

Then we'll add agentic RAG so it can find transactions by meaning, not just exact matches.

We'll also keep conversation history, so you can ask follow-up questions without having to repeat everything.

Day 2: Prepare it for production and connect it to other tools

Long conversations eventually become a problem, so we'll summarise older messages and manage the context we send to the model.

We'll trace what the agent is doing, look at prompt injection, and add confirmation before actions that could have consequences.

Then we'll write evaluations so you can change prompts, tools or models and still check whether the agent behaves the way you expect.

You'll also build your own MCP server and use it from Claude Desktop, VS Code or another MCP client.

Finally, we'll take the agent we've built and see what it looks like using Microsoft Agent Framework, including where a framework helps and where you may not need one.

During the workshop, we'll use Microsoft Foundry. If you prefer, you can bring your own OpenAI API key. The workshop project makes it easy to switch between the two.

An understanding of the pieces behind tools like Codex, Copilot and Claude.

And, most importantly, a project you can take home, change and use as a starting point when you add AI to your own applications.

If you answer yes to these two questions, you should feel comfortable in the workshop:

Do you prefer learning by building things instead of sitting through slides and theory?

NDC { AI }

Workshops

09:00 - 17:00 (UTC+01)

Vibe Coding for Production

Nick Chapsas

Build Your First AI Agent in .NET

Gui Ferreira

Architecting For AI

Sam Newman

Context and Skills Are All Your Agent Needs

Aleksander Stensby