Day 1: Foundations, Agents, Build on Agentic Security: Build, Audit, Break

Module 1: LLM Fundamentals

Mon, 01 Jan 0001 00:00:00 +0000

Module 1: LLM Fundamentals#

What is an LLM, actually? In this module, we’ll discuss tokens, weights, context, and more. You should come away with a deeper understanding of LLMs and associated technology.

Questions this module answers#

What actually happens when I send a prompt to an LLM?
What are tokens, weights, and sampling?
Why is “LLMs are glorified autocomplete” both accurate and misleading?
What is a context window?
Is the LLM inference API stateful or stateless?
What is prompt caching?
What’s the difference between a system prompt and a user message?
How do I pick a model?
Why do alignment and refusals matter for security work?

Slides#

Your browser can't display the PDF inline. Download the slides.

Module 2: Agents

Mon, 01 Jan 0001 00:00:00 +0000

Module 2: Agents#

It’s surprisingly simple to go from a chatbot to a powerful agent that can act in the world. This module covers the mechanics of tool-calling, what a harness is and how a typical one (Pi) works, and ways to build your own: skills, custom tools, MCP servers, subagents, and extensions.

Questions this module answers#

What turns a chatbot into an agent?
What is a tool and what happens when an agent calls one?
What is a harness and what can it do for me?
How much autonomy should I give an agent, and what risk do I take when giving it too much?
What is MCP, and when should I use it?
How do skills, custom tools, MCP servers, and subagents change what an agentic workflow can do?

Slides#

Your browser can't display the PDF inline. Download the slides.

Module 3: Agentic Coding

Mon, 01 Jan 0001 00:00:00 +0000

Module 3: Agentic Coding#

Use agents to write real code and learn how to make them work for you: planning, breaking things down, and verifying as much as possible, in a tight loop.

Questions this module answers#

What workflow reliably gets good code out of an agent?
Where does AI-generated code fail on security, and are the failures predictable or preventable?
How do I steer an agent toward secure code, and how far does that get me?
What model tiers should I use for what?
Who is accountable for code an agent wrote?

Slides#

Your browser can't display the PDF inline. Download the slides.