AI Agent Autopsy - Frameworks & Harnesses

AI Agents are being discussed with reckless abandon, they are touted as both the solution to all problems and the end of humanity. Every day we are waking to news about phenomenal new abilities or corporate disasters.
All of which makes it difficult to understand what they really are, and where they should be used.
In this talk we will go through the spectrum of kinds of AI Agents led by John Hawkins - Chief Ai Officer || Machine Learning Researcher. We will discuss the historical ideas in AI research that led to the current idea of an AI Agent. We will then start to pull apart the programming pieces and take a look at the innards of an AI Agent to understand how they are built and where their abilities and flaws come from. We will discuss the reasons why we should build an agent and the potential issues you will encounter. Expect to hear about a range of agentic coding frameworks such as LangGraph, Pydantic AI, Crew AI and the OpenAI Agent SDK.
We finish the talk by diving into the innards of the more autonomous agentic applications like Claude Code and OpenClaw to pull apart the components that make up an Agent Harness.
About John:
John Hawkins, Chief AI Officer at Intersect AI, where he helps organisations unlock value through bespoke AI solutions.
John brings over 20 years of experience applying machine learning, statistics, and data science across a wide range of industries - from finance and insurance to media and biomedical research.
He has built real-time predictive systems for customer engagement, fraud detection, and scientific applications, and has published 30+ peer-reviewed research papers.
He is the author of the upcoming book Data Science First: Building AI Powered Applications With Language Models (Wiley, 2026), and previously wrote Getting Data Science Done.
John also contributes to ongoing research with the Pingla Institute and the Transitional AI Research Group at UNSW.