A practitioner's guide to building a context engine, the reasoning layer that provides AI agents with the necessary organizational context to generate effective and appropriate code. The talk debunks common myths about RAG and large context windows, outlines core requirements for a robust context engine, and shares lessons learned from production.
Liam McGarrigle demonstrates how to build secure, observable, and controllable AI agents in n8n. The workshop covers creating a human-in-the-loop workflow for managing Gmail and Google Calendar, focusing on n8n's visual system for tool configuration, prompting strategies, and implementing essential approval steps to prevent unintended actions.
As AI handles more of the coding, the role of a software engineer is shifting from writing code to planning and reviewing the work of AI agents. This talk explores the implications of this shift, the new workflows it demands, and the tools required to manage them effectively.
Max Schoening, Head of Product at Notion, discusses how AI is reshaping software development. He argues that agency—the drive to effect change—is now more critical than specific skills, as AI makes the first 10% of any project 'free'. Schoening introduces his 'tiny core' theory for great products, debates the 'SaaSpocalypse', and emphasizes the growing importance of software quality and taste in an era of exploding software quantity.
This talk outlines the challenges of AI pricing, where traditional SaaS models fail due to unpredictable compute costs and margin pressure. It presents a five-step framework for developing a successful hybrid pricing strategy, emphasizing value alignment, customer trust, and rapid iteration as key competitive advantages.
This episode explores the foundations of AI agent memory, drawing parallels with human neuroscience. It also covers the practical impact of AI on data engineering roles, the democratization of AI development through low-code tools, and innovative applications of AI in elementary education to foster critical thinking.