May 03, 2026

Context Is the New Code — Patrick Debois, Tessl

Patrick Debois argues that as AI coding agents become more capable, the context that drives them—prompts, rules, and memory—needs its own engineering discipline, akin to how we manage code. He introduces the Context Development Lifecycle (Generate, Evaluate, Distribute, and Observe) to make context a shared, repeatable, and improvable part of software delivery, creating a flywheel effect where better context leads to better agent output and continuous improvement.

May 02, 2026

Human-in-the-Loop Automation with n8n — Liam McGarrigle

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.

May 02, 2026

I Gave an AI Agent the Keys to My Life (Here's What Happened) — Radek Sienkiewicz, Velvet Shark

A deep dive into the practical, long-term experience of giving a personal AI agent (Open-Claw) incremental control over one's digital life. The talk covers the gradual "permission creep," the pivotal role of an Obsidian knowledge base for providing context, the ecosystem of overnight cron jobs for self-maintenance, and the philosophy of using an agent to "optimize for your future self."

May 02, 2026

Software Engineering Is Becoming Plan and Review — Louis Knight-Webb, Vibe Kanban

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.

May 02, 2026

Why cultivating agency matters more than cultivating skills in the AI era | Max Schoening (Notion)

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.

May 02, 2026

How RAG, GraphRAG, and Context Engineering Improve AI Performance

Martin Keen explains that context, not model intelligence, is the biggest bottleneck in AI. He introduces Context Engineering, its four pillars (Connected Access, Knowledge Layer, Precision Retrieval, Runtime Governance), and advanced techniques like GraphRAG to build more reliable, context-aware AI systems.