Jul 28, 2026

OpenAI’s Plan to Make ChatGPT the Everything App — Akshay Nathan, OpenAI

Akshay Nathan, head of Core Product Engineering at OpenAI, discusses the journey and rationale behind ChatGPT Work. He explains how Codex's unexpected adoption by non-developers led to a unified agent harness, blurring the lines between developer and knowledge worker tools. The conversation delves into model capabilities, the role of artifacts and interactive 'Sites' in replacing traditional documents, and how AI fosters a new era of 'T-shaped' generalists. Nathan emphasizes the shift in productivity bottlenecks to 'ideas and taste' and the importance of 'quality at-bats' over mere 'motion' in an AI-powered development landscape.

Jul 11, 2026

Why AI Agents Don't Actually Understand You — Danielle Perszyk, Amazon AGI Lab

Daniel from Amazon AGI Lab details a cognitive science-driven vision for human-aligned AI, focusing on collective intelligence, real-time interaction, and redefining reliability through user mind modeling. He emphasizes aligning AI representations with human cognition to foster generalization, prevent reduced human agency, and revolutionize areas like education, advocating for diverse AI systems and frontier research over immediate productization.

Jun 15, 2026

Context Engineering for Coding Agents

A deep dive into advanced engineering techniques for coding agents, focusing on effective context management in LLMs like Claude. The talk introduces a practical framework using a brain-inspired analogy, proposing a Markdown-based 'wiki' as a long-term memory system to augment the agent's limited context window. This approach is demonstrated through a real-world challenge of extracting structured data from technical drawings.

May 01, 2026

988: In Case You Missed It in April 2026 — with @JonKrohnLearns

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.

Sep 17, 2025

Beyond Prompting: The Emerging Discipline of Context Engineering Reading Group

This summary covers a deep dive into the paper "A Survey of Context Engineering for Large Language Models". The discussion reframes the conversation from simple prompt engineering to a more systematic approach of building information environments for LLMs. It explores the foundational components of context engineering—generation, processing, and management—and their application in advanced systems like Retrieval-Augmented Generation (RAG), memory, tool use, and multi-agent systems.