Don Syme, designer of F# and GitHub Next engineer, explains how AI agents are moving from individual productivity tools toward continuous, collaborative automation inside repositories. He introduces continuous AI and agentic ops, GitHub Agentic Workflows with their guardrails, and the factory and farm metaphors for managing software production.
Alex Lieberman and CJ Hess of Tenex discuss how an AI-native engineering consultancy organizes its work around outcomes, not hours. They cover story-point compensation, the MetaHarness workflow that keeps plans and decisions in Git, token economics and model choices, the gap between enterprise AI rollouts and production agents, why vertical AI and mid-tier SaaS may or may not survive, and what this means for jobs and New York's AI scene.
Oliver Kennon of SemiAnalysis argues that GPU hours are an input rather than the product, and that the operator determines how much useful intelligence those hours produce. The talk covers serving stacks, cluster security, ClusterMAX operator ratings, rental price versus production cost, relative cost-curve positioning, and what compute grades and futures can and cannot hedge.
Felipe Felisola Caso and Francesco Galletta from Monzo explain how an internal Slack agent grew from a viral emoji trigger into a teammate authoring over 10% of merged PRs and running more than 1,800 tasks a day. They attribute its speed to existing platform capabilities, an MCP gateway, a sandboxed orchestration system suited to a regulated bank, and an agent designed as a composable building block for incidents, on-call data quality and non-engineer contributions.
Jeff Crume examines Jev, a new AI approach that makes structured decisions rather than generating text, through a cybersecurity lens. He argues that confidence scores are not evidence, that AI decisions expand the attack surface, and that observability, decomposed reasoning, independent controls, and human oversight are needed before trusting them.
This episode asks whether a model described as dangerously capable is a real security problem or a marketing narrative. It uses the Astra sandbox incident as a starting point, then covers how agents are moving from chat into the browser to book, file, draw, and shop, and what that shift means for payments, advertising, and merchant data.