Jun 21, 2026

⚡️Every product of the future will be a living system — Ronak Malde, Trajectory.ai

Ronuk Malde, CEO of Trajectory.ai, discusses his journey from building AI coding agents at Windsurf to his current focus on continual learning for enterprise AI. He shares insights on leveraging real-world user data, the unique challenges of model acquisition, and how Trajectory.ai's platform, powered by innovations like scaled SDPO and a novel training stack, enables dynamic, always-learning AI models for diverse industries from legal to finance.

Jun 19, 2026

Microsoft’s new AI models & bots dominate the internet

This episode explores how AI agents now dominate web traffic, the implications for content and advertising, Microsoft's new foundation models (MAI-Thinking-1 and MAI-Image-1) focusing on safety and cost efficiency, and the emergence of AI-generated films at the Tribeca Film Festival, debating AI's role as a creative tool and its impact on the future of art.

Jun 17, 2026

AI agents can manage your passwords. Should we let them? Plus: The biggest Patch Tuesday ever.

This episode of Security Intelligence delves into three critical cybersecurity topics: the implications of AI agents managing passwords, the impact of AI on vulnerability discovery and "Patch Tuesday" volumes, and the C-suite's evolving appetite for cyber risk in pursuit of innovation. Experts discuss the promises, pitfalls, and necessary strategic shifts in an AI-driven security landscape.

Jun 09, 2026

[404] – Developer Not Found: The Continuing Developer Evolution • Derek Bingham • YOW! 2025

Derek Bingham explores the rapid evolution of developer tools with AI, from coding assistants to autonomous agents. He emphasizes the shift from prompt engineering to context engineering, introduces Spec-Driven Development (SDD) as a framework for quality AI-generated code, and dispels fears about AI replacing developers, arguing instead for increased demand and the necessity of new skills like ethical and systems thinking.

Jun 09, 2026

Building AI Agent Systems and Scaling Challenges in Agentic AI

Scaling agentic AI systems presents unique challenges beyond traditional software scaling. This summary explains why expanding a single agent's capabilities leads to non-linear increases in cost, latency, and failure propagation. The talk frames this as a systems design problem solved by moving from a monolithic agent to a multi-agent architecture with distributed responsibilities, and it explores the critical architectural trade-offs between horizontal and vertical scaling of agent capabilities.

Jun 05, 2026

Building Agent Interfaces: Lessons from Chrome DevTools (MCP) for Agents — Michael Hablich, Google

Michael Hablich from the Chrome DevTools team shares hard-won engineering lessons on building effective and secure interfaces for AI agents. The talk covers moving from raw data to semantic summaries, measuring interface efficiency with 'tokens per successful outcome', designing for error recovery, and the critical importance of trust boundaries and deliberate friction in UI design for agents.