Sherwood Callaway of 11X discusses the architecture of "Alice," an AI Sales Development Representative. He covers the practical decision to use LangGraph for its reliability in production, the challenges of infrastructure and observability when using hosted agent platforms, and their methodology for running Evals to mitigate hallucinations by comparing generated content against source data.
The OpenAI team details the creation of a new, powerful AI agent in ChatGPT, achieved by unifying the Deep Research and Operator models. They cover its unified architecture with shared state across tools, the reinforcement learning techniques used for training, and the critical safety measures required for an agent that can take real-world actions.
Sagar Batchu, CEO of Speakeasy, discusses the pivotal shift in API development as AI agents become primary consumers. The conversation covers the rise of the Model Context Protocol (MCP), the challenges in building agent-ready APIs, and how Speakeasy provides a toolchain for creating, managing, and securing MCP servers.
Dan Shipper, CEO of Every, shares how his 15-person team operates on the bleeding edge of AI, shipping products without writing code, using a team of specialized AI agents, and pioneering new AI-first workflows. This summary covers Every's operational playbook, their AI stack, and Dan's predictions on how AI will reshape jobs, skills, and companies.
Anish Agarwal and Raj Agrawal, co-founders of Traversal, discuss how their AI agents automate root cause analysis (RCA) for critical system failures. They detail their agent's architecture, which leverages causal inference and large-scale computation to systematically find the root cause in minutes, and argue that the rise of AI-generated code makes AI-powered debugging an essential capability for modern software engineering.