Ai agents

How We Solved Agent Building — Andrew Qu, Vercel

How We Solved Agent Building — Andrew Qu, Vercel

Andrew Qu, Chief of Software at Vercel, details the year-long journey of building an internal data science agent, from its initial "awful" state to the release of Eve, a framework for agent development. He covers iterative architectural improvements, the critical "file system unlock" inspired by Claude Code, and the distillation of common queries into reusable "skills," culminating in a framework that simplifies the creation of specialized, company-specific AI agents.

No Memory, No Harness: Why the Database Is the Last Line of Defense — Kay Malcolm, Oracle

No Memory, No Harness: Why the Database Is the Last Line of Defense — Kay Malcolm, Oracle

Kay Malcolm discusses how AI, while boosting individual performance, often hinders overall team productivity due to fragmented context. She introduces the concept of an "agent harness" with "memory" as its central nervous system, vital for sharing context. Drawing on personal experiences with database sprawl, she highlights the inefficiencies of storing diverse memory types across multiple data stores. Malcolm then presents Oracle's AI database (26AI) as a unified solution, capable of natively managing all memory types in a single platform, thereby enhancing team collaboration and solving the context problem for enterprise AI agents.

Greg Brockman Says AGI Has Arrived

Greg Brockman Says AGI Has Arrived

OpenAI President Greg Brockman discusses the advent of the "AGI era" with models like Astra, highlighting the transformative power of AI agents capable of computer use and autonomous task execution. He delves into critical safety and security challenges, emphasizing the "defender's window" for proactive cybersecurity, and explores AI's evolving impact on employment, global sentiment, and the future of proactive AI assistants.

How Developers Secure AI-Generated Code: 5 Security Best Practices

How Developers Secure AI-Generated Code: 5 Security Best Practices

Discover five essential principles for implementing shift-left security in AI-assisted software development. Jeff Crume explains how to secure AI-generated code by focusing on outcome validation, integrating security early, scrutinizing dependencies, validating intent, and maintaining continuous security practices for more trustworthy AI-powered workflows.

Essential Skills for Becoming an AI Engineer: RAG, AI Agents, & More

Essential Skills for Becoming an AI Engineer: RAG, AI Agents, & More

Cedric Clyburn outlines the essential skills for AI engineering, distinguishing it from ML research. He details a three-tier skill stack covering foundational programming (Python, Git, APIs), AI-specific techniques (embeddings, RAG, AI agents), and deployment strategies (containerization, observability). The discussion emphasizes judgment over code generation and highlights key use cases like RAG systems and agent-based solutions.

OpenAI talks GPT-6 Astra and Millenium Prize, researchers create WeWorm exploit & IBM’s US Open app

OpenAI talks GPT-6 Astra and Millenium Prize, researchers create WeWorm exploit & IBM’s US Open app

This episode explores OpenAI's groundbreaking GPT-6 Astra model and its resolution of the Navier-Stokes equation, the AI-powered fan experiences developed by IBM for the US Open, and the concerning implications of AI-assisted cybersecurity threats like the WeWorm zero-click exploit.