A practitioner's guide to deploying a text-to-SQL agent in a real-world business environment. The talk covers the critical lessons learned in moving from concept to production, focusing on the importance of the communication channel (Slack), the necessity of a semantic layer over benchmark scores, and a pragmatic approach to system architecture, testing, and evaluation.
This talk explores the frontier of affective computing in AI agents, proposing a new architecture where emotion is a first-class component. It covers the technical challenges of deploying multi-modal, emotion-aware systems in production—from memory and learning to multi-agent orchestration—and delves into the critical ethical considerations of privacy, manipulation, and scientific validity.
The hosts explore the dawn of an agent-driven economy, spurred by tools like OpenClaw and social platforms like MoltBook. They discuss the critical shift for developers to build tools that AI agents, not just humans, will choose, focusing on the new go-to-market strategies, the rise of swarm intelligence, and the essential infrastructure required for this new paradigm.
Vitor, co-founder of Runlayer and former tech lead for Zapier Agents, provides a deep dive into the security vulnerabilities of the rapidly adopted MCP standard for AI agents. He outlines the primary attack vectors, including sophisticated prompt injections, supply chain attacks like 'rug-pulls', and tool schema manipulation, using real-world exploits as examples. The talk concludes with a multi-layered defensive strategy for users, developers, and enterprises to secure their AI agent deployments.
Ricky Doar, VP of Solutions at Cursor, shares best practices for leveraging AI in software development, focusing on effective problem decomposition, context management, and navigating both new and legacy codebases. He highlights common anti-patterns, such as over-reliance on AI, and offers strategies for debugging, model steerability, and building effective agent harnesses.
A technical guide on migrating ML experiments from Neptune to Weights & Biases, covering the migration script, API-level code changes, and best practices for organizing projects and analyzing results in the W&B platform before the Neptune sunset.