Apr 09, 2026

How AI Agents Will Transform the Financial System with Circle Co-Founder and CEO Jeremy Allaire

Circle CEO Jeremy Allaire delves into how programmable money and the Arc blockchain will power the emerging AI agentic economy. He explains how stablecoins like USDC offer an internet-native financial infrastructure for micro-transactions and large settlements, addressing the limitations of traditional banking for AI agents. The discussion covers the foundational principles of full-reserve banking, the unique attributes of Arc blockchain for machine-driven economic activity, the tokenization of real-world assets, and a bold vision for AI's potential to drive double-digit GDP growth and foster new on-chain organizational structures within the next decade.

Apr 08, 2026

From Neural Networks to Digital Brains: The Next Leap in AI • Daniel Lütgehetmann • GOTO 2025

Daniel Lütgehetmann of inait introduces "digital brains," biologically accurate computational models of real brains, as a solution to current AI's limitations in physical world interaction. Unlike traditional AI that struggles with dynamic environments and skill accumulation, these digital brains leverage biologically inspired learning rules to achieve dramatically faster learning in robotics and complex systems, demonstrating potential for real-world adaptability and efficiency.

Apr 08, 2026

From Chaos to Choreography: Multi-Agent Orchestration Patterns That Actually Work — Sandipan Bhaumik

Sandipan Bhaumik from Databricks explains that scaling from one to many AI agents is a distributed systems problem, not an AI one. He details common architectural anti-patterns like shared mutable state that cause race conditions and silent failures. The talk provides a practical framework based on distributed systems engineering, covering crucial patterns like choreography vs. orchestration, immutable state management with versioning, data contracts, and failure recovery using circuit breakers and compensation (Saga) patterns. Bhaumik illustrates how to build a robust, production-grade multi-agent architecture using tools like Databricks, LangGraph, and MLflow.

Apr 08, 2026

Cognitive Exhaust Fumes, or: Read-Only AI Is Underrated — Šimon Podhajský, Head of AI, Waypoint

A deep dive into a "read-only" personal AI system that analyzes your digital footprint—or "cognitive exhaust fumes"—from sources like email, notes, and browsing history. The author argues that this observer approach provides more profound insights and is inherently safer than action-oriented AI agents, by preventing data contamination and mitigating the high-stakes risks of write-access errors.

Apr 08, 2026

Platforms for Humans and Machines: Engineering for the Age of Agents — Juan Herreros Elorza

This talk by Juan Herreros Elorza explores how to design internal developer platforms for a future where AI coding agents are first-class users. It argues that the same best practices that make platforms accessible to humans—self-service interfaces, well-defined APIs, local-first workflows, and rich observability—are now critical prerequisites for agents to autonomously build, debug, and ship software. The session provides concrete principles for platform design, discusses how to manage AI-assisted contributions, and emphasizes the need to measure the impact of these changes on developer productivity and system reliability.

Apr 08, 2026

Your Insecure MCP Server Won't Survive Production — Tun Shwe, Lenses

Lenses.io experts Tun Shwe and Jeremy Frenay discuss the significant security and design hurdles in transitioning Model Context Protocol (MCP) servers from local development to enterprise production. They introduce five core principles for secure agentic design, including shrinking the attack surface and constraining inputs, and detail the necessity of remote MCP servers with robust authentication. The talk provides an in-depth comparison of OAuth 2.1's Dynamic Client Registration (DCR) and the more secure Client ID Metadata Document (CIMD) approaches for managing agent identities, offering a roadmap for building enterprise-grade agentic AI systems with MCP.