Multi agent systems

Jun 29, 2026

The Future Is Domain-Specific Agents - Justin Schroeder, StandardAgents

Justin Schroeder argues for a paradigm shift in AI agent development from monolithic, context-inflated agents (inheritance) to modular, domain-specific agents (DSAs) that operate through composition. He explains how DSAs offer superior token efficiency, cost savings with smaller models, enhanced security through capability limits, and better scalability, predicting their widespread adoption by 2027 as a solution to rising AI costs and the need for practical, customer-facing AI.

Jun 28, 2026

Building an Autonomous Engineering Org - Angie Jones, Agentic AI Foundation

Angie Jones details Block's journey in transforming its engineering organization into an autonomous one using AI agents. She outlines a five-stage AI maturity model, the strategic implementation of an 'AI Champions' program, and the technical steps taken to make repositories AI-ready and enable seamless agent delegation directly within developer workflows. The talk covers challenges in scaling multi-agent parallelism, including code review bottlenecks and resource management, and the development of an orchestrator ('Builder Bot') and 'Company World Model' to achieve full autonomy. It concludes with a critical reflection on the ethical implications of achieving such high levels of AI-driven automation.

Jun 26, 2026

Builders Unscripted: Ep. 4 - Pietro Schirano

Pietro Schirano, Founder & CEO of MagicPath, discusses his pioneering work with GPT-5.5 and Codex, transforming creative ideas into software and hardware solutions. He details using advanced AI for image-to-sound conversion, multi-agent workflows, resurrecting obsolete tech with new functionalities, and building his company, MagicPath, on the principle of humans directing AI agents. This interview provides deep insights into the creative potential and practical applications of cutting-edge AI for developers and entrepreneurs.

Jun 18, 2026

The Production AI Playbook: Deploying Agents at Enterprise Scale — Sandipan Bhaumik, Databricks

Sandipan Bhaumik presents a five-pillar framework for successfully moving AI systems from demos to production, inspired by a retail bank's failed chatbot PoC. The framework covers defining numerical success (Evaluation), tracing every AI decision (Observability), building robust data pipelines (Data Foundation), managing multiple AI interactions (Multi-agent Orchestration), and ensuring accountability and security (Governance). He illustrates these concepts with a banking chatbot case study, emphasizing continuous evaluation, data quality, and a proactive incident playbook.

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.

May 25, 2026

Scaling Meta's Multi-Agent Systems to a Billion Videos

Meta's approach to solving modality misalignment and content theft in short-form video using a multi-agent system of smaller, specialized models instead of a single large LLM. The talk covers the architecture (Perceiver, Retriever, Reasoner), evaluation stack, and key cost-saving optimizations.