This article analyzes why multi-agent handoffs often break on the second user message, comparing how OpenAI Agents SDK, LangChain, and Microsoft Agent Framework persist the current owner, transfer context, and maintain routing state across conversation turns.
The article presents a case study of separating architecture and development roles in AI-assisted programming, emphasizing decision boundaries, design baselines, deliverables, and evidence-based handoffs. It shows how architecture handles requirements and design while development implements, with gaps returned to architecture, and how mid-project changes require unified baseline updates to avoid conflicting local facts.
This article outlines a five‑stage framework for AI delivery—Discovery, Prototyping, Deployment & Co‑Running, Productization, and Handoff—explaining the purpose of each phase, common failure patterns, concrete success criteria, and how they form a repeatable map for scaling AI projects.
This article explains the Swarm collaboration model in LangGraph, contrasting it with Supervisor, detailing the handoff tool that atomically updates the active_agent state and routes control, and provides a complete travel‑booking example, custom handoff creation, common pitfalls, and best‑practice tips.
This article explains why single‑agent LLM pipelines fail when many tools are attached, introduces the Supervisor pattern that separates routing and execution across specialized agents, compares Tool‑Calling and Handoff approaches, provides a complete TypeScript implementation—including hierarchical supervisors—and lists five common pitfalls with concrete fixes.
The article examines why single‑agent setups fail, introduces the Supervisor pattern for clear responsibility separation, compares Tool‑Calling and Handoff approaches, provides a complete TypeScript implementation, explores hierarchical supervisors, and outlines five common pitfalls with concrete fixes.
This lesson explains how to extend a single‑agent system with multi‑agent collaboration, covering context isolation, Handoff and Router patterns, flat coordinator architecture, code examples, task decomposition, and practical run‑time demos for building complex AI workflows.
