Aug 13, 2026

When to Build Your Own Agent Harness | Harrison Chase, LangChain

Harrison Chase, co-founder of LangChain, delves into the critical role of the 'harness' in LLM agents, explaining how it orchestrates models and context. He covers customizing harnesses with middleware and sub-agents, the trade-offs between off-the-shelf and custom solutions for in- and out-of-distribution tasks, and the importance of evaluations and observability for continuous agent improvement. The discussion culminates in the 'data flywheel' concept and the `LangSmith Engine` for automating agent intelligence through iterative refinement.

Jul 09, 2026

Agentic AI Frameworks Explained: Workflows, Multi-Agent, & Production

This video tackles the overwhelming choice of agentic AI frameworks by categorizing projects into five types: linear workflows, autonomous multi-agent systems, role-based AI, production orchestration, and rapid prototyping. It details each type with examples and recommends specific frameworks like LangChain, AutoGen, and CrewAI, guiding developers to select the optimal tool based on their system design and real-world needs.

Jan 21, 2026

Context Engineering Our Way to Long-Horizon Agents: LangChain’s Harrison Chase

Harrison Chase, co-founder of LangChain, explains the evolution of AI agents from early, rigid scaffolding to modern, flexible "harnesses." He argues that "context engineering"—managing what an LLM sees—is the key to building effective long-horizon agents. Chase also explores how agent development differs from traditional software, highlighting the critical role of traces as the new source of truth and memory systems that enable agents to improve themselves over time.

Nov 10, 2025

Prompt Engineering for LLMs, PDL, & LangChain in Action

Martin Keen explains the evolution of prompt engineering from an art to a software engineering discipline. He introduces LangChain and Prompt Declaration Language (PDL) as tools to manage the probabilistic nature of LLMs, ensuring reliable, structured JSON output through concepts like contracts, control loops, and observability.

Sep 29, 2025

Underwriting Assist - A Multi Agent System // Somya Rai | Maria Zhang // Agents in Production 2025

Maria Zhang, CEO of Palona AI, and Somya Rai, Principal AI Engineer at EXL, discuss the architecture, scaling, memory management, and cost optimization of multi-agent systems in their respective domains of restaurants and insurance. They explore practical challenges, such as real-world bottlenecks and regulatory compliance, and share their technical stacks, including LangGraph, Ray, and NVIDIA platforms, for building robust and efficient agentic solutions.