메모: Agents automate real-world work, but reliable performance requires more than a good model, it requires a carefully designed harness built for specific tasks. This post explores the core agent loop, how stacking and extending loops builds mo
메모: LangSmith Engine watches your production traces, clusters failures into named issues, and proposes targeted fixes and eval coverage. Stop manually triaging agent failures.
Agentic Engineering: How Swarms of AI Agents Are Redefining Software Engineering
메모: Multi-agent systems that mirror real engineering teams — not just code faster — can cut debug time by 93% and compress cross-team delivery. Here’s the architecture built on LangGraph.
Why the Best AI Agents Are Simple: Sierra’s Zack Reneau-Wedeen on the Max Agency Podcast
메모: On the Max Agency Podcast, Harrison Chase and Sierra’s Zack Reneau-Wedeen sat down to explore the future of AI agents. Learn why simple architectures, outcome-based pricing, and avoiding “org chart shipping” are the keys to building high-pe
메모: Running code execution in an AI agent is harder than it looks. Your agent needs a real computer (filesystem, shell, package manager, persistent state) but handing it access to your infrastructure is dangerous.Think about it this way: you us