How our GTM Agent builds consistent, high-quality sales artifacts
Learn how LangChain built GTM Agent on Deep Agents to build high-quality, custom sales artifacts trained on business context.
11 of 800 posts
Learn how LangChain built GTM Agent on Deep Agents to build high-quality, custom sales artifacts trained on business context.
See how Workday used LangGraph and LangSmith to build an internal AI agent platform that cut prototype time from months to less than a day and compliance needs.
Eval-driven development helps you build AI agents against a consistent set of metrics. Define good behavior, write the eval first, then compare experiments.
LangSmith Bring Your Own Cloud is now generally available on AWS, giving Enterprise teams managed observability, evaluation, and deployment inside their own VPC.
Automate prompt engineering with Promptim's optimization library. Save time, improve AI performance, and switch models faster.
Dosu uses evaluation driven development and LangSmith to build reliable LLM products at scale, monitor production performance, and iterate with confidence.
Learn how Stripe built Kai, a company-wide AI agent on LangChain, LangGraph, and Deep Agents, reaching 5,000 users in roughly 4 weeks.
Async subagents let an agent stay responsive while background workers run long tasks. How the orchestrator, notifications and approvals work in Deep Agents.
LangSmith BYOC now runs on AWS (GA), Azure and Google Cloud (Beta). Your traces, evals, and agent deployments stay in your cloud account while LangChain runs it.
Explore 3 principles for effective human-in-the-loop workflows and how human-review is a strategic imperative for production-ready agents.
We compared seven browser toolsets for Deep Agents, picked Stagehand from Browserbase, and tuned it with LangSmith traces and evals. Here's what we learned.