LLMOps articles
10 articles about LLMOps, newest first.
- Scheduling Managed Deep Agents with LangChain and LangSmith — Learn how to use cron syntax to automate recurring AI tasks and deliver proactive reports to Slack using LangChain's Managed Deep Agents and LangSmith.
- Lyft Boosts Agent Resolution by 16% with LangGraph and LangSmith — Learn how Lyft used LangGraph's meta-agent architecture and LangSmith's observability to cut agent build time from six months to two weeks.
- Deploying LangChain Managed Deep Agents to Slack — Learn how to move AI agents from LangSmith Studio to production using Slack as the interaction layer for team collaboration and live monitoring.
- Stop Picking Frameworks: The 14-Step Blueprint for Production AI Agents — Learn how to design robust, production-ready AI agent systems using Dr. Maryam Miradi's comprehensive 14-step architectural framework.
- Automate Your Quality Control: Using LLM-as-a-Judge with LangSmith CLI — Learn how to use the LangSmith CLI to deploy an LLM judge that automatically flags user frustration in production traces at scale.
- Stop Breaking Your AI Agents: A Guide to Evals for Managed Deep Agents — Learn how to use Harbor and LangSmith to catch regressions and systematically improve your AI agents using Managed Deep Agents evals.
- Build-Time vs. Run-Time: Stop Your AI Agents from Deleting Your Database — Learn why flexible AI dev tools fail in production and how to secure your database agents using structured run-time tools and identity separation.
- Scaling AI Observability: How Clay Monitors Millions of Agent Runs — Learn how Clay uses LangSmith to move from manual agent review to automated, large-scale monitoring using online evaluators.
- From 12 Weeks to 2: How Madrigal Pharmaceuticals Scaled AI Agents — Discover how Madrigal Pharmaceuticals used LangChain and LangSmith to slash AI deployment times and master agent observability.
- Beyond the Hype: What Actually Makes a Great AI Engineer? — Stop hiring for buzzwords. Learn the critical skills and mindsets that separate mediocre AI developers from world-class AI engineers.