How Monday.com Built Sidekick on Deep Agents | Interrupt 2026

Description

Omri Bruchim, engineering manager at monday.com, walks through the full journey of building Sidekick — monday.com's intelligent personal assistant — from a simple LangChain React loop all the way to a production-grade agentic system powered by Deep Agents. He covers the real scaling failures that forced a rebuild, and the four engineering principles that got them to a 94% error recovery rate in production. Chapters: 0:00 Introduction and what we're covering today 0:31 About Omri and the monday.com AI platform 1:25 monday.com's mission shift: from managing work to doing the work 2:02 The SDR agent and job recruiter agent demos 2:22 The monday.com product suite: Monday Agent, AI Apps, and Sidekick 2:39 What Sidekick actually does 3:06 Sidekick V1: the LangChain ReAct loop that started it all 3:54 Why V1 broke: 200 tools, infinite context, context pollution 4:37 Why they chose Deep Agents to rebuild from scratch 6:55 Core philosophy: one smart orchestrator, not a swarm 7:41 The four principles — overview 7:44 Principle 1: Deferred tool discovery (the three-tier system) 9:55 Principle 2: Delegation first — sub-agents and async handoff 11:03 Delegation first — the middleware pipeline 12:04 Principle 3: The code-writing tool and LangSmith sandbox 13:04 Real-world example: finding a London office with live code 13:42 Principle 4: Self-healing with 94% recovery success rate 15:07 What's next for Sidekick 15:26 Takeaways for building with Deep Agents Resources: → Deep Agents: https://www.langchain.com/deep-agents → LangSmith: https://www.langchain.com/langsmith → LangChain Academy: https://academy.langchain.com → monday.com AI platform: https://monday.com/ai