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title: AI Agents at work: real-time platform insights in Slack
description: Monday.com built an AI-powered Slack bot to help engineers monitor platform health and access real-time insights without leaving Slack. The solution uses LLM...
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og:description: Monday.com built an AI-powered Slack bot to help engineers monitor platform health and access real-time insights without leaving Slack. The solution uses LLM...
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# AI Agents at work: real-time platform insights in Slack

**[monday Engineering](https://daily.dev/sources/monday)** · 8 min read · 17 upvotes · 0 comments

## Summary

Monday.com built an AI-powered Slack bot to help engineers monitor platform health and access real-time insights without leaving Slack. The solution uses LLM agents connected via Model Context Protocol (MCP) to query microservice data, with LangChain handling agent logic. Key challenges included preventing LLM hallucinations by pre-computing statistics server-side rather than letting the model calculate, tuning temperature parameters to reduce randomness, and carefully scoping the bot's capabilities. The team later added human-in-the-loop approval for data modifications and supervisor agent patterns for complex workflows. The bot now saves hours by automating repetitive queries about blocked users and service status.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://engineering.monday.com/ai-agents-at-work-real-time-platform-insights-in-slack/>

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---

Tags: [#ai](https://daily.dev/tags/ai), [#llm](https://daily.dev/tags/llm), [#microservices](https://daily.dev/tags/microservices), [#slack](https://daily.dev/tags/slack), [#langchain](https://daily.dev/tags/langchain)

[View this post on daily.dev](https://daily.dev/posts/ai-agents-at-work-real-time-platform-insights-in-slack-as53pzdrz)

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