Latitude releases an open-source, self-hostable agent observability tool with automated failure grouping and Claude Code telemetry · Digg

/Tech6h ago

Latitude releases an open-source, self-hostable agent observability tool with automated failure grouping and Claude Code telemetry

Story Overview

Latitude has shipped an MIT-licensed platform that ingests full traces from AI agents and turns raw conversation logs into searchable records, automatically clustered issues, and alerts when patterns repeat.

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Original post

Santiago@svpino#1889inTech

We don't need another dashboard.

Nobody has time to check a dashboard to see if their agents are working.

A dashboard is more work. It's one more thing to check, one more place to look, one more problem on my plate.

I don't want more work. Just tell me what's broken.

We need insights, not dashboards.

I'm glad these guys are focusing on giving people answers instead of building yet another dashboard.

cesar.wtf@heycesr

Most underrated data source in a company: your AI agent's conversations.

Your agent talks to more customers than any employee, but the data it generates goes nowhere.

@trylatitude changes that, see how:

8:10 AM · Jun 23, 2026 · 5.9K Views

Developer Impact

Traces become grouped issues without extra dashboards

The system clusters similar failures, shows affected users and trends, and lets teams move straight from alert to fix verification.

Setup Simplicity

One-command install pulls in Claude Code sessions

A dedicated telemetry hook captures prompts, tool calls, subagents, and per-turn costs for sessions running in the terminal, desktop app, or IDEs.

Sentiment

Many users praise Latitude's open-source AI agent observability platform for delivering production features like failure collapsing and no vendor lock-in, while one finds constant monitoring annoying.

Pos

95.0%

Neg

5.0%

20 comments with sentiment.

Cluster Engagement

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Related links

AI Agent Observability & Monitoring - Latitude

LATITUDE.SOVia

GitHub - latitude-dev/latitude-llm: Latitude is the open-source ai monitoring platform.

GITHUB

Posts from X

Most Activity

VIEWS15.1KBOOKMARKS31LIKES64REPLIES11

Chubby♨️@kimmonismus

Been waiting for someone in agent observability to do this properly. Latitude doesn't just hand you traces.

It collapses repeated failures into one issue with frequency and reason, and lets you search production conversations in plain English.

Open source, MIT licensed, self-hostable. Rare in this category. (and you know that i love open source)

If you run agents in prod, the Claude Code token telemetry is the part I'd try first.

cesar.wtf@heycesr

Most underrated data source in a company: your AI agent's conversations.

Your agent talks to more customers than any employee, but the data it generates goes nowhere.

@trylatitude changes that, see how:

5h15.1K6431

RETWEETS6

elvis@omarsar0

Very cool to see more focus on agent observability tools.

I pointed Latitude at my Claude Code setup and immediately saw which tasks were actually eating my token budget.

It's a great way to:

> See what your agent does > Catch the failures that keep repeating, with the frequency and reason > Fix them without leaving your editor

Open source and MIT licensed!

Try it free at http://latitude.so

cesar.wtf@heycesr

Most underrated data source in a company: your AI agent's conversations.

Your agent talks to more customers than any employee, but the data it generates goes nowhere.

@trylatitude changes that, see how:

4h4.3K2114

Rohan Paul@rohanpaul_ai

Agents token burn needs more visibility.

Latitude just launched an open-source, MIT licensed monitoring platform that turns AI agent conversations into production debugging data.

Most agents already talk to more users than any teammate, but those chats usually sit as raw logs, so teams miss frustration, unmet requests, repeated failures, and churn signals.

Latitude organizes that mess into a see, catch, fix loop: see sessions, users, tools, cost, latency, and behaviors; catch repeated failures through Signals; fix them from your editor through MCP.

The product is built for production agents, not just model calls, because agent quality depends on tool use, user intent, retries, cost, latency, and the gap between what the user expected and what the system did.

cesar.wtf@heycesr

Most underrated data source in a company: your AI agent's conversations.

Your agent talks to more customers than any employee, but the data it generates goes nowhere.

@trylatitude changes that, see how:

4h3.4K73

Robert Scoble@Scobleizer

Developers and builders!

Everyone is shipping agents and nobody has a clean system for seeing what they actually do in production.

@trylatitude just open sourced their monitoring platform with the see catch fix flow built in. You get clustered failure patterns, auto evals, and direct editor integration through MCP.

Self hostable or free tier. No paywall on core features because it is MIT licensed.

Try it: https://latitude.so/?utm_source=scoble&utm_medium=social&utm_campaign=latitude_v2_launch

cesar.wtf@heycesr

Most underrated data source in a company: your AI agent's conversations.

Your agent talks to more customers than any employee, but the data it generates goes nowhere.

@trylatitude changes that, see how:

36m2.9K52

Rohan Paul@rohanpaul_ai

Thier Github with 4.2k stars

https://github.com/latitude-dev/latitude-llm

Rohan Paul@rohanpaul_ai

Agents token burn needs more visibility.

Latitude just launched an open-source, MIT licensed monitoring platform that turns AI agent conversations into production debugging data.

Most agents already talk to more users than any teammate, but those chats usually sit as raw logs, so teams miss frustration, unmet requests, repeated failures, and churn signals.

Latitude organizes that mess into a see, catch, fix loop: see sessions, users, tools, cost, latency, and behaviors; catch repeated failures through Signals; fix them from your editor through MCP.

The product is built for production agents, not just model calls, because agent quality depends on tool use, user intent, retries, cost, latency, and the gap between what the user expected and what the system did.

3h89002

cesar.wtf@heycesr

@svpino you wrote our landing page lol. dashboards make you do the work, latitude does the work and just tells you what's breaking.

6h701

Alan Callahan@AphanFX

People and companies are going to fight over who owns what with your digital twin. If you work at a place for 5 years and that contact has a lot of information, who owns it, do you get to take it with you? Eventually your digital twin will be worth more than you are. I would try and use your own over a company’s system for as long as they don’t know any better, that way it stays with you no matter who you’re working for.

5h49

Alpha Batcher@alphabatcher

@kimmonismus ai agents got good upgrade today

4h45

Santiago@svpino

@heycesr More of that, please

6h34

Nura Sabo Haruna@Nursabo112

@Scobleizer @trylatitude AI agents are moving from demos to real production systems, and observability will be the difference between hype and reliable infrastructure. Open-source tools that help developers understand, debug, and improve agents are exactly what the ecosystem needs.

35m101

tan@captainntan

@kimmonismus this actually looks super useful for debugging agents, nice work

5h24

tan@captainntan

@svpino this is such a valid take, constant monitoring is annoying.

6h21

Hunter Gon@gonlenidefi

@kimmonismus the plain english search is what got me. most tools expect u to know what went wrong before u look for it

4h16

Bitplanet@Bitplanet_AI

@rohanpaul_ai Token visibility being treated as production debugging data instead of raw logs is the shift here

1h9

Hussain Hashim | Building Sunday Back@itsthedonhashim

@omarsar0 @omarsar0 tried it with my setup too. wild how much stuff you miss without these tools.

3h21

Strata@ChainZenit

@omarsar0 that actually sounds super useful for debugging token usage.

4h7

Simply AI@Simply_AI_00

@kimmonismus finally, real observability without the vendor lock-in. Open-source & self-hosted? shipping now

4h6

LucasH Sketch@dibujoslucas

@svpino just tell me what's on fire, I don't need a pretty chart about it

5h6

helicerat@helicerat0x

@kimmonismus oh the plain english search is the part I actually want

4h5

Meris Dabhi@Merisdabhi

@kimmonismus the fact that its mit licensed and self hostable is the biggest selling point honestly..

4h5