Most AI agent failures are invisible until users complain. Sentrial detects loops, hallucinations, and user frustrations in real time and helps engineering teams diagnose and fix issues fast. Production monitoring built for AI agents. Congrats on the launch Neel Sharma and Anay Shukla!

@sentrial_dev @theneelshar Loops and hallucinations are symptoms of a deeper issue, agents acting without a clear architecture of judgement. Monitoring helps, but the real leap will come from designing systems that know why they’re acting, not just what to do next

@sentrial_dev @theneelshar Most agent monitoring relies on output validation. Hard to catch divergent reasoning paths that still produce plausible results. Need causal tracing through the attention layers, not just logging the final token distributions.

@sentrial_dev @theneelshar Nice will look into this for my project.

@sentrial_dev @theneelshar im going to include this in my projects

@sentrial_dev @theneelshar Awesome. Congratulations

@sentrial_dev @theneelshar Observability bridges demo and production reality

@sentrial_dev @theneelshar 🚀🚀

@sentrial_dev @theneelshar All the best!

@sentrial_dev @theneelshar sick

@sentrial_dev @theneelshar bro this is gonna save so much time lol

@sentrial_dev @theneelshar Really smart angle—everyone is building agents, but very few are solving reliability

@sentrial_dev @theneelshar huge value add

@sentrial_dev @theneelshar The best developer tools feel invisible. That's when you know it's working.

@sentrial_dev @theneelshar @ycombinator, Combinator, this is a crucial point; effective monitoring is essential for reliable AI agent performance.

@sentrial_dev @theneelshar This is awesome

@sentrial_dev @theneelshar This is the unsexy infrastructure that actually matters. Benchmarks measure what agents CAN do. Monitoring measures what they ACTUALLY do in production. The gap between demo and deployment is almost entirely observability. You can't fix what you can't see failing.

@sentrial_dev @theneelshar Observability for AI agents is going to be as essential as APM was for traditional software. You can't fix what you can't see failing.

@sentrial_dev @theneelshar congrats on the launch guys!

@sentrial_dev @theneelshar Huge!!!

@sentrial_dev @theneelshar Big congrats to the team 👏 spotting agent failures before users feel them is exactly what production AI needs.

@sentrial_dev @theneelshar Cool

@sentrial_dev @theneelshar let's go!

@sentrial_dev @theneelshar so real. agent observability is becoming as critical as app observability. you can't manage what you can't see

@sentrial_dev @theneelshar 🤖

@sentrial_dev @theneelshar 这个判断很准，很多失败真是用户骂了才被发现。我们最近加了会话级轨迹回放，才看清循环和幻觉常常是一起出现的。除了这些行为信号，你们会把业务转化下滑也接进同一套监控吗？

@sentrial_dev @theneelshar @samiralatipova

@sentrial_dev @theneelshar i thought hallucination is no longer a thing?

Detection is step one. The next frontier is auto-correction — catching drift and silently fixing agents before users ever notice. We're building this at Talked to 11 teams running agents in production last week. Every single one had the same blind spot: agents degrading slowly, not crashing. Monitoring tells you what broke. We want to fix it automatically.