Atla is the only eval tool that helps you automatically discover the underlying issues in your AI agents. Understand step-level errors, prioritize recurring failure patterns, and fix issues fast–before your users ever notice.
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Much needed product!!! Can this tool handle sub-agents?
It sure can! We always perform our evals from the perspective & with the context of the active (sub)agent
Thanks Jorge! It was a big push and we're all very excited where we got in the end!
Awesome launch, well done to the team! Definitely need try this out soon :)
Thanks Alfie!
Just upvoted—this deserves attention. It feels like the team deeply cares about solving real user problems rather than chasing hype.
Thank you@yuncheng - we're indeed excited to help people (less painfully) evaluate their agents, we know it can be done!
@yuncheng @thelemonbot so needed right now -- startup space is absolutely saturated with "AI" products that barely function. IMO we're going to see a massive paring down soon; people and investors are growing tired of advertised features that don't work.
Really smart concept. Using AI to debug AI just makes sense, especially when you're dealing with complex agent behaviors. Way better than trying to manually catch all these edge cases.
Completely agree! The way we approach it preserves back-traceability from failure patterns down to the individual spans where they occurred. This also allows to organically build up an evaluation dataset from failure patterns.
Congrats on the launch, Roman and the Atla team! 🚀 Your tool sounds like a game-changer for debugging AI agents. The ability to detect and cluster failure patterns should really streamline the process and help teams focus on what really matters. Excited to see how it evolves! 🎉
Thanks Alex! Our vision is to automate the full debugging and improvement life cycle of agents. Claude Code / Cursor should just be able to pick up automatically generated failure patterns and implement fixes with zero human intervention.
This looks super cool! Definitely a much-needed product.
Thanks Jeremi!