Nice, i think that yall are on the correct path betting on evals, but please make your ui less "generic"
Launch HN: Lucidic (YC W25) – Debug, test, and evaluate AI agents in production
21–30 of 41 posts
Re: Launch HN: Lucidic (YC W25) – Debug, test, and evaluate AI agents in production
#22yet another observability tool thats joining the already overcrowded space
my vision is that the market is not really prepared for that right now, the best way is this guys is solving a really niche problem with their plataform and then expanding trough more areas
Re: Launch HN: Lucidic (YC W25) – Debug, test, and evaluate AI agents in production
#23Is the front end built using AI? It's unusable on Pixel 8a. You may lose users, please fix the responsive design.
Given that its a tool for development, it seems wise for them to focus on priorities other than mobile phone usablity
Re: Launch HN: Lucidic (YC W25) – Debug, test, and evaluate AI agents in production
#24Re: Launch HN: Lucidic (YC W25) – Debug, test, and evaluate AI agents in production
#25I've been keeping a rolling list of LLMOps/AI agent observability products funded by YC. What problems does Lucidic solve that the others do not?
https://hegel-ai.com https://www.vellum.ai/ https://www.parea.ai http://baserun.ai https://www.traceloop.com https://www.trychatter.ai https://talc.ai https://langfuse.com https://humanloop.com https://uptrain.ai https://athina.ai https://relari.ai https://phospho.ai https://github.com/BerriAI/bettertest https://www.getzep.com https://hamming.ai https://github.com/DAGWorks-Inc/burr https://www.lmnr.ai https://keywordsai.co https://www.thefoundryai.com https://www.usesynth.ai https://www.vocera.ai https://coval.ai https://andonlabs.com https://lucidic.ai https://roark.ai https://dawn.so/ https://www.atla-ai.com https://www.hud.so https://www.thellmdatacompany.com/ https://casco.com https://www.confident-ai.com
Re: Launch HN: Lucidic (YC W25) – Debug, test, and evaluate AI agents in production
#26I've been keeping a rolling list of LLMOps/AI agent observability products funded by YC. What problems does Lucidic solve that the others do not? https://hegel-ai.com https://www.vellum.ai/ https://www.parea.ai http://baserun.ai https://www.traceloop.com https://www.trychatter.ai https://talc.ai https://langfuse.com https://humanloop.com https://uptrain.ai https://athina.ai https://relari.ai https://phospho.ai https:…
You should compile these into a Gist or some static page.
Re: Launch HN: Lucidic (YC W25) – Debug, test, and evaluate AI agents in production
#27I've been keeping a rolling list of LLMOps/AI agent observability products funded by YC. What problems does Lucidic solve that the others do not? https://hegel-ai.com https://www.vellum.ai/ https://www.parea.ai http://baserun.ai https://www.traceloop.com https://www.trychatter.ai https://talc.ai https://langfuse.com https://humanloop.com https://uptrain.ai https://athina.ai https://relari.ai https://phospho.ai https:…
You should compile these into a Gist or some static page.
Here's my full list: https://gist.github.com/areibman/b1f66a9a037005b2d4bbf5ba2e5...
Re: Launch HN: Lucidic (YC W25) – Debug, test, and evaluate AI agents in production
#28Earlier quoted context omitted.
You should compile these into a Gist or some static page.
Here's my full list: https://gist.github.com/areibman/b1f66a9a037005b2d4bbf5ba2e5...
thank you, this is cool/interesting. i work in this space and I was thinking yesterday that it would be an interesting contemporary witness to record competition & then see how things shake out.
Re: Launch HN: Lucidic (YC W25) – Debug, test, and evaluate AI agents in production
#29You say your rubric approach is “better than llm as a judge.” Can you please elaborate on what makes you say that?
LLM as a judge for agent usually has context overload and even if you have a really good prompt for your evaluation, LLMs hallucinate because there is just too much information to ingest. So we created an agentic pipeline to basically do evaluations on rubrics which have better results and dont miss intricacies due to the overloaded context.
I'm reading: the difference is that this is an agent as a judge rather than an LLM as a judge, paired with more structured judging parameters. Is that right? Is the agent just a loop over each criterium, or is it also reflecting somehow on its judging or similar?
Re: Launch HN: Lucidic (YC W25) – Debug, test, and evaluate AI agents in production
#30Earlier quoted context omitted.
Colloquially, AI agents are just while loops with LLM calls and tool calls. More specifically, what distinguishes an agent from LLM pipelines is that its next step is determined dynamically (based on the output of the previous one) so the execution path isn’t fixed. The boundary between complex LLM chaining and agents is pretty fuzzy, but we support both. Haha also our whole backend is in Django :)
Gotcha, you're using the "LLM calling tools in a loop" definition. I think that's a decent one, but I worry that many people out there are carrying around completely different ideas as to what the term means.
Do you have a writeup on the different interpretations of "AI Agent"?