Lucidic emulates model training without changing model weights. The last decade made models intelligent, but intelligence is not the same as experience. Humans do not get better by memorizing thousands of examples; we build learning systems around ourselves: skills, memories, critique, practice, tools, and guidance. And every person learns differently because every task is different. Lucidic brings that idea to AI agents by training a custom learning system for each agent, so it learns what to remember, what skills to build, when to ask for help, and how to improve from experience. The model provides the intelligence, Lucidic gives it a way to learn.
Total raised
$500K
Last stage
Pre-seed
Investors
Jeremy Tian
Hi! I'm Jeremy Tian, one of the founders and the Chief Scientist at Lucidic AI, working to explain your AI models' decisions. I have a BS/MS in Computer Science with an AI specialization from Stanford University. Ex. Quantitative Trader at DRW and software engineering/machine learning engineering at Steel Dynamics. Contact me at [email protected]!
LinkedInAbhinav Sinha
Stanford BS/MS Computer Science with AI specialization; ex-Stanford AI Lab researcher, Apple software engineer, and quant at Citadel Securities and Susquehanna International Group.
LinkedInAndy Liang
Stanford BS/MS Computer Science (AI specialization); Stanford national competitive programming team; ex-Citadel and AppLovin. Built GrocerCheck, a COVID-19 app with 200K+ users endorsed by the Government of Canada.
LinkedInNo applications, no recruiter spam. Just the intro.
A few questions to make sure this role is the right shape for you. Two minutes.
I write the intro, send it to the founder, and handle the back-and-forth.
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.