Most AI memory implementations focus on storage and retrieval. The inference—what to actually store and why—is superficial. This talk introduces a different approach: solve the inference problem first by training reasoning models to produce formal logic. It's the hardest reasoning for humans, but LLMs excel at it—even more so when trained. Build the storage and retrieval system around scaffolding that logic to produce comprehensive, evolving representations. Vince Trost (Co-Founder, CEO of Plastic Labs) walks through how to use Honcho, how it reasons over data, and how developers can leverage that reasoning to solve memory, build stateful agents, and focus on building the best AI products possible. It's simple to implement, come see how.
Vince is the co-founder and CEO of Plastic Labs, a company on a mission to solve identity for the agentic world.
He was the first graduate from the Data Science program at Penn State University and has spent his career building AI applications in education, data science infrastructure on Ethereum, and is now building Honcho — a shared identity layer for LLM applications. His company has successfully raised $5.35m across 3 funding rounds to date.