Jordy Zomer built a Datalog engine so AI agents can forget correctly
Lemmalog separates fuzzy LLM extraction from deterministic facts, provenance and retractions, with early benchmarks showing promise and gaps.
By RuntimeWire Staff · Published
Primary source: pwning.systems
Why it matters
Lemmalog moves agent memory from transcript retrieval toward auditable state maintenance, giving developers a way to retract bad assumptions without asking an LLM to reconstruct every dependency.
Security researcher Jordy Zomer published the design and source code for Lemmalog on August 28th, turning a recurring failure in long-running AI-assisted vulnerability research into a Datalog engine that maintains what an agent currently knows.…