DOMAIN DOSSIER
AI Systems & Autonomous Agents
Investigating deterministic execution bounds, finite state control, memory limits, and grounding verification for modern LLM-driven agent systems.
01.Eliminate hallucination loops through formal finite state machines.
02.Bound vector and context memory to prevent runaway serverless allocations.
03.Require provenance and citation attribution for every generated claim.
Published Investigations in AI Systems (2)
RS-005VALIDATED
Sep 17, 2026Memory-Bounded LRU Caches for Vector Embedding Pipelines
Investigating deterministic cache eviction policies for multi-dimensional float32 embeddings in resource-constrained container environments.
AI SystemsAlgorithms
InspectRS-001VALIDATED
Sep 17, 2026Deterministic State Machines & Token Inverted Index for Agentic Retrieval
An investigation into eliminating non-deterministic hallucinations in LLM retrieval by pairing a deterministic finite state machine with a memory-bounded token inverted index, demonstrating sub-millisecond keyword localization and zero invalid state transitions.
AI SystemsArchitectureAlgorithms
Inspect