About Simone Systems Research
An independent research organization investigating the engineering, evaluation, and compute economics of autonomous AI systems.
Background & Purpose
As artificial intelligence transitions from conversational models to autonomous multi-step systems, the primary engineering bottlenecks shift from parameter scale to systems-level reliability: coordination topologies, verification bounds, resource allocation, and failure recovery.
Simone Systems Research conducts independent technical investigations aimed at developing reproducible methods, benchmark testbenches, and open software artifacts to address these challenges.
Leadership & Researcher
Jonathan Simone conducts independent research into AI agent orchestration, evaluation, verification, and compute efficiency. His work focuses on developing systems that distinguish plausible progress from independently verified improvement.
Research Program Areas
- Agent Orchestration: Deterministic state-machine coordination, sandboxed tool execution, and communication protocols across heterogeneous reasoning models.
- AI Evaluation & Verification: Testbench designs that isolate genuine algorithmic capability gains from benchmark leakage, metric hacking, and stochastic noise.
- Compute Economics: Quantitative trade-offs between inference cost, context compression, test-time compute, and verified task accuracy.
- Adaptive Systems: Closed-loop introspection, memory state tracking, and measured policy evolution in dynamic environments.
Inquiries & Contact
For research inquiries, preprint discussions, or technical collaboration: