Original research
Lab
Original experiments on questions people building agents face, including an LLM trading benchmark. Every result comes with its method and how sure we are.
One question each, measured and reported with its uncertainty. Pre-registered experiments write down what we expect before running anything.
- Safety & Guardrails Complete
A small decision model as a prompt-injection guard
Open models compared as prompt-injection guards for a coding agent at a fixed false-alarm rate: Cloudflare's Clef models with and without a retrained scoring head, and NVIDIA's Nemotron.
99.8% of new attacks caught by the large Clef model, untrained
- Benchmark Complete
LLM trading decisions
Which language models make the best crypto-futures trading calls, and under what market conditions? A deterministic backtest of agentic and single-call LLM traders across 20 historical scenarios, against buy-and-hold, technical-analysis and random baselines.
540 backtest runs: 5 models, 20 scenarios