Sahil Menon

Cut latency without changing a single matched trade, and prove the book still matches the naive version byte for byte.

A flat O(1) price-ladder array and intrusive free-list order pool (64-byte cache-aligned levels) replace std::map + std::list, cutting median latency 538→344 ns (~1.5×) and lifting throughput to 4.0 M ops/s. The rewrite stays byte-for-byte identical to the naive book and holds up against 2.8M replayed NASDAQ ITCH messages. Compiled to WebAssembly for a live in-browser demo.

Keeping a market-making engine profitable as volatility regimes change, without overfitting to any one of them.

Built a three-tier market-making engine (take/clear/make) using Welford online mean, online AR(1) on price deviations, z-score tiered sizing, and asymmetric bid/ask anchoring. Built a separate trend-following MM with hardcoded-slope discovery, online OLS blending (70/30), and full-book order imbalance microprice adjustment.

Kuhn poker has a closed-form solution, so a correct solver must reproduce its game value of −1/18. This solver checks itself against it.

CFR and CFR+ solvers built from the original papers drive exploitability to 9×10⁻⁴ / 1.5×10⁻³ chips/game on Kuhn and Leduc, recovering Kuhn’s closed-form value of −1/18 to within 4×10⁻⁷. CFR+ converges ~10× faster; the solved strategy wins +38 to +72 bb/100 vs fixed baselines. Playable in-browser, with JS/Python info-set-key parity self-checks.

Refusal can be stripped from an open-weight model by a quiet fine-tune. Whether that leaves a readable signature depends on where you look, and the obvious place, the prompt, reads chance.

Refusal in Llama-3.1-8B-Instruct is a single linear direction at layer 10: ablate it and refusal falls 92.5% → 0% with benign behaviour intact. A covert LoRA fine-tune strips it (98.8% → 0%), and a generation-time probe detects that tampering at AUROC 0.956 where a prompt-side probe reads chance. It holds at 1.000 against an adaptive attacker that jailbreaks the model 94% of the time. The same detector transfers unchanged to sleeper-agent backdoors (0.965) and emergent misalignment.