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Pramaana Labs raised $27M in seed funding led by Khosla Ventures to apply formal verification (using the LEAN programming language) to improve AI reliability in high-stakes domains like law, drug discovery, and tax preparation.
The author details the challenges of building a deterministic autonomous trading agent using a Rust execution layer and Python AI layer with Claude/OpenAI, emphasizing the critical role of hard-coded risk management to prevent emotional or inconsistent trading.
The author details their decision to exclude LLMs from generating final fact-check verdicts in favor of a hybrid architecture that uses LLMs for data extraction and a deterministic Python layer for scoring, citing issues with stochastic instability and auditability.