We spent the last few months benchmarking PatentPal against Claude 3.5 for drafting provisional patents. The most critical failure point for technical founders

We spent the last few months benchmarking PatentPal against Claude 3.5 for drafting provisional patents. The most critical failure point for technical founders using LLMs is under-disclosure. Generative AI excels at writing 5,000 words of generic boilerplate, which fails 35 U.S.C. §112(a) enablement standards. PatentPal is highly effective at rigid terminology tracking (preventing antecedent basis errors) and auto-generating flowcharts from claims. However, we found Claude 3.5 (with extended reasoning) to be far superior for software patents, specifically its ability to ingest raw Python/C++ code and translate the control logic into proper method claims. We also outlined the privacy differences; consumer Claude retains data for 30 days and may train on it, while the API can be configured for zero-retention. We are happy to answer questions about the prompt engineering stack required to force LLMs into strict USPTO compliance.