David M. Cohen

David M. Cohen advises companies on protecting and scaling the business value of their products and services, including those based on software, data driven systems, and artificial intelligence. His work focuses on building IP and technology strategies that tie directly to revenue drivers, product differentiation, and defensibility, rather than collecting patents and intellectual property that have high costs and do not protect core value.

David works closely with product, engineering, and legal teams to identify what creates value, including system architecture, personalization and recommendation logic, ranking systems, orchestration layers, data pipelines, and user interaction flows. He designs coordinated strategies across patents (utility and design), trademarks, trade secrets, agreements, and governance based on how systems operate and how competitors would attempt to replicate them. His practice spans patent strategy and prosecution, trade secret programs, technology transactions, and open source and licensing compliance. He regularly advises on structuring IP ownership, drafting and negotiating software and AI related agreements, and reducing risk in technology deployment and data usage.

A significant part of David’s work focuses on AI and software risk mitigation, governance, and training. He develops practical policies, best practices, and internal guidance for engineering, product, and legal teams on topics such as AI usage, data handling, model inputs and outputs, and integration of third-party tools. He frequently delivers training and builds governance frameworks that enable teams to move quickly while managing legal and operational risk.

David has experience across artificial intelligence, including generative AI and large language model (LLM) systems, as well as software platforms, distributed architectures, and data driven products. He has developed strategies for AI driven decision systems, multi-model and orchestration frameworks, attribution systems for AI generated content, and real-time recommendation systems based on user behavior, often aligning protection with product impact and revenue generation.

He previously worked in a seconded in-house role at a global technology company, advising on patents, data rights, product design, and technology risk across engineering and business teams. Clients rely on him for practical guidance that connects legal protection, product development, and commercial outcomes. He has also worked within the federal court system on patent matters, providing additional perspective on how IP strategies perform in litigation.