New framework addresses the critical gap between GenAI pilots and production deployment in high-trust, regulated industries
PALO ALTO, Calif., Sept. 8, 2025 /PRNewswire/ — Theo Ai Chief Product Officer Jay Mandal, along with Dr. Megan Ma, Executive Director of the Stanford Legal Innovation through Frontier Technology Lab, has published a Stanford Law whitepaper titled, Building for Production: A Revised Playbook for Enterprise-Ready Generative AI Solutions. The paper outlines a practical, product-led approach for moving generative AI from proof-of-concept to full-scale production – a leap most enterprises still fail to make.
Drawing on Mandal’s experience leading AI-driven product growth at Theo Ai, SAP, Google Ventures-backed LawPivot, as well as his experience as Head M&A Attorney at Apple, the whitepaper offers a step-by-step framework for building GenAI products that can meet the operational, compliance, and trust requirements of industries such as law, healthcare, and finance.
Key themes from the paper include:
- A New Definition of AI Product-Market Fit — incorporating user experience, data governance, hallucination mitigation, and rapid iteration through vibe coding.
- Verticalization as the Next Competitive Advantage — why and how industry-specific GenAI builders will outpace general-purpose LLM providers.
- The 5 Gaps Preventing Production Deployment — including lack of integration planning, weak evaluation pipelines, and insufficient user trust.
- The New Role of Product Leaders — redefining responsibilities in the full lifecycle from scoping to post-launch iteration in high-stakes enterprise environments.
- A New Era of System Design of AI Solutions – the optimal solution will seamlessly integrate multiple multi-modal foundational models, with a UX/UI at each step that meets the users’ needs.
“Generative AI continues to capture immense interest across industries, but the reality is that many pilots stall before reaching maturity,” said Dr. Megan Ma, who co-leads the Stanford Law School LiftLab, where she conducts research and leads teams in prototyping generative AI tools for legal and enterprise settings. “The next phase of AI implementation will depend on shifting the focus from chasing generic use cases to targeting where AI can truly transform workflows. The novelty of AI has waned and organizations are ready for systems that are built for compliance and deliver measurable value”
“Generative AI has incredible potential, but in the enterprise, potential means nothing without production readiness,” said Mandal. “This playbook is designed to help builders bridge the gap between excitement and execution.”
The whitepaper was developed as part of Ma and Mandal’s teaching and research at Stanford Law School. Mandal serves as a Stanford Guest Lecturer and a Fellow at Stanford CodeX where he lectures on AI, product management, and legal ethics. It is available for download at https://law.stanford.edu/publications/building-for-production-a-revised-playbook-for-enterprise-ready-generative-ai-solutions/.
About Theo Ai
Theo Ai is the first predictive engine designed by technical and legal professionals to forecast the outcome of legal disputes. Its AI models are trained on historical case data and incorporate real-time analytics with predictive modeling to deliver accurate and actionable insights. Theo Ai is meeting the most critical need for legal professionals – offering accurate case outcome predictions, backed by data. To learn more and join the waitlist for Theo Ai, visit: https://theoai.ai/
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