In a significant shift within the realm of AI-driven software development, Litera has unveiled its “Agentic Product Development Lifecycle (PDLC),” an approach that promises to enhance R&D productivity and drive AI adoption across its operations. Spearheaded by Greg Ingino, Chief Technology Officer at Litera, the plan focuses on transforming software development practices within the organization over a period that spans from Q1 FY2025 to Q2 FY2026. As detailed by Mr. Ingino, this transformation has accelerated both the pace of delivery and the adoption of AI-driven tools to a considerable extent. The full account can be accessed
here.
Central to this approach is Litera’s embrace of AI agents, notably Cognition’s AI coding agent, Devin. With these tools, Litera significantly reduced the time from idea conception to market delivery. Notably, the legal AI agent “Lito” progressed from a conceptual stage to an MVP in just six months, illustrating the swiftness of AI integration within the company’s development cycle. Monthly active users of these AI offerings rose significantly, with Lito’s user base expanding by 300% quarter over quarter and Litera One’s platform growth nearing its 91% end-of-quarter target.
The new PDLC leverages AI at almost every stage of product development, thereby placing greater ownership and responsibility in the hands of engineering managers, speculatively augmenting development speed up to eight times over previous benchmarks. The new system, referred to as Mates, autonomously handles various life cycle processes from ideation to deployment, significantly reducing manual interventions and potential bottlenecks.
Before implementing these changes, AI support in the code change process at Litera was nominal. By Q2 FY2026, AI assisted nearly 70% of pull requests, constituting more than half of all code modifications. During the same period, there was also remarkable growth in developer output metrics, with the code changed per developer increasing considerably. The transition has been underpinned by the development of a centralized orchestration platform, ARGO, which streamlines various operational stages and ensures seamless handoffs.
The implementation has resulted in more efficient resource allocation, with reduced staffing needs while simultaneously increasing output. The productivity gains have not come at the expense of quality and security; defect rates have declined, and test coverage has broadened due to the influence of automated testing agents such as QualityMate and SecureMate.
Despite the evident successes, Litera aims to address the challenges presented by its rapid development pace, particularly those associated with go-to-market strategies and the need to scale automation in oversight and quality assurance procedures further. Litera plans to maintain its progression by streamlining its integration processes, aiming to align release capabilities with consumer and organizational readiness.
Overall, Litera’s Agentic PDLC emphasizes a shift towards a fully automated, AI-driven workflow that reduces time demands on engineers and enhances productivity across the board, offering a proactive blueprint for other companies considering similar transformations.