Pressed to prove the ROI of new AI coding tools, an enterprise client used Trility’s DORA-aligned diagnostic to uncover software delivery friction, unify leadership alignment, and secure a targeted roadmap for engineering velocity.
An enterprise client faced mounting pressure from its executive leadership team to demonstrate accelerated software delivery following a widespread investment in AI coding assistant licenses. However, adoption remained fragmented, and team maturity varied significantly.
As the 2025 DORA State of AI-assisted Software Development report notes, AI tools act as an amplifier of the underlying environment. Introducing automated code generation to a system already blocked by manual testing, large batch sizes, and fragmented requirements does not produce speed; it simply pushes more volume into a downstream bottleneck.
Their CIO realized that something needed to change within the organization to see the full positive impact of bringing in AI tools to increase software product delivery.
Trility leveraged its AI-Assisted Engineering Diagnostic built directly upon the seven core practices of the DORA AI Capabilities Model. To establish a data-driven baseline, we analyzed the reality of daily delivery across a 150+-person IT roster through comprehensive team surveys, stakeholder interviews, and value stream mapping.
This process allowed the cross-functional team to map out a feature's journey from backlog to production and gather key operational metrics. The diagnostic generated granular team scorecards, an executive readiness assessment, and a clear archetype mix (categorizing teams by their specific operational profiles), giving the client an objective look at where their execution model stood relative to the global DORA panel.
The diagnostic transformed vague executive pressure into a precise, prioritized strategy. The data revealed that while the organization possessed exceptional foundational strength in stability, team performance, and user focus, a critical throughput shortfall was being caused by large batch sizes.
Armed with objective metrics rather than guesswork, this client’s leadership gained the clarity and common vocabulary to align upstream executives. They confidently committed to immediate funding for a prioritized small-batch delivery discipline while planning for long-term internal developer platform investments, creating a clear pathway toward compounding returns on their AI tooling investment.
