New framework outlines how enterprises must redesign product and software delivery systems for the realities of AI-native execution.
RAVL today announced the launch of Leap Left, a new strategic approach designed to help enterprises rethink how products and software are delivered in the AI era.
AI doesn’t fix broken delivery models, it amplifies them. AI can generate code faster, but the firms that create the most value will be the ones that redesign how ideas move from concept to production”
— Rick Davidson
As generative AI rapidly accelerates coding, testing, and software execution, organizations are discovering that traditional delivery models are not built for AI operating at scale. While engineering throughput is increasing dramatically, many enterprises continue to struggle with slow decision-making, unclear requirements, fragmented workflows, governance complexity, and delivery friction across teams.
Leap Left introduces a system-level approach to AI-first product and software delivery focused not just on accelerating engineering, but on redesigning the conditions that allow AI to operate effectively across the entire delivery lifecycle.
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“Most organizations are still trying to layer AI onto delivery systems built for a completely different era of software development,” said Rick Davidson, CEO of RAVL. “AI accelerates engineering execution, but engineering has never been the only constraint. The real advantage now comes from how clearly organizations define problems, make decisions, validate outcomes, and move work through the system.”
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A core component of the framework is the RAVL Leap Left AI Maturity Model. It is designed to provide organizations with a practical starting point for AI-first transformation by helping teams assess AI delivery maturity, surface bottlenecks, identify foundational gaps, and prioritize the investments that will generate the greatest ROI.
“The Leap Left AI Maturity Model gives organizations a way to baseline their current state, identify the true constraints slowing delivery, and focus investment where AI can drive meaningful business impact,” Davidson added.
The framework outlines the foundational capabilities organizations need to move beyond isolated AI experimentation and toward scalable, enterprise-grade AI delivery. This includes new approaches to product validation, workflow design, governance, operating models, engineering practices, and capability development.
Leap Left is grounded in RAVL’s experience helping financial institutions and complex enterprises modernize delivery systems in highly regulated environments where speed, governance, reliability, and organizational trust must evolve together.
“AI doesn’t fix broken delivery systems, it amplifies them,” Davidson said. “The firms that create the most value from AI won’t simply be the ones that generate code faster. They’ll be the ones that redesign how ideas move from concept to production.”
The announcement comes as enterprises increasingly shift from AI experimentation toward operational implementation. According to RAVL, many organizations are beginning to realize that AI adoption is no longer just a tooling challenge. It is an organizational, operational, and product delivery challenge.
Alongside the announcement, RAVL has released a supporting industry paper exploring the changing economics of software delivery, the rise of AI-native product delivery, the maturity curve organizations are navigating today, and the foundational shifts required to scale AI effectively across engineering, product, and delivery teams.
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