Progressive Leasing accelerates software delivery with Observe AI SRE

Story Highlights

• ‍AI-driven release certification: AI SRE validates deployments across development and production, detects subtle changes in system behavior, and routes findings to responsible teams.‍
• Accelerated investigations and analysis: Engineers move from manual exploration to contextual insight, reducing time to insight from hours to minutes.‍
• Expanded self-service across teams: Engineering and customer-facing teams use AI SRE to support customers and investigate issues, taking burden off observability specialists. 

Today’s accelerated pace of software delivery introduces new reliability risks

Progressive Leasing serves millions of customers through point-of-sale lease to own programs across the United States. Its platform is embedded directly into the purchase experience across 30,000+ retail partners and e-commerce channels, where approval decisions must be delivered with minimal latency and high reliability. This requires highly available systems that continuously evaluate risk and customer data; any disruption can  impact revenue, retailer relationships, and customer trust.

Zack Ogden, Senior Director of Enterprise Technology, oversees observability and incident response. His team already maintained a disciplined SDLC, complete with regression tests and end-to-end validation.

“We do a really good job at providing alerting and monitoring. If something’s wrong, we’re going to know about it,” Ogden says. “But knowing after the fact isn’t enough, we wanted to catch issues before they impact customers.”

As the company embraced AI-assisted development and automation, the pace of software delivery grew faster. More changes moved through the pipeline, system interactions grew more complex, and there was less time to validate each one.

“Moving faster is one pillar of our AI enablement. Another key benefit is that AI SRE helps us identify unknown unknowns that take an army of people to sift through. We wanted a smarter way to surface those signals automatically.”

To keep pace with accelerating development, Progressive Leasing embedded Observe by Snowflake and its AI SRE directly into observability and deployment workflows.

AI validates software deployments using Observe; issues are routed back to engineers

Progressive Leasing has integrated Observe’s AI capabilities into their deployment pipeline through an internal orchestration layer connected to Observe’s MCP gateway. The AI agent operates within the automated workflow, evaluating changes across development and production environments.

Deployments are analyzed in context. Traffic patterns, error signals and environmental shifts are evaluated together, providing clearer visibility into what changed and where. Using Observe's context graph, the AI agent connects unusual signals back to specific deployment events: the software update, endpoint, and time it was deployed. This workflow also runs in development environments so that the agent can surface issues before they reach production.

Findings are typically routed directly to the responsible teams for affected services, who can drill into logs and telemetry within Observe immediately. Within the workflow, the agent also generates monitors in Observe to help ensure new features trigger alerts when behavior changes. 

This validation is largely automated and embedded in the pipeline rather than a separate review step. “We baked these checks into a gating system. It’s built to prevent bypassing. You either get a passing score or you don’t,” Ogden says.

Investigations move from manual exploration to contextual analysis

When issues surface in production, the critical first step is to understand the scope of what’s happening. This initial investigation phase can take significant time and involve multiple teams.  AI SRE is integrated into Observe’s UI and helps response teams understand the scope of the incident quickly. Using Observe’s observability context graph, AI SRE highlights affected services, recent changes, and relevant signals so teams can focus their efforts immediately.

Engineers can drill directly into logs and telemetry using AI SRE to quickly focus on affected areas, reducing time spent in manual exploration during the initial response phase. The initial phase of investigations can now move from hours to minutes, improving time to clarity while maintaining disciplined incident management practices

In the past, Ogden says, “Discovering where an issue originated could have taken hours manually correlating logs, and using multiple tools. Observe is tied into all of our systems. AI SRE gives you better insight because it has the information at its fingertips and can give it to you right away.”

Observability becomes a self-service tool across engineering, support, and operations

AI SRE also changed who can effectively use observability. Previously, deep expertise in telemetry and query languages often resided within a small group of SREs. Engineers frequently relied on escalations or tickets to access the right visibility. “The speed to which we onboarded is a testament to the platform’s learning curve,” Ogden says. “And now using AI SRE, it’s even easier.”

With Observe by Snowflake and its AI SRE embedded into daily workflows, engineers can ask natural language questions, generate dashboards quickly and investigate service behavior independently. Incident commanders can quickly identify affected areas and bring in the right teams, reducing the need to manually assess and correlate the initial incoming signals.

“We’re using AI SRE everywhere at this point,” Ogden says. “It’s how we build, how we validate changes and how we support the business. Engineers use it when they’re deploying, support teams use it to understand what’s going on and operations uses it when something needs attention. Because most of the data is in one place, the AI actually much of the context it needs to be useful.”

By using observability as a self-service tool beyond specialists, Progressive Leasing has increased self-service across engineering, support, and operations teams.

“Observe is tied into all of our systems. AI SRE gives you better insight because it has the information at its fingertips and can give it to you right away.”

Scaling For A Future Driven By AI

For Progressive Leasing, Observe and its AI SRE are becoming a key part of operating in an era when development is accelerating through the use of AI. As development accelerates through automation and AI-generated code, validating and managing change at scale increasingly requires embedded intelligence.

“I don’t know how companies 18 months from now stay relevant if they don’t have products like this in their tech stack,” Ogden says. “This level of automation and speed with AI is going to become table stakes.”

By automating validation, accelerating analysis, and expanding self-service, Progressive Leasing has embedded AI-driven productivity into its engineering foundation, increasing their velocity of innovation while helping maintain system reliability.