Coursedog
Steering AI with confidence: How Coursedog uses Span to illuminate engineering performance
30% → 95%
WEEKLY AI ADOPTION BY THE END OF 2025
40%
More PRs year-over-year as teams embraced AI
25%
Increase in rework surfaced early, prompting new guardrails
“Span illuminates what’s happening inside our engineering organization. That visibility helps us govern AI adoption, drive accountability, and act early as we evolve how we build and ship products.”
Jeff Burgazzoli
VP of Engineering
Background
Coursedog provides academic operations software that helps colleges and universities manage curriculum, scheduling, assessment, and institutional workflows. As the company expanded its platform and customer footprint, its R&D organization grew to more than 50 people across engineering, product, and design.
Jeff Burgazzoli, VP of Engineering, is responsible for guiding execution, investment, and platform health as the organization scales. For Jeff and his leadership team, understanding how work moves through engineering is foundational to maintaining alignment, quality, and predictable delivery.
Challenge
AI Acceleration Demanded Greater Visibility
As AI-assisted development accelerated across engineering, leadership recognized that speed alone would not define success. They needed a clear view into how AI was influencing execution, quality, and the overall health of the development lifecycle.
Before Span, reporting required stitching together data from multiple sources. The team relied on Notion databases, spreadsheets, and manual analysis to understand sprint health, velocity, and quality trends. While workable at a smaller scale, this approach made it difficult to see lifecycle patterns clearly or respond with confidence as development accelerated.
Leadership wanted to move beyond measuring adoption to understanding its operational impact. Were teams becoming more effective? Where might risk be emerging? And how could they ensure that increased output translated into durable engineering performance rather than downstream friction?
Coursedog needed a system-level view of engineering that leadership could trust and operationalize.
Solution
An Operating Layer for Modern Engineering
Today, Jira and Span views form the operating layer for how engineering runs at Coursedog. By unifying signals across pull requests, tickets, and deployment data, Span provides leadership with a reliable picture of execution across teams.
These views power weekly team rituals, monthly business reviews, and quarterly board reporting. Leaders can quickly understand how work is progressing, where effort is concentrated, and how development patterns are evolving as AI becomes embedded in everyday workflows.
Span allows the organization to track lifecycle stages, monitor workstream investments, and evaluate trends as they emerge. This shared visibility keeps teams aligned while giving leadership the confidence to guide engineering with intention.
“We operate out of Jira and Span views on a daily and weekly basis, and those same views power our monthly business reviews and quarterly leadership reporting.”
Jeff Burgazzoli – VP of Engineering
Results
Clarity to Move Faster, and in the Right Direction
AI adoption scaled rapidly across Coursedog’s engineering organization, rising from 30% to 95% weekly usage by the end of 2025. Pull request throughput rose alongside it, increasing about 40% year over year as teams embraced AI-assisted workflows.
Rather than focusing on speed alone, leadership looked for the second-order effects of this acceleration. Span illuminated how the shift was reshaping the development lifecycle.
Rework had long been the most time-intensive stage of development. Within a single quarter, the team saw it increase by approximately 25 percent, an early signal that rising code volume was placing new pressure on review and quality processes.
Because the trend surfaced early, Coursedog is able to respond before it becomes systemic. Engineering leaders are introducing stronger quality guardrails, enhancing review practices, and setting clearer expectations around code evaluation. Span also helps identify where review responsibilities are concentrated, informing performance conversations and reinforcing accountability across teams.
The same visibility is reinforcing executive alignment. Coursedog now reports a consistent set of engineering metrics to senior leadership, creating greater confidence in how progress, risk, and investment priorities are understood at the highest levels of the organization.
Span gives Coursedog the clarity to understand how AI is transforming its engineering system and the confidence that the organization is moving in the right direction.
Looking Ahead
As AI continues to reshape software development, Coursedog is focused on progressing from adoption toward true proficiency. Leadership is digging deeper into the root causes behind lifecycle trends, refining guardrails, and using workstream insights to guide future investment decisions.
Coursedog has worked closely with Span throughout its evolution, helping inform how the platform develops. “As early adopters, we’ve helped shape the direction of Span,” says Burgazzoli. “The team listens to our feedback and builds in ways that directly support how we operate.”
With Span embedded into operating rhythms, Coursedog is positioned to steer through change with intention. Span provides the visibility and partnership the organization needs to ensure that faster development translates into stronger, more resilient engineering performance.