Early in my career, I was part of a product launch that went badly wrong. We were racing to meet a deadline for a major broadcast customer. Developers were pushing code as fast as they could. QA was always playing catch-up, validating yesterday’s builds while developers were already three features ahead. There was no single point of accountability: dev pointed to incomplete requirements; QA pointed to insufficient test time; product management pointed to both.
Launch day arrived. Within hours, intermittent failures appeared under load — something the team had only lightly stress-tested. We spent the next two weeks in fix mode, patching issues that should have been caught before the product ever reached a customer. The cost wasn’t just over-time hours or emergency budgets. We had damaged a key customer relationship and put real operational pressure on their team.
The lesson was unambiguous: speed without structure isn’t velocity. It’s chaos. And in broadcast and media operations — where the cost of failure is measured in revenue, reputation, and airtime — chaos is not an option.
That experience is foundational to how our R&D teams work today. It’s also what convinced me that engineering discipline isn’t just an internal quality standard — it’s the foundation of customer trust. The habits our teams have built since then are what make real partnership possible. Here’s what those habits look like in practice.
Testing against reality, not assumptions
One of the most important changes our teams have made is how we structure validation. We now build and maintain test systems that are representative of actual customer environments — configured the way customers run them, not the way a clean lab environment would suggest. These systems are dedicated to customer evaluations; they’re not shared with release processes.
We also share test plans with customers. We run tests in parallel with them. This matters more than it might seem. In the past, customers would go off and build a test plan we’d never seen, and sometimes they’d be testing the product in ways that — had we known — we could have flagged as unsupported or addressed differently.
Transparency in the testing process closes that gap. It means fewer surprises on both sides, and it means customers can trust that what we validated is actually what they care about.
Quality built in, not checked at the end
Our teams have made substantial investments in QA automation and system-level test coverage. The goal isn’t to automate for its own sake — it’s to make quality consistent and repeatable. Automated test cases provide core coverage quickly, which frees our QA engineers to focus on more complex scenarios that benefit from human judgment.
We’ve also extended our use of AI into static code analysis, penetration testing, test case generation, and defect detection. These don’t replace engineering expertise — they amplify it.
AI helps our teams maintain consistent test coverage as products evolve and has become a vital part of our modernization and refactoring strategy for certain products. Our use of AI comes with careful attention to product and IP security. We have a dedicated AI strategy team that works across all teams to help ensure AI can be used safely and effectively across all functional teams.
The measure of success isn’t how fast the team ships. It’s how confident everyone — including the customer — can be in what ships.
Over the past two years, AI has significantly transformed the assessment and development of new products and operational processes at Imagine Communications.
CPO, Brendon Mills, explores that experience in more detail in our AI-focused blog ➜
Simplicity creates predictability
A good process enables good work and minimizes bureaucracy. Our release, customer escalation, and customer commit processes focus on the essence of delivery and give teams a consistent approach to managing the real tension that exists in every software organization.
We’ve been able to land on the right balance between delivery and the necessary project telemetry. When Imagine commits to a delivery timeline, the discipline behind that commitment is what makes it reliable and predictable. Not heroics. Not hope.
R&D and Customer Care: a closed loop
One of the cultural changes I’m most proud of is how our R&D teams work with customer care. When a customer encounters an issue, our support engineers don’t just log a ticket and wait. They triage, replicate, and work directly alongside R&D to get to a resolution. Development teams also focus on understanding how customers found the issue. Was it a workflow dependency? Content related? … or an interop issue? Resolving the issue is important, but learning how to fortify our products against similar issues is key to overall product quality.
We’ve also introduced biannual internal TechOps workshops where our DBA and R&D teams train our Tier 2 care engineers — strengthening their capability to resolve issues that historically would have required escalation to engineering. That investment in cross-team knowledge sharing results in faster resolutions and an improved customer experience.
Customer feedback shapes product priorities. When a major customer told us their top priority had shifted, our teams quickly understood why and were ready to adapt. That kind of responsiveness only works when R&D and the customer-facing teams are genuinely connected, not siloed.
Strengthening teams
None of this discipline matters if teams don’t have the autonomy, skillset, and resources to execute. We’ve worked hard to ensure we have the right people in the right roles with the autonomy to make the best choices for the product and customer. We have provided our teams with dedicated customer-centric test infrastructure to exercise real-world workflows with realistic content. Ensuring teams have the right skills at the right capacity to deliver is critical to customer success.
Quality and throughput aren’t in competition. When teams have the right resources and the right structure, both improve together.
Journey or destination?
My advice: stay focused on both! Great teams using efficient tools and processes are truly the most productive. Staying focused on what our customers need and what our products aim to deliver aligns that productivity with the greatest chance of success.
Testing against reality. Building quality in from the start. Creating predictability through simplicity. Staying connected to the customers we serve. Giving teams the autonomy and support they require. None of these are dramatic, but managed together and practiced consistently, they’re the foundation to a genuine partnership — inspiring trust and confidence in Imagine’s ability to deliver.
Imagine Executive Blog Series
Want to see where it all started? CEO Steve Reynolds outlines how Imagine changed its internal culture — strengthening responsiveness, accountability, and delivery discipline to rebuild customer trust.
