When DevOps first entered the scene, it felt revolutionary — breaking down silos between development and operations, shortening delivery cycles, and empowering teams to own what they build. But like every great movement, it has evolved.
In 2025, we’re witnessing the rise of Platform Engineering — DevOps’ next act.
Where DevOps asked teams to “build it and run it,” platform engineering says, “Let’s build the system that makes it easier for everyone to build and run.”
It’s a subtle but powerful shift — from individuals owning pipelines to organizations owning the developer experience. And for Agile teams, that shift represents a huge opportunity to deliver faster, safer, and smarter.
From DevOps to Platform Engineering
DevOps was never meant to be a department. It was a mindset — a set of practices designed to improve collaboration, automation, and feedback loops between development and operations. But as organizations scaled, many discovered an unintended consequence: DevOps fatigue.
Developers were spending too much time managing infrastructure instead of focusing on delivering value. Toolchains became sprawling and inconsistent. And despite good intentions, velocity often stalled under the weight of complexity.
Platform engineering emerged as the natural evolution — creating dedicated teams that build and maintain internal platforms to support the rest of the organization. These platforms act as self-service ecosystems that abstract away repetitive, operational tasks, giving product teams the autonomy to focus on innovation.
Put simply, DevOps broke the wall. Platform engineering builds the bridge.
The Agile Connection
At its core, platform engineering aligns perfectly with Agile principles: empowerment, collaboration, and continuous improvement.
Instead of creating more hierarchy or process, platform teams function as enablers — reducing cognitive load for developers and removing barriers to flow.
In many Agile organizations, product teams rely on the platform team for tools, environments, and automation pipelines. That relationship only works when there’s a shared culture of trust and partnership.
If a platform team acts like a gatekeeper — dictating tools or enforcing standards without context — agility dies. But when the platform team acts as a service provider, co-creating with the teams they support, agility thrives.
That’s why the best platform teams treat their users (the developers and delivery teams) as customers. They use feedback loops, prioritize backlogs, and run retrospectives just like any other Agile team.
They’re not just building infrastructure — they’re delivering value streams.
How AI Is Accelerating Platform Engineering
Artificial Intelligence is playing an increasingly important role in how modern platforms operate.
AI-driven observability tools now predict system bottlenecks before they happen. Machine learning models optimize CI/CD pipelines by analyzing historical build data. Intelligent assistants help developers troubleshoot deployment issues or even write infrastructure-as-code configurations in real time.
And as someone who’s experimented with using AI to accelerate Agile delivery, I see enormous potential here.
Imagine platform teams using AI to automatically generate documentation for new pipelines, detect underused resources, or identify recurring incidents across teams.
Just as I use ChatGPT to create epics and user stories for my Agile coaching team, platform engineers can use similar tools to generate and refine infrastructure templates, draft runbooks, or even simulate changes before deployment.
It’s not about replacing engineering skill — it’s about amplifying it.
When done right, AI doesn’t remove human judgment; it enhances it. It enables teams to focus on strategy and outcomes instead of routine maintenance.
Metrics That Matter: Measuring Outcomes, Not Outputs
One of the biggest traps in both Agile and DevOps has always been measuring the wrong things.
Counting deployments, tickets closed, or story points completed may look impressive, but they don’t tell you whether you’re actually delivering value. Platform engineering gives us a chance to rethink metrics in a way that’s truly outcome-driven.
Here are a few examples:
- Developer Experience Metrics: How quickly can a new developer ship their first change? How easy is it to deploy safely? These measure friction, not just activity.
- Flow Efficiency: How much time does work spend in progress vs. waiting? This reveals systemic bottlenecks that slow delivery.
- Change Failure Rate: Are deployments reliable? Lowering this indicates platform maturity and resilience.
- Lead Time for Changes: How long does it take from code commit to production? Faster, safer flow means happier teams and customers.
- Value Stream Health: Are we improving how value moves through the system, not just how fast we push code?
As Gartner’s Agile Outlook 2025 report notes, “Outcome-based metrics are the single most accurate indicator of true agility — measuring whether value was realized, not just delivered.”
That’s exactly where platform engineering shines: it creates the conditions for better flow, higher reliability, and more sustainable delivery — not through more meetings or rules, but through thoughtful automation and intentional design.
Cultural Alignment: The Real Engine Behind the Platform
Technology alone doesn’t make a platform successful. Culture does.
Building a healthy relationship between platform and product teams requires the same principles we teach in Agile coaching: transparency, feedback, and shared ownership.
Here are a few cultural lessons I’ve seen separate thriving platform initiatives from struggling ones:
- Co-creation Over Command
Platform teams succeed when they build with product teams, not for them. Invite developers into discovery sessions, gather user feedback, and treat platform improvements like customer-centric product enhancements. - Empowerment Over Enforcement
Instead of forcing adoption through mandates, platform teams can build irresistible products — ones that are so easy to use and so reliable that teams want to use them. - Psychological Safety
Just as Agile teams need psychological safety to experiment, platform engineers need it to innovate. When failures are treated as learning opportunities, platforms evolve faster. - Shared Purpose
Everyone — from platform engineers to product owners — should be aligned on one thing: delivering value to the customer. The platform isn’t successful when pipelines are faster; it’s successful when outcomes improve.
This alignment is what turns platform engineering from a tech initiative into an organizational capability.
Bringing Platform Thinking to Agile Coaching
Even outside of software engineering, the mindset behind platform engineering applies to Agile leadership.
As Agile coaches, we build platforms for people — frameworks, tools, and environments that help teams thrive. When we remove friction from processes, standardize what should be standardized, and free teams to innovate within safe boundaries, we’re doing platform engineering in a different form.
And, just like technical platforms, our success isn’t measured in how many ceremonies we run or templates we create. It’s measured in whether teams are learning faster, delivering value sooner, and growing more capable over time.
The Road Ahead
Platform engineering represents more than just a new technical discipline — it’s a cultural evolution. It extends the spirit of DevOps, strengthens Agile delivery, and creates a foundation where teams can move with confidence and autonomy.
As AI continues to mature, the best platform teams will be those that blend automation with empathy — using intelligent systems to reduce toil and elevate human problem-solving.
In that sense, platform engineering is really about the same thing Agile has always been about: building systems that serve people, not the other way around.
Because at the end of the day, great platforms don’t just accelerate delivery. They amplify culture.
And in 2025, that might be the most powerful outcome of all.
References:
- Gartner, Agile Outlook 2025: The Age of Contextual Agility
- McKinsey & Company, The Rise of Platform Engineering in Enterprise Delivery (2024)
- Puppet, State of DevOps Report (2024)
- GitHub, State of AI in Software Development (2024)
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