Developers code, they were “born to do it”, to quote an erroneously attributed Dr. Seuss idiom. The problem is, so many software application development engineers spend more of their time on provisioning and systems planning, on debugging and testing… and on onward maintenance and management that, despite the rise of DevOps, just seems to get in the way of the core compulsion to cut code continuously. But can platform engineering change this cumbersome dynamic and, if so, what cultural shifts need to happen?
Recent Forrester research suggests that developers spend a surprisingly small portion of their time (around 24%) actually writing code from scratch. Much of their day is spent working within platforms, collaborating, testing and troubleshooting. This revelation (if it is a substantiated one) may signal a bigger shift in enterprise IT. It might just mean that platform engineering isn’t emerging i.e., it’s already here, reshaping how software is built.
“The developers’ world is evolving in the AI age. From building applications, they will now be asked to create full-on agentic systems, or AI-driven applications capable of autonomous decision-making and task execution. Instead of coding assistants, they will rely on AI-powered app generation and maintenance platforms,” proposes OutSystems CEO, Woodson Martin. “Instead of being code writers, developers will ultimately become strategic change makers, guiding how agentic AI interacts with people, data and business processes.”
But are developers truly ready to embrace this change?
A New Mental Model
As we know, platform engineering isn’t just a set of tools or abstractions. It’s a new mental model – one that will redefine how developers build, collaborate and innovate in the years ahead.
OutSystem’s Martin says that as platform engineering becomes a core part of the development process, teams must increasingly rely on automation, insights and real-time recommendations. This is not to replace developers, but to elevate their work. He reminds us that platform engineering takes on the repetitive, operational tasks, like troubleshooting and scaffolding, freeing developers to focus on higher-value initiatives, solve complex problems creatively and take on more strategic, vision-oriented roles.
Look! Invisible Engineering
“Great platform engineering is practically invisible, empowering without obstructing. Importantly, it isn’t just for senior engineers; it democratizes access to advanced capabilities for developers at every level,” said Martin. “Looking ahead, as teams grow more comfortable integrating AI into their workflows, the next evolution is agentic AI, where autonomous agents take on more complex responsibilities, independently interacting with systems and driving business decisions. It’s a fundamental change, not just in how software is built, but in who (or what) is building it.”
But can we fully trust AI to build mission-critical enterprise systems?
Martin’s organization is known for its low-code platform technologies, which the lion’s share of his commentary will naturally gravitate towards. As such, he thinks the low-code is capable of giving AI a “reliable foundation and the control required” for enterprise demands. He urges us to think of AI as the architect and low-code as the builder, turning ideas into real, workable, scalable systems. Without that foundation, AI outputs risk remaining fragile sketches. After all, we all know that agentic systems need reliable scaffolding, so this should be what platform engineering provides.
Just as DevOps once did, the rise of platform engineering and AI-powered workflows demands more than technical adoption. It calls for a cultural transformation in how developers approach their work.
From Tool, To Teammate
To thrive in a platform engineering-first world, developers must rethink their roles, responsibilities and workflows, especially as AI moves from tool to teammate.
“Success requires cross-functional ownership,” insisted Martin. “The most effective platform teams operate at the intersection of engineering, operations, security and product, focusing on enabling developers to confidently delegate routine and complex tasks to autonomous agents. Today, developers often use AI tools but double-check their outputs meticulously, a necessary step for building trust and accuracy. However, with the reliable, governable low-code scaffolding afforded by platform engineering, developers can ease up on AI scrutiny and trust their systems to work independently, focusing instead on higher-impact work.”
Additionally, he points out, platforms must act as enablers, not enforcers, providing autonomy with guardrails. By embedding compliance and security best practices into their core, platforms help developers maintain standards while fostering innovation.
DevOps Developed, Not Dead
Speaking to Martin about where he feels platform engineering fits in to his firm’s product mindset, we might have initially imagined that (as a low-code platform provider) he might show some level of antagonism or negativity towards a new paradigm, methodology, cultural workflow approach (define platform engineering as you will) designed to provide aspects of self-service through internal developer platform technologies that might just make you think of low-code and draw some parallels.
That’s not how the OutSystems CEO sees it. He’s upbeat and says that DevOps didn’t die, it evolved. His final thoughts are that platform engineering is DevOps productized, codified and scaled. What began as a mindset has matured into a design pattern. He thinks that this isn’t the end of DevOps: it’s the foundation for a new era defined by intelligent platforms and agentic AI. It’s something more sustainable, scalable and future-ready.