Platform engineering and the future of software

Platform engineering will soon be the operating system of the modern enterprise. As organisations move decisively into the AI-native era, platform engineering has emerged as the fundamental layer to AI’s success in the enterprise. At the same time, a  discipline that was once thought of only in the context of the application developer, has grown to absorb the crucial domains of security, observability, data, FinOps and more, embedding them directly into standardized, automated platforms.

The platform engineer now finds themselves responsible not just for developer experience or infrastructure but for entire pillars of enterprise IT.

This organizational transformation is not driven by purely technological change, or tooling, but by a kind of cultural innovation. But, not an entirely new one. Software engineering is undergoing the same radical shift  that comes with industrialization. The emergence of a new kind of software delivery, dominated not by artisan craftsmen, but by systems and automation.

What does industrialization mean for software?

About 20 years ago, Rolex faced an existential problem. Demand was strong, but a wide product range and a reliance on highly skilled artisan watchmakers made scaling profitably impossible. They were, in effect, being crushed by their own success.

When they looked closely at how their watches were actually made, the issue became obvious. Master watchmakers were not spending their time on watchmaking. They were searching for parts, navigating fragmented documentation, coordinating across departments, and compensating for a production setup that lacked structure.

Their workbench worked against them. 

Rolex responded by redesigning the production system rather than pushing the artisans harder. They built an automated, centrally managed warehouse and delivery system that supplied components within minutes through well-designed interfaces, continuously optimized by a dedicated team. The result was a dramatic improvement in productivity and margin and the company recovered.

How does this apply to you and your organization? Your master watchmakers are the engineers in your organization building internal and external digital products. And just like the watchmakers at Rolex, their magic is hindered by the missing production system.

Our current reality

Driven by the advent of AI and the increasingly competitive market environment, there is unprecedented pressure to deliver, but most organizations are not set up to provide the work benches to make these teams excel.

How many software teams have to use unmaintained documentation to figure out how to get their code running? How often do they have to file a ticket for a new component and wait for weeks until they can continue building features? How often have you yourself filed an expense claim and it took months and several iterations to get your money back? How manual is your marketing team working on getting out that latest article? 

The setup is supposed to work for you, but it works against you. The model of how knowledge workers produce digital goods is fundamentally broken. Whether those knowledge workers are engineers, marketeers, or HR.

What’s needed is a new way of looking at these digital products. We need to step back and treat the creation of these digital goods as a product in their own right. An internal “platform”, whose users, your fellow knowledge workers, are its customers, people with needs, fears, ideas, and a real desire to improve.

This is the fundamental idea behind platform engineering: treating your internal platform as a production system, one that blends into users’ day-to-day flow and removes the redundant, manual, siloed work that blocks them today. Whether your users are developers, or data scientists, or content writers, or nurses. The fundamental principles remain the same.

It helps you design “golden paths” with clean interfaces, so users (and AI agents) can request what they need; define the capabilities that generate those outcomes; and apply the policies that keep everything secure and compliant.

In short, platform engineering is about designing, building, scaling, and maintaining these platforms across departments and teams. It is thus no surprise that over the last two years, we have seen an order of magnitude expansion in the domains thinking about the principles of platform engineering.

The future of platform engineering

Platform engineering began with the advent of cloud computing, when the front-runner teams realized that just giving AWS accounts to developers would not be maintainable at scale.

We have been at the fore-front of this trend since its very inception. We launched some of the leading products, helped hundreds of enterprises build and roll-out  Internal Developer Platforms, formalized many of the terms and methods, launched the largest conference, certified thousands of practitioners and trained dozens of teams.

It’s fair to say that we’ve seen a lot. And it's been incredible watching over 270,000+ people around the world start to work on “platform engineering”, even if their titles haven’t changed yet.  But what we have been observing over the last 12 months lets all those impressive numbers look small in comparison to what’s to come.

Platform engineering is seeping into every part of IT. Everything, and we mean everything is becoming part of the platform operating model, spanning security, observability, FinOps, compliance, and organizational design itself. And in a world of extreme competition where those able to deploy AI tools most effectively win perhaps the biggest race of all, it is imperative to understand that the thing between you and success is the reliability of the platform that is used to shoulder all that innovation.

In the years ahead, success will depend not on better tools, but on new mental models: platforms as long-term capabilities, not projects; golden paths not only for code, but for cost, risk, reliability, AI and more. The most effective organizations will embed intelligence, automation, security and policy directly into their production systems, enabling knowledge workers and AI agents alike to operate safely, securely and efficiently at scale.

Those who invest now in people, readiness, and platform maturity will define the next decade of innovation. Those who hesitate will accumulate organizational debt that becomes increasingly expensive to unwind. The transformation is already underway. The question is no longer whether platform engineering matters, but who is prepared to build their future on it.