Let's be brutally honest: legacy software companies are getting their lunch eaten by AI-native startups. And it's not even close.
While established players continue to map out waterfall roadmaps and schedule quarterly planning rituals, nimble upstarts like Cursor, GitHub Copilot, and countless others are shipping features at a pace that would give traditional product managers heart palpitations.
The gap isn't just noticeable—it's existential.
The Elephant in the Enterprise Room
Here's the uncomfortable truth most enterprise leaders refuse to confront: your development velocity problem isn't primarily about your developers. It's about everything *surrounding* your developers.
Your developers are smart. They're capable. But they're often drowning in organizational quicksand before they ever write a single line of code.
Let's paint the picture: "Jane Developer" arrives Monday morning, coffee in hand, ready to implement that brilliant solution she conceived over the weekend. But before she touches her IDE:
- She needs to request access to three different services
- She has to wait for DevOps to provision the right environment
- She's hunting down credentials for dependencies
- She's updating configuration files
- She's fighting with the VPN
- She's waiting for approvals from three different teams
Four hours later, she might - *might* - be ready to actually start coding. By then, an AI-native startup has already shipped two features and started on a third.
The Myth of "Cultural Transformation"
Every enterprise consultant will tell you that what you need is a massive cultural transformation.
"Agile mindset!" they'll proclaim, as if chanting an incantation. "DevOps principles!" they'll insist, while charging by the hour.
This is both true and utterly useless advice.
Yes, culture matters. But culture changes at the speed of molasses in January. And while you're busy running workshops about agile principles, your AI-native competitors are capturing your market.
So here's my controversial proposition: stop trying to change how people *think* about development and start removing the obstacles that stand between them and actual coding.
The Plumbing Revolution You're Missing
What if the unlock isn't about teaching old dogs new tricks, but about removing the hurdles from the track altogether?
The real revelation hiding in plain sight is this: legacy companies don't need to completely reinvent how they build software; they need to eliminate the friction that exists before coding begins.
I call this "invisible plumbing" – the infrastructure layer that simply makes obstacles disappear without requiring developers to even think about them.
Imagine a world where:
- Development environments self-configure based on the task at hand
- Access control is predictive and proactive rather than reactive
- Dependencies and secrets are automatically resolved
- Integration testing happens continuously in the background
This isn't science fiction. The technology exists right now to create this reality. What's missing is the will to implement it.
The ChatGPT Effect Is Coming for Enterprise Development
Remember the first time you used ChatGPT for a task you used to do manually? That moment when you realized, "Well, I'm never going back to the old way"?
That's the transformation waiting to happen in enterprise development.
I recently needed to research parenting strategies for my profoundly gifted son. I could have spent days traversing academic papers and books, taking notes, synthesizing information. Instead, I used an AI research assistant to do the heavy lifting in minutes.
The choice between the easy button and the hard path wasn't really a choice at all.
The same principle applies to enterprise development. Once developers experience truly frictionless environments, trying to force them back into the old way won't just be difficult—it will be impossible.
The Hard Truth About "Hard" Changes
Enterprise leaders love to say, "Change is hard." It's the perfect excuse for maintaining the status quo. But let's challenge this assumption: Is change really that hard when the alternative is dramatically better?
Change is hard when:
- The benefits are marginal
- The learning curve is steep
- The outcome is uncertain
Change is surprisingly easy when:
- The new way is 10x better
- The friction to adopt is minimal
- The results are immediately visible
This is why the "plumbing" approach is so powerful. It doesn't ask developers to change how they work; it simply removes the obstacles that prevent them from working effectively.
Your Competitors Aren't Waiting
While you're reading this, contemplating whether your organization is ready for change, your AI-native competitors have shipped three more features.
The uncomfortable reality is that the gap between traditional software companies and AI-native startups isn't static—it's widening every day. Each innovation in AI tooling accelerates the divergence.
The longer you wait to address the fundamental plumbing issues in your development process, the further behind you'll fall.
The Path Forward
So what's the concrete action plan for an enterprise company that wants to close the speed gap?
- Stop obsessing over developer behavior and start obsessing over developer experience
- Identify and eliminate every friction point that exists before code can be written
- Invest in "invisible plumbing" that makes development feel effortless
- Measure time-to-first-line-of-code as your most critical metric
- Reward teams that remove obstacles rather than those who "manage" them
The companies that will survive the AI revolution aren't necessarily the ones with the most advanced AI strategies. They're the ones that can ship software fast enough to keep pace with rapidly evolving customer expectations.
The question isn't whether your enterprise can change - it's whether you can afford not to.
What do you think? Is the "plumbing" approach the unlock that enterprise software companies need? Or are there deeper cultural issues that can't be solved with better infrastructure?