Are We Returning to the Webmaster Era, in the Age of AI?
More than 30 years ago, when the web was just beginning to spread,
there was a role called the webmaster.
The webmaster handled everything,
design, HTML, early CSS, backend scripts, server setup, and maintenance.
One person owned the entire website.
This wasn’t because webmasters were superhuman.
The systems were simpler, and the ecosystem was limited,
making this all-in-one responsibility possible in the mid-1990s.
Specialization Was Inevitable
As the web evolved, complexity increased rapidly.
Traffic grew.
Data accumulated.
Security risks emerged.
User experience became a competitive advantage.
At that point, specialization was unavoidable.
Roles split into frontend and backend,
then further into DevOps, SRE, security, and data.
After decades of building software and leading engineering teams,
I’m convinced this specialization was essential for scale and reliability.
Where the Real Bottleneck Is Today
Today, something fundamental has shifted.
AI assists with:
- Code generation and refactoring
- Test creation
- Infrastructure and deployment drafts
- Security analysis
- Documentation
AI is not perfect, and human judgment is still required.
But execution itself is no longer the primary constraint.
The real bottleneck has moved.
It is no longer speed,
it is understanding and judgment.
Understanding why something should be built,
and judging how it should fit within users, teams, and systems.
Role Convergence Is Quietly Returning
This shift isn’t limited to engineering.
Marketing, design, planning, and analysis are experiencing the same change.
AI handles much of the operational workload,
while humans focus on meaning, direction, and decisions.
Roles are not disappearing.
They are re-converging around broader responsibility.
We are not going back to shallow generalists.
We are moving toward integrators,
people who can see the whole system and guide it.
This Is Not the Old Webmaster
There is an important difference.
The original webmaster did everything manually.
The modern version doesn’t.
In the AI era, value comes from the ability to:
- understand intent
- evaluate outcomes
- connect people, tools, and systems
- and guide AI effectively
In many ways, we are returning to an integrated role,
but at a much higher level of abstraction.
What Experience Means Now
After decades in engineering, my view of seniority has changed.
Experience today is less about knowing every solution
and more about:
- framing the right problems
- recognizing patterns across teams
- designing collaboration, not just systems
- knowing when not to build
AI optimizes performance.
Humans optimize understanding and judgment.
That is where the real leverage now lives.