If you've been in tech over the last year, you've probably noticed that almost every conversation eventually ends up talking about AI.
LLMs, AI Agents, RAG, MCP, prompt engineering...there's something new every week.
Like many of you, I've been spending time learning these technologies, experimenting with different tools, and trying to understand where everything is heading.
But while learning AI, one question kept coming back to me.
Whre does AI actually fit within Enterprise Architecture?
Most conversations start with the model.
I think they should start with the enterprise.
Looking Back
Over the last two decades, I've worked through several technology shifts.
Physical infrastructure → Virtualization
Virtualization → Cloud
Cloud → Platform Engineering
Automation → Everything
Every transition introduced new tools, new platforms, and new buzzwords.
But something interesting never changed.
Successful enterprise systems still depended on the same fundamentals:
Business goals
Enterprise Architecture
Reliable platforms
Security
Data
Governance
Operations
Technology changed.
Engineering principles didn't.
That's one of the reasons I don't see AI as something completely separate.
AI Is Just Another Enterprise Capability
Today, AI is often treated like its own universe.
Dedicated AI teams.
AI platforms.
AI roadmaps.
AI strategies.
That all makes sense.
But I think there's a risk if we start treating AI as something that sits outside Enterprise Architecture.
AI doesn't work in isolation.
It needs good data.
It needs infrastructure.
It needs platforms.
It needs security.
It needs governance.
It needs integration with business applications.
And, most importantly, it needs to solve a real business problem.
From an architect's point of view, AI isn't an island.
It's another enterprise capability.
Just like databases, APIs, messaging platforms, Kubernetes, and cloud services became part of our enterprise landscape, AI is becoming another capability that needs to be architected—not bolted on.
The Enterprise Architect in Me
One thing I've always liked about Enterprise Architecture is that we rarely start with technology.
We usually ask questions like:
What business problem are we solving?
Which capability are we improving?
What data do we need?
How will this integrate with existing systems?
How do we operate and govern it?
Only then do we choose the technology.
Personally, I think AI deserves the same treatment.
Instead of asking:
"How do we implement AI?"
maybe we should ask:
"Which business capabilities can benefit from intelligence, and how should we architect that?"
It's a small change in thinking, but I believe it leads to much better solutions.
It's About More Than Models
Right now, everyone is comparing models.
Who's faster?
Who's smarter?
Who's cheaper?
Those are interesting discussions.
But in the enterprise, success usually comes down to questions like:
Can we trust the data?
Is it secure?
Can we scale it?
Can we operate it?
Can we govern it?
Does it actually create business value?
Those aren't AI questions.
They're engineering questions.
And we've been dealing with them for years.
Why I Started HELIX
Over the last few months, I've been documenting my learning and trying to connect the dots between Enterprise Architecture, Platform Engineering, and AI.
That became HELIX.
It's simply my engineering journal.
A place where I share ideas, architectural viewpoints, experiments, and lessons as I continue learning.
Some posts will be architecture-focused.
Some will be hands-on.
Some may simply be questions I'm still trying to answer.
And that's okay.
Technology evolves, and so should our thinking.
Let's Discuss
This is just one perspective.
I'm genuinely interested in hearing how others see it.
Do you think AI should be treated as its own discipline?
Or do you see it as another capability within Enterprise Architecture?
How is your organization approaching Enterprise AI?
What challenges have you run into?
I'd love to hear your thoughts in the comments.
If you're an architect, platform engineer, developer, or just someone exploring AI in the enterprise, let's learn from each other.
Final Thoughts
AI will continue to evolve.
New models will come.
New frameworks will appear.
But I believe good engineering principles will remain the same.
Business.
Architecture.
Platforms.
Governance.
Operations.
AI doesn't replace those foundations.
It builds on them.
That's the journey I'm exploring through HELIX, and I hope you'll join the conversation
Thanks for reading! 👋
This is the first article in my HELIX series, where I'll be exploring the intersection of Enterprise Architecture, Platform Engineering, and Artificial Intelligence. If you enjoyed this article or have a different perspective, I'd love to hear from you. Let's build the discussion together.
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