Week 1: AI Native — A Term You Might Not Know Yet, But Will Soon Need to Understand
Every once in a while, a new term enters the conversation before most people notice it.
Right now, one of those terms is AI Native.
You might not have heard it yet—and if you have, it probably wasn’t clearly defined.
But make no mistake: if you're leading platforms, teams, or technical orgs, this concept is coming for you.
The question is whether you’ll define it for yourself, or wait until someone else does it for you.
What People Are Saying
If you search online today, here’s what you’ll find:
“AI Native systems have AI capabilities that are intrinsic and trustworthy.” — Splunk
“AI Native refers to companies built from the ground up with AI at their core.” — Foundation Inc
“Becoming AI Native is rewiring your company DNA.” — Forbes Tech Council
“AI Native systems are designed for continuous learning.” — Studio Global
It sounds promising.
But when you look closer, none of these definitions really say what it means in practice.
- What does “AI at the core” actually change?
- What happens to how we structure teams, build systems, or deliver software?
- How do we know when something is AI Native, and when it’s just an AI feature in disguise?
Right now, there are more questions than answers.
That’s where this newsletter begins.
The Shift Ahead
We believe the shift toward AI Native will eventually reshape how modern companies work—just like Cloud Native did ten years ago.
But we’re still early.
And like Cloud Native in 2014, the pillars of this new era haven’t been agreed on yet.
Back then, we started with containers, CI/CD, and orchestration.
It took years—and painful transformations—to realize the real goals were:
- Scalability
- Resilience
- Flow of value
Today, we’re at a similar moment.
People are experimenting. Startups are making bold claims. Enterprises are adding “AI” to their stack.
But the real shape of this change is still forming.
What AI Native Isn't
AI Native isn’t just about adopting AI tools.
It’s not about prompt engineers or dashboards.
It’s not about replacing humans with chatbots—or reducing cost. (Jevons paradox)
It’s about rethinking how systems evolve—and what we expect from them.
In the past, we built for predictability.
In the future, we’ll need to build for learning, unpredictability, and constant adaptation.
Big Questions
- What does that mean for your architecture?
- For your team structure?
- For trust, observability, and flow?
That’s what we’re here to explore.
About Waves of Innovation
This newsletter is grounded in decades of transformation work—from monolith to Cloud Native, and now from Cloud Native to AI Native.
Each week, we’ll examine one idea, shift, or pattern worth paying attention to.
We’ll draw from real transformation projects, early experiments, and the upcoming Next Transformation book by Pini Reznik and Michael Mueller.
We’ll offer real insight for leaders navigating change—while most of the industry either lags behind or never catches on at all.
If you’re reading this now, you’re early.
That’s your advantage. Let’s use it well.
Questions for You
- When you hear “AI Native,” what do you think it should mean?
- What would have to change in your org for AI to become part of the system, not just a tool?
- What happens if we let the wrong people define this shift?
(Contact us at anytime. We’re learning together.)
Key Takeaways
- AI Native is a new and emerging concept—most definitions today are vague or superficial
- It’s not about tools—it’s about systems, behavior, and organizational design
- Just like Cloud Native, its real meaning will come from how teams adopt it in practice
- The earlier you engage, the more influence you’ll have over how it’s shaped