That second title is one I'm claiming for myself. Let me explain why.
For over 16 years, I've worked in infrastructure and technology - building systems, consulting for enterprises, and watching technology cycles unfold. I've seen hype come and go. I've learned to tell the difference between noise and signal.
Today, I work as a Product Manager at Mavvrik, where I focus on AI cost governance. It's a space I find endlessly fascinating.
Here's what drew me in: Everyone is building AI agents. But few are asking the harder questions about what they actually cost - and what they should cost.
Not just the API bills. The deeper economics. Why do similar agents have wildly different cost profiles? Where does the money go in multi-step workflows? What's worth optimizing, and what isn't?
These questions drive my curiosity. They're what I spend my time thinking about.
Why "AI Economist"?
FinOps taught enterprises to manage cloud costs. But AI agents introduce new challenges.
They're non-deterministic. Multi-step. They call other agents. They retry. They reason in loops. The patterns are different from traditional infrastructure.
Someone needs to map the economics of this new paradigm. How to measure it. How to think about it. How to make it sustainable.
That's the work I find meaningful. That's what I'll write about here.
What to Expect
This blog is where I'll share my thinking on:
Agent economics - What AI agents cost and why it matters
Product building - Lessons from working in an emerging space
Cost governance - Frameworks for understanding AI spend
The business of AI - Where value gets created and captured
I'll share what I'm learning along the way. The insights. The questions. The ideas worth exploring.
One Belief
AI agents will become infrastructure - like databases, APIs, and cloud compute before them.
And like all infrastructure, making them economically sustainable will matter.
I'm excited to be working in this space, and I'm grateful you're here.
If these topics interest you, subscribe. Let's learn together.
Dinesh