I've never had a clean career story.
Not because I didn't think about it.
But because even with a plan, the path rarely behaves the way you expect.
The part that was deliberate
Some of the early decisions were very intentional.
I chose to study economics, mathematics, and statistics after a science-focused education because I wanted a path that connected more directly to real-world problems.
I knew early on that industry would be a better fit for me than academia.
I enjoyed research. I was good at it. But I was more drawn to applied work, problems that had consequences, not just answers.
If I had followed that path directly, I likely would have ended up in economics, policy, or financial institutions.
That would have been a cleaner story.
The part that changed the direction
Life introduced a different constraint.
Marrying a software engineer and moving into the Silicon Valley ecosystem made technology a much more natural center of gravity.
That wasn't part of the original plan.
But it was a decision point.
And I leaned into it deliberately.
Choosing breadth over prestige
Once I moved toward technology, I had options.
I had opportunities to join large tech companies.
I chose not to.
Instead, I focused on building AI and data science in non-tech organizations: retail, consumer, and consulting environments.
That choice was intentional.
I wanted exposure to a broader set of problems. I wanted to work closer to business decisions, not just technology. I wanted to understand how systems actually operate, not just how they are designed.
It was a less obvious path.
But it gave me something I would not have gotten otherwise.
The pattern that repeated
Across roles, a pattern started to emerge.
I was often building something that did not exist yet.
Creating teams.
Defining the problem.
Figuring out how to connect models to real decisions.
In earlier roles, this meant starting from scratch. Later, at larger organizations, it meant scaling and consolidating what had already been built.
From the outside, this looks like a linear progression.
From the inside, it felt like a series of decisions around the same question:
What does it take to make these systems actually work?
The through-line that was always there
There are a few things that were consistent, even when the path wasn't.
I've always been interested in how consumers behave, how small changes influence decisions at scale.
I've always cared about business impact: not just building systems, but seeing them change outcomes.
And I've had a long-standing belief in the potential of AI, well before the current wave made it obvious.
That belief shaped more of my career than I realized at the time.
What didn't stay linear
Even with that direction, the path didn't stay clean.
Roles didn't always connect neatly. Some decisions only made sense later. There were periods where I wasn't sure if I was moving forward or just changing direction.
Nonlinear careers sound intentional when you describe them afterward.
In the moment, they mostly feel uncertain.
From planning to direction
For a long time, I tried to plan my career carefully.
At some point, I realized that planning only works up to a point.
The most important opportunities were not the ones I mapped out in advance.
They came through people I chose to work with, problems that felt worth solving, and moments where staying comfortable was easier than changing direction.
Over time, I stopped trying to control each step and started focusing on direction instead.
Not a detailed plan.
An orientation.
Toward work that has real impact.
Toward problems that require building, not just analysis.
Toward environments where I could learn faster than I was comfortable with.
That turned out to be more reliable than any long-term plan.
Why I stepped away from the predictable path
By the time I reached senior leadership roles in enterprise AI, the path finally looked clear.
The next roles were visible. The scope would grow. The trajectory made sense.
But what I enjoyed most was never the predictability.
I liked building.
I liked the early stages, where nothing exists yet and you have to figure it out.
And I wanted to be closer to where AI was evolving most rapidly.
That combination made the decision clear.
I could stay on a well-defined path.
Or I could move closer to the part of the problem that interested me most.
What building changed
Starting Toutami was not something I had planned years in advance.
But it was consistent with everything that came before.
A belief in AI.
A preference for building over maintaining.
A desire to work on systems that matter in real life.
It also made one thing very clear.
The gap between what is possible and what actually works is still large.
That is where I want to spend my time.
What I believe now
I don't think planning is useless.
But I don't think it is sufficient.
You can make deliberate choices.
You can choose direction.
You can build skills that compound.
But you cannot predict the exact path.
The path is shaped by decisions you cannot fully anticipate.
And often, the most important ones don't look obvious at the time.
I don't expect my career to stay linear.
But I also don't think it ever was.
It just took time to see the pattern.