About
I didn’t transition into product. The work pulled me there.
Career
Choosing quality because quality is where decisions show up.
I studied computer science at Universitas Indonesia. Partway through, I started paying attention to which problems in software were actually hard, not algorithmically but in practice. The answer, consistently, was the gap between what a system was designed to do and what it actually did when real users touched it.
That gap is where quality engineering lives. I chose it not because I wanted to find bugs, but because it put me closest to the full picture: the product intent, the implementation, and the user experience. All at once, most roles in software give you one or two of those. Quality engineering gives you all three, simultaneously, usually under pressure.
My first professional roles confirmed this instinct. The interesting problems were never purely technical. They were decisions that had been made (about scope, about edge cases, about what “working correctly” even meant) that hadn’t been questioned carefully enough, and were now visible as failures in production.
Scale changes the questions you ask.
At Tokopedia, the scope of the problems grew. The systems were larger, the teams were bigger, and the consequences of a production failure were measurable in real business terms. Quality work at this scale stopped being about individual test cases and became about understanding systems: how components depended on each other, where the fragile points were, and what a failure in one place meant for everything downstream.
This is also where my responsibilities started expanding beyond their formal description. At Tokopedia, test engineers were expected to participate actively in cross-functional planning. Not just execute tests, but contribute to readiness decisions, flag risks before they became incidents, and communicate status to product and engineering leadership. I found myself doing that work and noticing that the most important contributions I was making were upstream of execution: shaping how the team thought about the problem before anyone wrote code.
The TokoFood integration (one of the first major joint initiatives following the GoJek-Tokopedia merger) put this into sharp focus. The coordination challenge across multiple teams and two organizational structures was not a testing problem. It was a product problem. I took on the dependency tracking, the cross-team sync, and the stakeholder communication because the project needed someone to do it. Because, honestly, that was the most interesting work available.
Recognizing the direction the work had always been pointing.
By the time I was working within the GoTo Financial ecosystem, the pattern was clear. I kept asking questions that weren’t strictly in my remit: Why are we building this? What does the user actually need here? What’s the simplest version of this that solves the real problem? These are product questions. I was asking them from an engineering chair, which meant I could see the technical constraints clearly, but I wasn’t in the room when the decisions were made.
I want to be in that room. Not because I want authority for its own sake, but because the decisions being made there (about scope, about trade-offs, about what gets cut and what gets kept) determine whether the engineering work that follows matters. Getting those decisions right requires someone who understands what’s technically possible, what the user actually experiences, and what the business needs. That is what I have spent seven years learning to see.
Working style
I work best when the problem is still open.
My instinct when starting a new problem is to map what I don’t know before I map what I do. Assumptions are the most common source of expensive mistakes in product work, and the ones that do the most damage are usually the ones the team agreed on without noticing. I tend to name those explicitly and early.
I write things down to find out what I think: not to share prematurely, but because writing forces precision. A vague concern in your head stays vague until you try to put it in a sentence. The sentence usually reveals whether the concern is real or just noise.
In cross-functional settings, I prefer to understand how engineers think about a problem before I have an opinion about the solution. Not because I defer to engineers. Because the implementation constraints often contain information that should change the product decision, and that information tends to surface in conversation rather than in documentation.
I’m most useful in the space between engineering and product, where the question isn’t “can we build this” but “should we build it this way, and what are we not asking.”
Domain
Fintech products fail in ways that matter.
Most product failures are inconvenient. A fintech product failure can mean someone’s money doesn’t move when it needs to. That distinction changes how you think about edge cases, about reliability, about the difference between a feature working and a feature being trusted. I find that distinction motivating in a way that other domains don’t quite replicate.
Southeast Asia’s financial infrastructure is also genuinely interesting from a product perspective. The regulatory environment, the banking penetration gaps, the diversity of user contexts. A payment product that works well here has to navigate constraints that don’t exist in more mature markets. That complexity produces more interesting product problems. The intersection of compliance requirements, technical reliability, and user trust is exactly where engineering judgment and product thinking both have to be present.
Having worked inside these systems at GoPay and Tokopedia, I also understand the specific failure modes: the edge cases in payment flows that erode trust quietly over time, the coordination challenges of multi-system transactions, the gap between what a fintech product says it does and what a user actually experiences in a moment of financial need. That operational familiarity is hard to develop from the outside. It’s the part of my background I expect to carry furthest in a product role.
What good looks like
The role I want to be in.
I’m looking for Product Manager or Technical Product Manager roles in fintech, payments, or adjacent marketplace products. The distinction between PM and TPM matters less to me than the nature of the work: I want to be close to the technical decisions without being removed from the user ones.
The teams I work best in tend to treat engineering and product as genuinely collaborative. Not as separate functions that hand off work to each other, but as people who are thinking about the same problem from different angles and need each other to get it right. I’ve seen what happens on teams where that relationship is healthy, and I’ve seen what happens when it isn’t. The difference is visible in the product.
The problems I find most engaging are the ones where the solution isn’t obvious. Where scope needs to be defined, not just executed, and where understanding the system is a prerequisite for understanding the user problem. I’m less motivated by optimization work on clearly defined problems, and more motivated by the earlier stage: figuring out what the problem actually is.
Target role
Product Manager · Technical PM
Domain
Fintech · Payments · Marketplace
Location
Jakarta · Open to international opportunities
Experience
7+ years, fintech & marketplace