KelolaResto

KelolaResto is a restaurant operations product covering QR ordering, inventory, and day-to-day management. The initial thesis was that useful software still fails when adoption adds friction or operational risk.

I began by studying how orders moved, what owners monitored, where staff lost time, and which workflow changes restaurants could realistically adopt.

I built the first working version in three days, covering the core restaurant workflow and a usable path from QR ordering into daily operations. Over the next three weeks, I expanded and refined the initial feature set while validating the market in parallel.

As the sole product engineer, I owned research, prioritization, interface design, frontend, backend, infrastructure, deployment, and support. AI-assisted tools accelerated research, scaffolding, review, and documentation; I remained responsible for architecture and production decisions.

I visited restaurants and spoke with owners and managers about operations, customer flow, costs, current software, and adoption barriers. I also assessed competitors to understand where a new product could enter and what might justify switching.

The research showed a crowded market where established competitors had strong distribution and operational lock-in. Replacing software embedded in daily operations created meaningful switching risk, even when a new product improved individual features.

There was still room for a differentiated entrant, but the opportunity required a stronger entry point, more time, and more runway than the current approach could support.

The validation did not eliminate the market opportunity. It showed that the current product thesis did not overcome adoption and switching barriers strongly enough.

Rather than continuing to add features because the product already existed, I chose to preserve runway and plan a pivot around the strongest research insights. The result was both a working product and a better-informed decision made before committing more time and capital.