One of the biggest mistakes I made in the early days of Pangea was trying to build the perfect product before we had users who cared. The instinct — to build it right the first time — cost us years.
The lesson I eventually learned, and the principle I operate by now, is this: ship fast, then systematize. Get something into the world, see if anyone cares, and only then invest in building the systems to scale it.
Speed is a feature. Y Combinator hammered this home. The entire batch is structured around one question: what can you accomplish between now and Demo Day? Pick a KPI, grow it week over week. That forcing function compressed our decision-making and cut through the noise.
But speed without systems creates chaos. If all you do is move fast, you accumulate technical debt, operational debt, and organizational debt that eventually buries you. The companies that scale are the ones that know when to shift from exploration to systematization.
AI has changed the equation. Right now, I run three different projects with nine active work streams. I'm reinventing Pangea's entire tech stack using AI coding agents to move faster than a traditional engineering team could. The "ship fast" part has gotten dramatically faster. You can go from idea to working prototype in hours, not weeks. But the "systematize" part is just as important as ever.
Start with the smallest thing that could possibly work. No feature flags, no configurability, no abstraction layers. Just make it work. Talk to users immediately. Once you have signal, systematize ruthlessly. Build the data infrastructure, write the automations, create the dashboards. If you do something twice, automate it the third time.
The future of building belongs to people who can move between creation and systematization fluidly — who know when to be scrappy and when to be rigorous. AI makes the fast part faster. But knowing what to build, and when to build it properly, is still the hard part.