In distributed systems, solving the right problem at the wrong time is just an expensive way to die. We've all been to the optimization buffet - tuning whatever looks tasty until things feel 'good enough.' But here's the trap: your system will fail in a specific order, and each constraint gives you a limited window to act. The ideal system reveals its own bottleneck; if yours doesn't, that's your first constraint to solve. Your optimization workflow itself is part of the system under optimization.
3 posts in this series
Users abandon before experiencing content quality. No amount of supply-side optimization matters. Latency kills demand and gates every downstream constraint. Analysis based on Duolingo's business model and scale trajectory.
22 November 2025Once latency is validated as the demand constraint, protocol choice determines the physics floor. This is the second constraint - and it's a one-time decision with 3-year lock-in.
29 November 2025While demand-side latency is being solved, supply infrastructure must be prepared. Fast delivery of nothing is still nothing. GPU quotas—not GPU speed—determine whether creators wait 30 seconds or 3 hours. This is the third constraint in the sequence—invest in it now so it doesn't become a bottleneck when protocol migration completes.
06 December 2025