A common problem in the privacy technology circle is the obsession with stacking algorithms in laboratories while ignoring real-world scenarios.

A technical leader once experienced a painful lesson. He designed a agricultural product traceability system for a public welfare organization, choosing the most popular privacy protocol at the time. The laboratory test results were almost perfect—encryption strength met standards, verification was lightning-fast, and the theoretical framework was flawless.

But once in the field, all the impressive data collapsed.

Network connectivity in mountainous areas was extremely unstable, taking over ten minutes to upload a single data point. The farmer looked at the phone screen with a confused expression, completely unable to understand key management, and data was mistakenly deleted five times in three days. Existing hardware devices were completely incompatible with the system, and upgrade costs doubled, exceeding the budget. This so-called "world-changing" technical solution became scrap metal in reality.

"In our tests, we always compare whose algorithm is more dazzling, but never ask whether users will use it, whether network conditions allow it, or if there is enough funding," he summarized in his failure report.

This "lab thinking" is too common in the privacy technology circle. Researchers are busy publishing papers and optimizing metrics, but few actually take their solutions into real-world scenarios for testing. Only after a project hits a wall and blood is shed do they begin to reflect on the gap between technology and application.

Then a turning point appeared. He started paying attention to privacy solutions like Walrus that focus on practicality. The difference is that these solutions consider "boring" but critical factors such as network fluctuations, device compatibility, and user experience from the very beginning.