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scaling-interaction-assumptions

Verify and design for user-base scaling — broader audiences, more diverse use cases, more edge cases, behaviors that weren't anticipated. Use when launching to a new market, scaling from beta to GA, expanding from one team to a company, or any context where the user population is growing or changing. Interaction scaling is often harder than load scaling because it surfaces design assumptions that worked for the original audience but fail for a broader one.

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# Scaling — interaction assumptions

The second kind of scaling fallacy: assumptions about how users will behave, what use cases they'll have, what they'll consider acceptable. A design that works for 100 early users — who tend to be sophisticated, motivated, and tolerant of rough edges — frequently fails for 100,000 broad-audience users who lack those qualities.

Interaction scaling is often harder than load scaling because it requires anticipating how a broader, more diverse audience will use the product. Engineers can load-test infrastructure; product designers have to imagine future users.

## Common interaction-scaling failures

**Original audience assumptions don't transfer.** A productivity tool designed for engineers expects technical sophistication; when adopted by non-technical professionals, the assumptions fail.

**Edge cases become common.** A 1-in-1000 case happens 100 times a day at a million users. Designs that assumed "this won't happen often" find that it does.

**Feature discovery breaks down.** Features that were discoverable when the product had 5 of them become invisible when the product has 50. Users miss capabilities or use them wrong.