Gnobu

I’ve been noticing a pattern across different systems (security, payments, operations):

Most systems treat identity as something stable — once verified, it’s assumed to remain consistent.

But in real-world usage, identity behaves differently depending on:

• context (location, environment, timing)

• intent (what the user is trying to do)

• interaction flow (sequence of actions)

This creates a mismatch.

So systems compensate by:

• collecting more user data

• adding more rules

• increasing verification steps

Yet issues still show up:

• legitimate users get blocked

• risky behavior passes through

• systems behave inconsistently under edge cases

It feels like the limitation isn’t identity verification itself — but the assumption that identity is static.

Curious how others here think about this:

Are there practical ways to model identity as something dynamic without making systems overly complex or slow?