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Build a feature-flag engine: deterministic percentage rollouts, targeting rules, and monotonic ramp-up

A 10% rollout where the same user flips on and off between requests is worse than no rollout. The whole problem is determinism: hash the user into a stable bucket so ramping 10% to 25% only ever adds users, never reshuffles them.

Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.

A 10% rollout where the same user flips on and off between requests is worse than no rollout. The whole problem is determinism: hash the user into a stable bucket so ramping 10% to 25% only ever adds users, never reshuffles them.

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