AI Native problem library

Search names and tags without changing the input.

Clean up strings and report invalid fields.

Keep the latest event per ID in a stable order.

Build pagination that handles boundary values.

Group paid orders and rank category totals.

Merge overlapping or touching booking intervals.

Rebuild the final task list from an action log.

Assign jobs to workers and calculate completion times.

Produce a valid execution order and detect cycles.

Find minimum reachable costs in a directed graph.

Implement a capacity-limited cache that tracks recency.

Limit requests within each user’s sliding time window.

Fix whitespace, duplicate tags, defaults, and input mutation in existing code.

Reject insufficient stock and invalid quantities while preserving stock and reservation consistency.

Fix expiration boundaries, updates, and recency in an existing cache.

Normalize Unicode labels into stable URL slugs.

Mask sensitive fields in nested JSON logs.

Compare numeric version segments with stable ties.

Apply capped exponential backoff and stop conditions.

Repair mutation and off-by-one cursor behavior.

Handle embedded commas, newlines and escaped quotes.

Apply each event ID once and aggregate account balances.

Evaluate wildcard rules with deny overriding allow.

Merge nested objects, delete null fields and replace arrays.

Bucket requests and aggregate errors and durations.

Maximize context priority under a token budget.

Rank cosine similarity with zero vectors and stable ties.

Preserve overlap and correctly stop at the final chunk.

Track consecutive failures and exact cooldown boundaries.

Maintain sliding medians for odd and even windows.