This is a clever problem, and it exposes exactly where traditional spreadsheets start to break down. The user has built a system that works, parsing event titles for keywords, subtracting hours from category buckets, but the moment a session crosses midnight, the logic falls apart. That's not a limitation of their effort. It's a limitation of the tool itself.
What makes this scenario so instructive is how ordinary it is. A studio share with friends, a Google Calendar booking system, a handful of time categories. Nothing exotic. Yet the user is already thinking about edge cases: a session that starts at 8 PM and ends at 2 AM. They need to split that duration into pre-midnight and post-midnight segments, because late-night hours shouldn't cannibalize their DND or walk-in allocations. In a traditional spreadsheet, solving this means writing a conditional formula that checks whether the end time is earlier than the start time, then calculating two separate intervals. It's doable, but it's brittle. Add one more rule, say, a different rate for sessions that start before 6 AM, and the logic multiplies in complexity.
An AI-native approach would handle this differently. Instead of forcing the user to encode every rule as a formula, it would let them describe the problem in plain language: "Split any session that crosses midnight into two rows, one for each calendar day, and assign the hours to the correct category." The AI would parse the intent, generate the transformation, and apply it consistently across all past and future entries. The user wouldn't need to debug a nested IF statement or worry about what happens when daylight saving time hits. They'd simply see accurate totals for each person and each hour type.
This is the shift that matters. Spreadsheets are powerful, but they reward users who think like programmers. Most people don't want to think like programmers. They want to manage their studio time, split costs fairly, and move on. An AI-native spreadsheet doesn't ask them to learn new syntax. It asks them what they need, then builds the logic for them. That's not a futuristic promise. It's a practical solution for the problem right in front of us: a session from 8 PM to 2 AM that needs to become two clean, categorized entries. The user already knows what they want. The tool should be smart enough to do the rest.