The user who posted this query isn't asking for a revolution. They're asking for a simple, clean way to find duplicate routes in a spreadsheet without breaking the rest of their data. That request reveals something important: traditional spreadsheet tools have conditioned people to expect friction. You have to write formulas, learn conditional formatting, or risk corrupting your dataset just to answer a basic question like "Are any of my routes identical?" That is not a user problem. That is a product problem.
This person's dataset is small and clear. Four rows. Three columns. A straightforward pattern. Yet the fact that they felt the need to apologize for being "a bit of a noob" suggests that the tools they're using have made them feel inadequate instead of empowered. No one should feel like a novice for wanting to spot duplicates. Duplicate detection is a fundamental data operation, not an advanced trick. In a well-designed system, the answer should be visible in one glance or one click. Instead, this user has to navigate workarounds, and that is where the industry has failed them.
What this user needs is a solution that treats their data with respect. They don't want to rearrange columns, insert helper columns, or write nested functions. They want to see which rows share the same departure and destination, and then move on with their work. That is a human-centered outcome. An AI-native spreadsheet should understand intent, not syntax. It should look at a table like this and surface the duplicates without the user having to translate their request into formula language. The technology exists to make that happen. The question is whether the tools we use will prioritize user time over tool complexity.
The practical takeaway is straightforward: if you find yourself apologizing for not knowing a spreadsheet trick, the tool is the problem, not you. The future of data management is not about memorizing functions. It is about tools that understand what you are trying to do and help you get there faster. This user's request is a perfect example of a task that should be invisible. Spotting duplicates is not a skill test. It is a data hygiene task. And the best tools will make it disappear into the background so you can focus on what your routes actually mean.