I strongly disagree. Thinking through and handling all of the edge cases that could break my code inevitably takes more time than getting it to work for the few examples I know of and calling it a day. For example, I just wrote a function to generate a rolling average from a timeseries dataset with one data point per day. All of my sample data has exactly one datum per day. But I just know that eventually there will be an issue that causes data gaps, and of course writing code to handle gaps when they occur takes more time than not doing so and ignoring the consequences. And that's not even mentioning the time required to write unit tests.

Furthermore, a lot of the extra time comes not from the initial coding exercise, but the diligence and follow-up required. ie. Cool, I've implemented a feature, but did I go through carefully and ensure that I've removed all my console.logs and commented out experiments? Did I leave dead code anywhere? Did I make any changes that require renaming or refactoring of other parts of the codebase? I never submit a PR these days without carefully going through my own git diff and double-checking myself. I almost always catch something when I do. These things take time.