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If you'd read to the end of the article, you would have seen that the author takes a more balanced view: Having said all this, there are times when applying ya
by ScottBurson 11y ago
If you'd read to the end of the article, you would have seen that the author takes a more balanced view:
Having said all this, there are times when applying yagni does cause a problem, and you are faced with an expensive change when an earlier change would have been much cheaper. The tricky thing here is that these cases are hard to spot in advance, and much easier to remember than the cases where yagni saved effort. My sense is that yagni-failures are relatively rare and their costs are easily outweighed by when yagni succeeds.
- lowbloodsugar 11y agoMy point is that the initial assumptions never hold because we can never say "We know this is how it is going to turn out". We can say "This is how we hope it is going to turn out." YAGNI embraces this lack of knowledge explicitly, as you quote from the article, and my quote from five posts up. We're not saying that YAGNI is always better in any specific sample, we're saying YAGNI is an optimal strategy across the entire range of samples.