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When I am trying to decide how much time I should spend on product 'quality' (robustness, bug free, elegant design) I always think of it in the context of exper

When I am trying to decide how much time I should spend on product 'quality' (robustness, bug free, elegant design) I always think of it in the context of experiments. The product is actually a byproduct of a sequence of experiments where the true focus is 'learning outcomes'. I consider the best experiments those which you learn the most at the cheapest cost. For a given experiment, if a poorly designed product gives you "outs" and makes your experiment less conclusive ie) well the users _might_ think this, but it also might be because my product looks like a POS. Well that isn't a very good experiment to execute. There are definitely high quality experiments you can perform where the product quality itself is poor but the learning outcome is high. This is especially true if you can filter your data set (only consider early adopters for example)

rmoriz 13y ago
The opposite can be true, too. Imagine you build something like a paid 4chan in AngularJS (e.g. not really new business idea combined with rather new technology). You might get false positives because some people just subscribe because of the new technology. They are not really interested in the product but just to watch the execution/implementation to learn for themselves. This is not sustainable because those customers will quit as soon as they got their findings out of your experiment.
- enos_feedler 13y ago
  My main point was to be experiment driven and let the requirements flow from that. The idea of filtering by early adopters is just a suggestion on how to think "experimental results first" and that you don't need to run your experiment across 'everybody' in order to get the results you need (as there are surely some people in this set who demand polish/perfection). In regards to what you are saying about early adopters giving you false positives, it depends on what assumptions you are testing in your experiment. What is your hypothesis in this experiment?

rmoriz 13y ago

The opposite can be true, too. Imagine you build something like a paid 4chan in AngularJS (e.g. not really new business idea combined with rather new technology). You might get false positives because some people just subscribe because of the new technology. They are not really interested in the product but just to watch the execution/implementation to learn for themselves. This is not sustainable because those customers will quit as soon as they got their findings out of your experiment.

enos_feedler 13y ago
My main point was to be experiment driven and let the requirements flow from that. The idea of filtering by early adopters is just a suggestion on how to think "experimental results first" and that you don't need to run your experiment across 'everybody' in order to get the results you need (as there are surely some people in this set who demand polish/perfection). In regards to what you are saying about early adopters giving you false positives, it depends on what assumptions you are testing in your experiment. What is your hypothesis in this experiment?