This idea of asking how much can be implemented in a given sprint is an important clarification. Though, this can be impractical and/or sub-optimal for many con

This idea of asking how much can be implemented in a given sprint is an important clarification. Though, this can be impractical and/or sub-optimal for many contexts. The one-size-fits-all approach of scrum, where so often it is a company or a new person joining and just declaring that "we'll do scrum" now is where things can get de-railed because it is not the universal way to do all development. So, to paraphrase the distinction, instead of death marching for a large set of features without any feedback, the team decides "we won't do more than 2 weeks of work at a time before we ship & deploy some feature." (I really wish I could find the link) A recent hacker news article looked at this situation and noted how this does not really allow for extensive R&D where there is no deliverable after the end of two weeks. An example was Google BigTable which had no deliverable at all for 8 months. Yet, the investment into BigTable lead to a very huge pay-off, and the point made was that there was no good way to break up the R&D required into two week deliverables, and the ROI of that work was far more than most any 2 week increment. Overall the issue for scrum is context, it has its places where it works well - but it is not the one-size fit all solution that so many places try to make it out to be. For example, two weeks does not always allow for a lot of rework, experimentation, architecture, and R&D. A team can choose to make a deliverable be "the results of R&D", is this still fungible thinking and is not actually delivering a release. Personally I would be a lot happier whenever a scrum master and/or product owner/manager that run a scrum team could clarify exactly when scrum is a bad fit (this feels like the expert-beginner problem). If a person knows when scrum is a bad fit, they can at least try to mitigate those problems and/or lean on other development methodologies. It is almost like silo'ing into one programming language and using only that language despite it not being the best tool in some situations (and also of detriment, various alternative techniques are not learned; eg, sometimes a bash script is the right tool to use, and not branching out and trying to solve some problems with a full blown programming language leads to a lot slower of a solution. To illustrate this, Amazon once had a team spend time to find all phone numbers on its website. This took a long time and the program was complex and never worked well, a very competent shell scripter got wind of this and solved it in 15 minutes with a bash one-liner. This became an interview question at Amazon at one point even, in part to check if a candidate will realize that their language of choice might be a bad fit for the problem at hand)