Now that the prototype is complete and validated, it is time to start building the rest of your AI system. The prototype tackled a few top-priority user stories, but building the production system will be about completing the rest of the user stories you identified during the “Defining the Project” step.
Before your development team starts building the rest of the user stories, however, it is prudent to go through the existing user stories list to ensure that they are all still valid. Over time, your priorities might have shifted or you might have learned more from building the prototype. For instance, perhaps another team already implemented one of the AI models that your system was going to need to use in their system. Instead of implementing the same AI model, you can save development and debugging time by using theirs. Further methods for increasing AI model reuse will be discussed in the next chapter. In this way, user stories may need to be updated or dropped to ensure that users will still receive value for each production user story.
Reusing the Prototype vs. Starting from a Clean Slate
There are differing viewpoints on leveraging prototype code when building a full production system. Some are of the mindset that you should throw away the prototype code completely and start from scratch, taking only what you have learned. This way, you are not bringing over suboptimal code and initial bad practices. Others say to start with the same code base and ...
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