The point is to constrain innovation to the areas that you vitally need it.
Say you are building some sort of visual AI startup, say something that does generative AI things with videos.
You would a) use a boring AF web stack b) use ffmpeg and c) don't go and try do a bunch of silly serverless things, d) try use one of the relatively settled model serving platforms if it's viable for you.
Then you can use all of your innovation budget on your model itself, your training infrastructure etc, things that will provide you with a competitive advantage over people trying to do the same thing as you.
Say you are building some sort of visual AI startup, say something that does generative AI things with videos.
You would a) use a boring AF web stack b) use ffmpeg and c) don't go and try do a bunch of silly serverless things, d) try use one of the relatively settled model serving platforms if it's viable for you.
Then you can use all of your innovation budget on your model itself, your training infrastructure etc, things that will provide you with a competitive advantage over people trying to do the same thing as you.