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A good architect will choose a tech stack that's within the distribution of AI models training data. This is because the productivity increases to using these tools is huge. And so you want to follow patterns and technologies that take advantage of this.
When you're choosing, it's now prudent to think about how normal your tech stack is.
People often said in the past to choose boring tech stacks. Now the cost to choosing non-boring tech stacks is even higher.
My friend Eric McKay astutely points out that this may create moats and deeper network effects for existing frameworks, especially ones that become popular around the time of a new model's training and release.


















