For AI to produce mission-critical software, developers must explicitly define what 'good' looks like and establish clear success criteria upfront, as AI systems will iteratively work toward these defined goals but cannot determine quality without clear parameters.
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Deep Dive
Can AI produce mission critical software? Defining what good looks like vital #AI #sdlc #softwareAdded:
I think for any software project, you have to have some idea of what good looks like. And and I think sometimes it's harder and sometimes it's easier.
But, how you know, as a human, right?
You're going to do a software project.
At some stage, you got to decide whether it's good enough to ship or you're done or whatever happens to be. So, you still need to know what your definition of good is in that point. The advantage and and I think in the old human world, you would kind of start the project and you kind of worry about that for down the road. Which was always, I think, an error, actually. You know, better projects were the ones that thought about how you're going to test it and define what what good looked like up front. But, I I think in the the AI world, that becomes utterly critical because otherwise, you you're basically saying to the engineering team of coders or whatever, "Go and create this thing.
I'm not going to tell you what I really want. I'm not going to define what good looks like or your success criteria.
Just go and build something." And then they don't know. Whereas, once you've defined something that the AIs are tenacious and they will be able to iterate against that and just keep going and going and going and going and going until till they've solved it.
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