Yeah, this is a succinct way to describe a
very important dynamic in software engineering that is usually unfamiliar to most inexperienced developers but a central facet of most experienced developers.
Software engineering is almost always a process of iteration. The better you get at iterating, the better you are at engineering. This can take on a lot of forms (my old manager would constantly repeat the mantra "don't let perfect be the enemy of good," which is arguably a recognition of the same dynamic), but at the end of the day, if you expect to "one-shot" a complex implementation and you build a process around that assumption, then you will fail. Almost ironically, the best way to avoid that issue is to assume you will fail (potentially multiple times) and to build a process around that assumption.
Interestingly, it seems like a lot of experienced engineers I work with have just forgotten this concept in the world of AI. They expect AI to just get things perfect in one-shot and are dismayed when it fails. There's a lot of discussion around how we handle code reviews because some developers are just letting AI one-shot a solution then sending it to review. It boggles my mind that competent engineers aren't allowing their AI to fail, so to speak, and are instead wasting cycles trying to figure out how to get AI to produce the perfect solution the first time.
To me, it's obvious that there's just a fundamental gap in alignment that prevents a consistent "perfect one-shot" to probably ever be possible (at least, within the current paradigm of development). I can spend an hour writing a spec and try to include every little detail of context I can think of, but in what world could we expect anyone, let alone an AI, to be able to envision the solution the same way we can? We just lose way too much information through communication for that to ever be possible. Yet I see people very dismissive of the capabilities of AI because it's not literally magic.
Software engineering is almost always a process of iteration. The better you get at iterating, the better you are at engineering. This can take on a lot of forms (my old manager would constantly repeat the mantra "don't let perfect be the enemy of good," which is arguably a recognition of the same dynamic), but at the end of the day, if you expect to "one-shot" a complex implementation and you build a process around that assumption, then you will fail. Almost ironically, the best way to avoid that issue is to assume you will fail (potentially multiple times) and to build a process around that assumption.
Interestingly, it seems like a lot of experienced engineers I work with have just forgotten this concept in the world of AI. They expect AI to just get things perfect in one-shot and are dismayed when it fails. There's a lot of discussion around how we handle code reviews because some developers are just letting AI one-shot a solution then sending it to review. It boggles my mind that competent engineers aren't allowing their AI to fail, so to speak, and are instead wasting cycles trying to figure out how to get AI to produce the perfect solution the first time.
To me, it's obvious that there's just a fundamental gap in alignment that prevents a consistent "perfect one-shot" to probably ever be possible (at least, within the current paradigm of development). I can spend an hour writing a spec and try to include every little detail of context I can think of, but in what world could we expect anyone, let alone an AI, to be able to envision the solution the same way we can? We just lose way too much information through communication for that to ever be possible. Yet I see people very dismissive of the capabilities of AI because it's not literally magic.