We can certainly do better, but it takes a _lot_ of time, effort, care and discipline; something most teams don't have, and most projects can't afford.
Bugs arise from the inherent complexity introduced by writing code, and our inability to foresee all the logical paths a machine can take. If we're disciplined, we write more code to test the scenarios we can think of, which is an extremely arduous process, that even with the most thorough testing practices (e.g. SQLite) still can't produce failproof software. This is partly because, while we can control our own software to a certain degree, we have no control over the inputs it receives and all of its combinations, nor over the environment it runs in, which is also built by other humans, and has its own set of bugs. The fact modern computing works at all is nothing short of remarkable.
But I'm optimistic about AI doing much better. Not the general pattern matching models we use today, though these are still helpful with chore tasks, as a reference tool, and will continue to improve in ways that help us write less bugs, with less effort. But eventually, AI will be able to evaluate all possible branches of execution, and arrive at the solution with the least probability of failing. Once it also controls the environment the software runs in and its inputs, it will be able to modify all of these variables to produce the desired outcome. There won't be a large demand for human-written software once this happens. We might even ban software by humans from being used in critical environments, just like we'll ban humans from driving cars on public roads. We'll probably find the lower quality and bugs amusing and charming, so there will be some demand for this type of software, but it will be written by hobbyists and enjoyed by a niche audience.
Bugs arise from the inherent complexity introduced by writing code, and our inability to foresee all the logical paths a machine can take. If we're disciplined, we write more code to test the scenarios we can think of, which is an extremely arduous process, that even with the most thorough testing practices (e.g. SQLite) still can't produce failproof software. This is partly because, while we can control our own software to a certain degree, we have no control over the inputs it receives and all of its combinations, nor over the environment it runs in, which is also built by other humans, and has its own set of bugs. The fact modern computing works at all is nothing short of remarkable.
But I'm optimistic about AI doing much better. Not the general pattern matching models we use today, though these are still helpful with chore tasks, as a reference tool, and will continue to improve in ways that help us write less bugs, with less effort. But eventually, AI will be able to evaluate all possible branches of execution, and arrive at the solution with the least probability of failing. Once it also controls the environment the software runs in and its inputs, it will be able to modify all of these variables to produce the desired outcome. There won't be a large demand for human-written software once this happens. We might even ban software by humans from being used in critical environments, just like we'll ban humans from driving cars on public roads. We'll probably find the lower quality and bugs amusing and charming, so there will be some demand for this type of software, but it will be written by hobbyists and enjoyed by a niche audience.