While I certainly don't work at Cisco, I've come to the conclusion that I need to re-examine my priors when it comes to code rewrites and general maintainability.
AI makes these projects significantly more feasible, at least in my domain. We have some critical-path software I wouldn't touch with such an approach, but the vast majority of our code is internal and/or supporting tooling.
For those cases, burning it down and rewriting via AI tooling has proven far more productive than anything we have attempted in the past. This is for old technical debt laden stuff everyone has been afraid to touch for well over a decade.
It's not perfect, but it moves the needle where before a lot of such projects were stuck on the backburner for years.
It certainly introduces new bugs and such, but at least this way forward momentum is happening vs. just being stuck in decision/analysis paralysis forever.
This also assumes some very senior SME folks are driving the process. I would not expect similar results with junior or even mid-level folks in these specific domains.
> While I certainly don't work at Cisco, I've come to the conclusion that I need to re-examine my priors when it comes to code rewrites and general maintainability.
One of the reasons to avoid rewriting has long been that the time spent rewriting code that works is time not spent writing code to meet new business needs. In other words, it's usually a huge opportunity cost, rarely balanced out by sufficient gains to be net positive.
I do think AI does challenge this prior, as the time needed to do a rewrite shrinks dramatically. It's not zero, of course, but it now becomes worth asking if it's worth doing, rather than defaulting to avoiding rewrites in nearly all cases.
Does the coding assistant demonstrate any tricks to improve the likelihood of success for such rewrites?
What works for me is that I do have a different model (if possible) to review and check against the diff vs the original ask/requirement. Because a rewrite will just cleanup the code even if something look 'not right' but it is actually on purpose due to the requirement, so the second model is the one that can check and catch.