Developers worldwide use AI to write code faster, but speed creates new failure risks. The speaker argues you need stronger quality assurance, user acceptance testing, and human validation throughout development to catch what AI misses.
Chapters
When I'm talking to a lot of people who are interviewing potential developers, some of the biggest concerns that they have is the potential of developers, whether they're in San Francisco or Brazil or the Philippines, leveraging AI to produce their code and just kind of the level of protection there. And so it's something that I think is going to continue to evolve where I think that AI is going to certainly speed up the time to ship. I think it's going to call for a greater emphasis on things like quality assurance, user acceptance testing. Things like that, because I think the code can get shipped pretty quick. But if it doesn't have like a human element working through it, I think there are numerous failure points. So what I would tell anybody who is considering hiring is that the development process itself, it's just one component of it all. You really have to think holistically about, am I really QAing this pretty hard to make sure that it's working and I'm validating