Original Summary

This is maybe a bit of a rant, but I am quite exhausted recently. Customers demand extremely fast delivery of new features as they are getting used to AI-assisted development and can vibe-code stuff themselves, so naturally they expect us as their software provider to also react to new feature requests with a new release within days instead of weeks.<p>That forces us to use heavily AI-based workflows, but if we&#x27;re honest the speed advantage we can get through that only materializes if we are skipping detailed manual code review of all the AI-changed code, as that produces tons and tons of revisions and edits.<p>What I found after around a year is that the codebase is riddled with inconsistencies and hacks that were quitely introduced by the AI, really ridiciulous stuff sometimes. I&#x27;d say the codebase is close to the point where it will become unmaintainable and we will have to consider a large scale refactor or cleanup, only that with the new pace everyone seems to be going at this becomes very hard. So I&#x27;m feeling a bit trapped, and I become more and more skeptical of AI for software development. Don&#x27;t get me wrong for some things it works great but I think I have to stop using it for large-scale feature implementation or anything that is more complex than glorious refactoring or autocomplete within very narrow bounds, as it&#x27;s just not there yet.<p>And yeah I&#x27;m using the latest and greatest models, even they are not able to produce something that is consistent over the long run it seems. I have also tried writing research papers with Fable and all these other glorified models and that was a disaster as well, can&#x27;t get how people think these things accelerate development by 10x, even 2x seems hard to get outside of specific areas where you have a very well specified problem that you can exactly describe to an agent. On the large scale, these things are still so far from the general ability of a developer it&#x27;s laughable. They are very smart for keeping a ton of context and producing extremely precise solutions, but thinking about software code on a large scale over an extended period of time is something they can&#x27;t do.

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Hacker News 新项目
  • 发布时间：2026/10/1 16:44:15