Lots of AI usage has been spent inside companies on building new software. Sometimes people are trying to rebuild existing software. I've seen more than a few articles say that Slack is dead (it's changing), or Monday is dead, or some other SaaS isn't going to survive because people can vibe code their own replacement. I know a few people trying to do this, with very mixed success.

I saw this post from Jason Friend of Basecamp, where he noted that most products wouldn't exist if everyone were an entrepreneur. This is because the great products exist precisely because an entrepreneur had a great idea and followed it through. They made mistakes, they learned, and they spent a lot of time getting the product right. The coding was likely a part of this, but the mistakes, the changes of direction, the decisions on what to add or take away, those are time-consuming things not shortcut by AI. The coding isn't the big delay in lots of products. A great response to the post notes this: there are many decisions that go into a product. Many people don't think about all those decisions.

Certainly, some people will use AI and do a great job coding a replacement for some existing product. They'll make their own version of a product, likely learning a lot from existing software. They will shortcut some design and testing time since they know what they want. It's the software they already use, and they know how it works. They don't need to design it.

However, the software is just part of the process, especially in the SaaS world. Infrastructure and operations are big. While a replacement Slack might not need quite the level of hardware, networking, DR, disks, etc., it needs a lot more than an individual can build and manage. An LLM might help you determine where your bottlenecks are and help you build the systems needed to manage more resources, but it's going to take time. Especially if you don't know what sorts of hardware and bottlenecks will occur as more people use your software.

It's also going to make mistakes.

Imagine your LLM gives you a piece of bad code that doesn't perform. We can refactor and fix that. Now imagine your LLM doesn't configure DR correctly. Fixing that is a little harder, especially if you don't realize DR is lacking until an incident occurs.

Software is hard. One thing I've learned over the years in advocating for customers' requests in Flyway, SQL Prompt, or Redgate Monitor is that the coding takes time and effort, but much less than the decisions on what and how to build something. Those eat up time and focus. Once you solve these, AI definitely helps the rest go quicker, especially if you have AI building tests. However, until you solve the problems around coding, it's not necessarily faster or better.