I don’t currently use LLMs to code. However, I see value in taking things learned from an LLM coding tool such as Claude Code, and building something that is more useful.

When thinking about using LLMs or some other AI tool to generate code, here are two things I am looking for.

• Output quality can be objectively defined by a numerical value.
• Code output that does not have to be manually reviewed by a person.

With these two criteria in mind, I think the workflow of using LLM tools to write code and then manually reviewing the code is not effective.

First of all, information overload is a major challenge right now. Having to review additional code adds to the overload. LLMs can also generate code at a very fast pace, and reviewing additional code adds to the overload.

Also manually reviewing LLM generated code may not be useful. People including myself do not enjoy doing code reviews. Getting code change requests reviewed was a consistent problem for developers at the past several tech jobs I had. I have also seen open source projects where there were dozens or even hundreds of change requests waiting to be reviewed. Some of them were open for more than a year.

Also, source code quality isn’t an entirely objective measurement. It is true that source code determines of a program runs without bugs. However, source code also has subjective measurements. Different people can format code in different ways because of preferences, and equivalent logic can be implemented in multiple ways.

If an AI tool is being used to write code, I think it is best for someone to look at the user-facing output and not pay attention to the generated code. In this case, an effective AI tool would save time and reduce the amount of information someone has to process. If an LLM is used to generate code, I think vibe coding is better than manual review.