I’ve been using v0 to develop a web app. This is a long session and I’ve arrived at version 143 of my app. At this point the issue arrives.
v0 starts adding some random escape character such as “/” or forgot to close its comment. It constantly edit, review its work, find the same type of error, try to fix, announce that it has finished the job, review the work and found the same error again and again.
It keeps running in this loops continuously for nearly 2 hours and the result keeps getting worse.
To my observation:
It seems to complicate the issue at first by trying to review everything before making edit.
This could result in an overload of information and lead the Agent into the wrong path
This behavior is somehow very consistent with ChatGPT 5 in canvas mode. When making long edit, it suddenly decides to stop generating and is stuck at this point onward.
Hope the engineering team and look into this issue and find a fix. For me the best strategy I can pull out is to revert it back to its previous working version and redo my development.
This is a tricky problem to solve: \n is a single token and LLMs can have a hard time spotting the backslash on its own, especially in longer files. This affects all LLMs at a fundamental level which is why you see it in ChatGPT Canvas as well
One solution to explore is to have the v0 agent use tools to invoke a compiler/linter when hitting these categories of errors
But until we solve it, the best way to reduce the chances of running into it is keeping your chat context small. Breaking large files into small files means the LLM can operate in smaller steps, and duplicating your chat can create a new one with no chat history (although this doesn’t affect v0 as much as it used to)
This is annoying but at the same time an interesting behavior that is common to all AI agents I used. They can be very efficient in doing complex tasks but will fail with simple task such as fixing import.
Exactly the same problem I was facing. To my experience we should stop it as soon as possible once it shows a sign entering dead loop. I don’t know how exactly we are charged but since it’s generating response, it may consume credits.
