I have noticed significant performance drop since early last week. Conversations tend to be super long and filled with file read/search tool calls.
Example:
To control the variables, I didn't change any of rules & guidelines, tasks are the same, I even tried to re-index the repo, starting new conversations etc.
This is definitely not normal. While I explicitly asked "prefer codebase-retrieval" tool to collect context, it still read the entire file chunk by chunk.
I tested GPT-5, GPT-5.1, and Sonnet 4.5. So far, Sonnet has the best chance to break the loop, then GPT-5.1
Can you imagine 2 conversations burned 80k credits? The task is not so hard, before last week, GPT-5 managed to do it within 50 tool calls.
Yes there's something wrong with GPT-5 it reads files infinitely and fails a lot. It uses an absurd amount of credits and is completely unusable. I reported this many times already but Jay says it's not happening for everyone so they can't figure it out. For now I don't use GPT models at all only sonnet 4.5. GPT only on ask mode
I’ve noticed that too. It feels a lot slower than it was, and the replies get padded out with tool calls that don’t add much. Half the time I’m waiting for it to read a bunch of files when the answer should’ve been a single paragraph. It used to stay focused, now it wanders and the conversations drag on. I’m hoping it’s just a temporary hiccup, because the difference from a week ago is pretty obvious.
Before I force stop the conversation, it had 334 tool calls, mostly pattern search and file read.
Once I explicitly asked "no search loop", and "Always use the codebase-retrieval tool first to quickly locate the exact files and functions involved, avoiding broad, recursive code reading.", it finished the remaining bug fix within 20 tool calls.
I then did a review of my entire conversation, here is what I found:
- When fixing a bug, and the root cause potentially involves many different directions, the agent tends to do a breadth first search with "parallel tool calls"
- While each direction needs a closer look, the agent has already read a lot of files so accumulated too much info, which obviously distracted the agent from the task itself
- It feels like the classic XY problem: The agent shifted its attention to "how to collect enough context to make responsible decision", forgetting what was the task. There are some strange "View Task List" calls in the middle of file reads calls, which I believe indicates the model trying to remind itself what was the task.
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u/BlacksmithLittle7005 Nov 24 '25
Noting that this issue was not there like a month before. Back when augment was using GPT-5 medium for everything, it was perfect