When a major AI release like GPT-5 arrives, the excitement is enormous, but so are the initial problems; bugs, strange behaviors, and critical limitations appear and are detected on Reddit, X, Discord, and developer forums, and they often get lost in the noise.
At Scalevise, we have created a public tracker to centralize these reports: https://scalevise.com/resources/gpt-5-bugs-issues-tracker/ This live feed collects critical and newly discovered GPT-5 issues and updates almost in real time.
How it works: we continuously monitor developer threads on Reddit, user reports on X, official OpenAI forums, Discord communities, and technical posts and Q&A boards. We only include critical failures or new issues to avoid noise from minor complaints. Each entry shows the report's date and time, a concise description, links to sources when available, and a button to quickly share on X.
Share on X with one click: each entry lets you open a pre-filled tweet with the bug title, the tracker link, the hashtags #gpt5 #gpt5bug #scalevise, and the mention @scalevise to follow the conversation. This alerts the community and helps measure which issues attract the most attention.
Why it matters: the GPT-5 rollout continues to evolve, and although official channels fix some problems quickly, many bugs go unnoticed for weeks until enough developers report them. A central, public, and easy-to-share tracker speeds up the visibility of urgent issues, helps teams avoid wasted time, and gives OpenAI a clearer view of real problems in production.
We want to improve this resource with your help. If you have ideas about new sources to monitor, ways to automate bug verification, sharing formats for LinkedIn or Reddit, or a scoring system to prioritize severity, share them. You can leave a comment on Dev.to, reply on X, or contact us directly at https://scalevise.com/contact
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Visit the Scalevise tracker to follow GPT-5 bugs and share what you consider critical: https://scalevise.com/resources/gpt-5-bugs-issues-tracker/ Together we can detect problems faster and improve AI reliability in production.
