One post tagged with "ChatGPT" - Cuckoo AI Network

### Common Pain Points and Limitations **Limited context memory:**A top complaint is ChatGPT’s inability to handle long conversations or large documents without forgetting earlier details. Users frequently hit the context length limit (a few thousand tokens) and must truncate or summarize information. One user noted *“increasing the size of the context window would be far and away the biggest improvement… That’s the limit I run up against the most”*. When the context is exceeded, ChatGPT forgets initial instructions or content, leading to frustrating drops in quality mid-session. … **Hallucinations and errors:**Despite its advanced capability, ChatGPT can produce incorrect or fabricated information with confidence. Some users have observed this getting worse over time, suspecting the model was “dumbed down.” For instance, a user in finance said ChatGPT used to calculate metrics like NPV or IRR correctly, but after updates *“I am getting so many wrong answers… it still produces wrong answers [even after correction]. I really believe it has become a lot dumber since the changes.”*. Such unpredictable inaccuracies erode trust for tasks requiring factual precision. **Incomplete code outputs:**Developers often use ChatGPT for coding help, but they report that it sometimes omits parts of the solution or truncates long code. One user shared that ChatGPT now *“omits code, produces unhelpful code, and just sucks at the thing I need it to do… It often omits so much code I don’t even know how to integrate its solution.”*This forces users to ask follow-up prompts to coax out the rest, or to manually stitch together answers – a tedious process. … Devs often notice even subtle changes in quality after model updates and have been very vocal on Reddit about perceived “nerfs” or declines in coding capability. They also push the limits (building complex prompts, chaining tools), so they crave features like expanded context, fewer message caps, and better integration with coding tools. In summary, developers value ChatGPT for speeding up routine tasks but are quick to point out errors in logic or code – they view it as a junior assistant that still needs oversight.