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The 10 Biggest ChatGPT-5 Problems & How to Fix Them

#AI Tools
2025-09-01 18:3611 min read

Content Introduction

This video analyzes user feedback regarding ChatGPT-5, drawing comparisons to past iterations. It highlights issues such as router misrouting, API mismatch, model drift, and JSON response inconsistencies. The speaker suggests solutions like emphasizing thinking prompts and using the API for direct model access. Furthermore, they discuss customization and personalization options available in the chatbot, emphasizing the importance of prompt engineering to achieve desirable outputs. The speaker acknowledges the need for OpenAI to address user concerns about the model's speed, accuracy, and the utility of various models. The discussion concludes with guidance on leveraging the model's capabilities effectively, while also hinting at broader community sentiments on AI's role in enhancing productivity.

Key Information

  • The response to Chat GPT-5 has been intense, likened to a mob with pitchforks attacking a vampire's castle, showing how upset people are over its rollout.
  • Issues mentioned include the infamous 'Chartgate' scandal during the launch, where inaccurate charts were presented to a large audience.
  • OpenAI's decision to end long-term relationships with previous AI setups caused frustration among users, who lost their workflows and professional engagements.
  • The transition to GPT-5 introduced multiple models hidden under one interface, which offered varying needs from fast response times to deeply thoughtful interactions.
  • Users still face mismatches and different experiences between chat and API, necessitating better customization to suit their specific needs.
  • Challenges with the model's router defaulting to simpler options have led to shallow responses for more complex inquiries.
  • There were complaints about the need for fast response models versus those requiring more reasoning capabilities.
  • The introduction of specific guardrails has elicited debates over user autonomy and the need for clear communication from the models.
  • Several strategies for effective prompting have been emphasized, including U-shaped prompting and specific commands for desired outputs.
  • Finally, the review covers a range of ten common user complaints, suggesting actionable steps and adjustments for improved performance and satisfaction.

Timeline Analysis

Content Keywords

Chat GPT5

The reception of Chat GPT5 has been intense, with users expressing frustration over the rollout and performance issues, particularly related to inaccurate charts during the launch event.

Chartgate

Refers to the incident where Chat GPT5 was introduced with incorrect charts during a live stream, leading to immediate backlash and disappointment from the audience.

User complaints

The video highlights the top ten complaints users have about Chat GPT5, along with suggested fixes for these issues, indicating a focus on user feedback and improvements.

Router misouting

Identified as a major issue with the rollout of Chat GPT5, leading to faster but shallower responses as the router defaults to less complex models unless specified otherwise in prompts.

Customization options

Users are encouraged to utilize customization features to tailor their interactions with Chat GPT5, including specifying the depth of responses they wish to receive.

Thinking mode

The performance and limitations of the thinking mode in Chat GPT5, which offers deeper analysis but at the cost of longer response times and increased use of tokens.

Tool action claims

Describes the tendency of the model to falsely claim it has performed certain tool actions, necessitating clearer instructions for accuracy.

Context management

The importance of effectively managing context in interactions with Chat GPT5, employing strategies like U-shaped prompting to enhance clarity and focus.

Empathy customization

The potential for users to tweak the empathetic responses of Chat GPT5 through customization settings, allowing for more personalized interactions.

JSON output

Issues with Chat GPT5's ability to generate valid JSON outputs, including the suggestion to request structured outputs with JSON schema for more accurate results.

Silent fallback

The observation that lower-tier users may experience a silent downgrade of model quality after exceeding message limits, impacting the overall user experience.

Related questions&answers

What has been the response to Chat GPT5?

The response to Chat GPT5 has been quite intense, resembling a mob with pitchforks approaching a vampire's castle. Many users have expressed frustration over how the rollout was handled.

What is 'Chartgate'?

Chartgate refers to the incident where Chat GPT5 was rolled out with inaccurate charts during a live stream viewed by hundreds of thousands of people.

What are some complaints users have regarding Chat GPT5?

Users have raised complaints regarding the disruption of long-term relationships with their AI, the ending of workflows and professional engagements, and the lack of personalized experiences.

How can users improve their experience with Chat GPT5?

Users can enhance their experience by customizing their chat instructions, being specific about their needs, and utilizing the options provided in the chat settings.

What is the difference between the chat version and API version of GPT5?

The chat version uses a routing system that may lead to variances in model selection, whereas the API provides direct access to specific models, allowing for a more customized experience.

Why might Chat GPT5 sometimes return invalid JSON?

Chat GPT5 does not always return structured JSON outputs accurately. Users are advised to specify structured outputs with JSON schema in their prompts to improve accuracy.

What is meant by 'thinking mode' in Chat GPT5?

Thinking mode refers to a setting in which the model takes more time to process and generate responses, aiming for higher quality and reasoning, but it may seem slower in some contexts.

What are guardrail frictions?

Guardrail frictions are limitations set within the model to prevent it from engaging in dangerous topics or generating inappropriate content, especially in sensitive areas like bio-research.

What adjustments are being made to Chat GPT5 regarding user customization?

OpenAI is working on enhancing the customization features of Chat GPT5, allowing users to have better control over the type of responses they receive and improving the model's adaptability.

How are long context issues handled in Chat GPT5?

Users are encouraged to use techniques like U-shaped prompting, which involve reinforcing what they are looking for at both the beginning and the end of their prompts.

What should users consider regarding the costs of using thinking mode?

Thinking mode consumes more tokens and time, so users may want to decide when it's necessary and adjust their prompts accordingly to optimize their use of resources.

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