La preuve qu'OpenAI bride ChatGPT (et la solution secrète)

La preuve qu'OpenAI bride ChatGPT (et la solution secrète)

by Ludo Salenne

Applied Sciences & Engineering AI — Models & Research UYQArtificial intelligence (AI)UYQFGenerative artificial intelligence
🎙 Ludo Salenne 👥 267K 📅 February 25, 2024 ⏱ 27 min 👁 46K 📄 tutorial 🧭 2026-08-21
Available in: English (current) Français

Keywords

ChatGPTOpenAIsystem promptprompt injectiondeveloper modeword limitimage generationcustom instructionsdata analysisAI resources

Summary

The video, presented by Ludo Salenne, claims to prove that OpenAI artificially limits ChatGPT’s performance, particularly in terms of response length and image generation. The creator demonstrates a method to extract ChatGPT’s system prompt, revealing explicit restrictions such as a 60-second execution limit for Python code, a maximum of one image per request, and a 100-word limit for image generation prompts. He then attempts to bypass these limitations using various prompt engineering techniques, including a ‘developer mode’ persona and custom instructions. After several iterations, he claims to have found a prompt that enables generating four images in a single request and producing longer texts, though he acknowledges that the results are not always consistent. The video also warns against misinformation circulating on social media about ChatGPT’s system prompt, showing that some claims are not present in the actual system prompt. The creator shares his findings and provides a link to his resources, including a pastebin with the extracted system prompt. The overall tone is enthusiastic and tutorial-like, aimed at helping users get more out of ChatGPT.

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Critical Evaluation

Value of the Information & Strength of the Argument

The video provides a valuable, hands-on demonstration of how to extract and analyze ChatGPT’s system prompt, which is not officially documented. The creator’s iterative approach to testing and refining prompts is instructive and shows a practical methodology for prompt engineering. However, the argumentation is largely anecdotal, based on personal experiments and a single tweet, without rigorous scientific validation. The claim of ‘hacking’ is somewhat overstated, as the methods used are essentially prompt injection and role-playing, which are known techniques. The video does not provide a controlled comparison or statistical evidence to support the effectiveness of the proposed solution, and the creator himself notes that results are not always reproducible.

Scientific Rigor, Source Quality, Title Accuracy

The video cites a tweet by Dylan Patel and a pastebin link as sources for the system prompt, but these are not official OpenAI documents. The creator does not verify the authenticity of the system prompt beyond his own tests. The title is somewhat clickbait, but the content does deliver on the promise of showing limitations and a workaround. The video also includes a promotional segment for the creator’s own training course, which is clearly marked. The overall scientific rigor is moderate: the creator is transparent about his methods and limitations, but the evidence is not peer-reviewed or independently verified.

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Title / Content Match

The title is somewhat sensationalist but accurately reflects the content: the video provides evidence of ChatGPT's limitations and a prompt-based workaround.

Quality & Reliability

6/10

The video demonstrates a practical method to extract and analyze ChatGPT's system prompt, but relies on anecdotal evidence and a single tweet as source. The claims about 'hacking' are based on user experiments, not official documentation, and the reproducibility is not guaranteed.

Chapters

Cited Sources

Concurring Sources

  • OpenAI's official documentation on ChatGPT — While not directly cited, this documentation provides context on how ChatGPT works, which aligns with the video's observations about system prompts and limitations.

Dissenting Sources

  • Tweet by Dylan Patel — The video argues that this tweet contains false information about ChatGPT's system prompt, specifically regarding word limits, which the creator claims are not present in the actual system prompt.

External References

Contribution & Novelties

The video offers a practical, step-by-step method to extract and analyze ChatGPT’s system prompt, which is not officially documented. It also provides a prompt-based workaround to bypass certain limitations, such as generating multiple images in one request. While the ‘hack’ is not a true security exploit, it demonstrates the power of prompt engineering. The video also serves as a cautionary tale about misinformation on social media regarding AI capabilities.

Pour aller plus loin :

  • Prompt injection — This concept is central to the video’s method of extracting the system prompt.
  • Custom instructions in ChatGPT — The video explores using custom instructions to influence behavior.
  • System prompt — Understanding system prompts is key to the video’s approach.

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Radar Profile

The radar profile shows a balanced but moderate performance across all dimensions. The video scores highest on 'quantite_information' and 'niveau_technique', reflecting the detailed tutorial and technical depth. However, 'fiabilite_globale' is lower due to the anecdotal nature of the evidence and lack of official sources. The overall profile suggests a useful but not highly rigorous content.

Reliability 5/10

💬 Très positif. Sur les 30 commentaires analysés, la grande majorité exprime une forte appréciation, remerciant le créateur pour la démonstration et la solution, avec des éloges sur la qualité pédagogique et l'utilité pratique.