40+ Things ChatGPT Images Can Actually Do

40+ Things ChatGPT Images Can Actually Do

by Matt Wolfe

Applied Sciences & Engineering AI — Models & Research UYQArtificial intelligence (AI)UYQFGenerative artificial intelligence
🎙 Matt Wolfe 👥 1.0M 📅 April 28, 2026 ⏱ 33 min 👁 90K 📄 tutorial 🧭 2026-08-28
Available in: English (current) Français

Keywords

ChatGPT imagesAI image generationuse casespromptsproductivity

Summary

Matt Wolfe presents a comprehensive overview of practical applications for OpenAI’s ChatGPT image generation model (referred to as ChatGPT Images 2.0). The video is structured as a series of demonstrations, each showcasing a different use case, from creating YouTube thumbnails and storyboards to designing business assets like flyers, menus, and social media carousels. The author emphasizes the model’s ability to generate accurate text, pull information from URLs, and create detailed visual plans such as travel itineraries, chore charts, and infographics. He also highlights its capacity for brand development, including logo exploration and mood boards. Throughout the video, Wolfe provides the exact prompts used, allowing viewers to replicate the results. He notes some limitations, such as occasional aspect ratio errors and inaccuracies in map generation, but overall presents the model as a significant improvement over previous versions. The video concludes by encouraging viewers to experiment with the model and explore its potential for enhancing productivity and creativity.

156 words

Critical Evaluation

Value of the Information & Strength of the Argument

The video’s primary value lies in its extensive, practical demonstration of the ChatGPT image model’s capabilities. The author tests a wide range of prompts, from simple thumbnail concepts to complex infographics, and shows the actual outputs, which provides concrete evidence of the model’s strengths and weaknesses. The argumentation is straightforward and based on personal experience, which lends credibility to the demonstrations. However, the video lacks a critical analysis of the model’s limitations beyond surface-level observations, and the presentation is largely promotional, focusing on what the model can do rather than potential risks or ethical considerations. The author’s enthusiasm is evident, but the argumentation would be stronger with a more balanced perspective.

Scientific Rigor, Source Quality, Title Accuracy

The video is a tutorial and demonstration, not a scientific study. The author relies on his own testing and does not cite external sources for the claims about the model’s capabilities. The only external references are links to his own website and social media profiles. The title accurately reflects the content, which is a list of use cases. The video’s rigor is limited by the lack of independent verification and the potential for bias, as the author is promoting AI tools. However, the demonstrations are clear and reproducible, which adds some credibility. The adéquation between the title and content is good, as the video delivers exactly what the title promises.

236 words

Title / Content Match

The title accurately reflects the content, which showcases numerous practical use cases for ChatGPT's image generation model.

Quality & Reliability

7/10

The video is a practical demonstration of ChatGPT's image generation capabilities, based on the author's direct testing. The information is presented clearly and the author acknowledges limitations (e.g., aspect ratio issues, map inaccuracies). However, the content is promotional in nature and lacks independent verification or critical analysis of the model's broader implications.

Key Moments

Markers derived by PSI from the transcript: the creator did not define chapters.

Cited Sources

  • FutureTools.io — Mentioned as the author's website for exploring AI tools and news.
  • FutureTools Newsletter — Mentioned as a weekly newsletter for AI tools and news.
  • Matt Wolfe on LinkedIn — Author's LinkedIn profile, listed in the video description.
  • Matt Wolfe on Threads — Author's Threads profile, listed in the video description.

Concurring Sources

Dissenting Sources

  • Critique of AI image generation limitations — This article discusses limitations of AI image generators, such as bias and inaccuracies, which the video only briefly touches upon.

External References

Contribution & Novelties

The video provides a comprehensive, hands-on overview of the practical applications of ChatGPT’s image generation model, showcasing over 40 use cases. It goes beyond simple image generation to demonstrate how the model can be used for complex tasks like creating infographics from URLs, designing brand identity, and planning social media calendars. The author’s approach of showing real prompts and outputs adds practical value for viewers looking to replicate these results.

Pour aller plus loin :

  • OpenAI’s ChatGPT page — Official page for ChatGPT, where the image generation feature is available.
  • Nano Banana (Google’s image model) — A reference to another AI image model mentioned in the video, useful for comparison.
  • Prompt engineering guide — A comprehensive resource on crafting effective prompts for AI models, relevant to the video’s emphasis on prompt design.

132 words

Radar Profile

The radar profile shows high scores in information quantity and quality, reflecting the video's extensive demonstrations and clear explanations. The technical level is moderate, as the content is accessible to a general audience. The overall reliability is good, but the promotional nature and lack of critical analysis prevent a higher score.

Reliability 7/10

💬 Très positif. Sur les 30 commentaires analysés, les utilisateurs expriment un fort enthousiasme pour les démonstrations pratiques, certains partageant leurs propres expériences réussies avec les prompts, et d'autres saluant la créativité et l'utilité du contenu.