Summary of "Comment utiliser ChatGPT mieux que 99% des gens"

Summary of Comment utiliser ChatGPT mieux que 99% des gens

This video explains a powerful method to dramatically improve the results you get from ChatGPT and other AI models by focusing on context engineering rather than just prompt writing. The speaker emphasizes that most people mistakenly believe that crafting the perfect prompt is the key to success, but in reality, providing rich, detailed context to the AI yields far superior outputs.

Main Ideas and Concepts

Disillusionment with AI quality: Initially, the speaker tried various AI models (Claude, Gemini) to write scripts faster but found the quality lacking.
Prompt engineering is overrated: Many tutorials focus excessively on how to write prompts, but this is mostly beginner-level advice and insufficient for high-quality results.
Context engineering is the key: Instead of focusing on the prompt alone, the focus should be on providing comprehensive background information (context) to the AI.
Analogy with onboarding a new employee: Just as a new employee needs detailed onboarding (company goals, audience, past successes and failures, competitor analysis, examples of good and bad work) to perform well, AI needs a similar level of context to produce high-quality output.
Providing rich context improves AI output quality by 5 to 10 times: Sharing product pages, customer reviews, target customer personas, past successful and unsuccessful examples, etc., allows the AI to generate much better results.
Context engineering works across many use cases: From creating ads, social media scripts, YouTube intros, emails, essays, to sales pages, the principle remains the same—give AI detailed, relevant information.
Three approaches to context engineering:
1. Deep research by AI: Ask ChatGPT to gather relevant information from the internet to build context.
2. Providing your own documents/data: Supply AI with transcripts, competitor analysis, customer avatars, past successful examples, etc.
3. Normal prompt without extra context: Quick but less effective.
Use cases for context engineering:
- Writing YouTube intros optimized for watch time and engagement.
- Creating viral TikTok scripts.
- Writing marketing ads that generate significantly higher ROI.
- Producing high-quality essays or emails by providing relevant context about the audience or evaluator.

Step-by-Step Methodology for Context Engineering

Identify the task: e.g., write a YouTube script, ad, email, essay.
Gather relevant context:
- Past successful examples (scripts, ads, emails, essays).
- Audience or customer personas (age, fears, desires, goals).
- Competitor examples and market research.
- Product details, customer reviews, and other supporting documents.
If you don’t have these documents, ask ChatGPT to perform a deep search to generate them.
Feed all this context to ChatGPT as part of the input before asking for the final output.
Request the AI to produce the content using this rich context.
Review and provide feedback if necessary, similar to onboarding a new employee.

How to Monetize Context Engineering

The speaker outlines three ways to make money using this technique:

Offer services to businesses:
- Write scripts, posts, ads, sales pages using context engineering for entrepreneurs and companies.
- Provide AI automation workflows that generate content automatically.
- Teach others how to use context engineering effectively.
Start your own AI-powered business:
- Use AI with context engineering in e-commerce, agencies, coaching, real estate investing, etc.
- Outperform competitors by making better decisions and producing higher quality content faster.
Boost your own job performance:
- Complete tasks faster or with better quality.
- Impress bosses and colleagues, earn promotions.
- Run a side business alongside your job.

Additional Notes

Context engineering requires more initial effort (minutes to gather and input context) but yields exponentially better results.
It’s especially valuable for high-stakes or high-value tasks.
The speaker references having worked with top YouTubers and having 8 years of marketing experience to validate the method.
The video includes before-and-after examples showing the dramatic difference in AI output quality when using context engineering.

Speakers and Sources Featured

Main Speaker: Unnamed French-speaking AI and marketing expert sharing personal experience and methodology.
References to AI models: ChatGPT, Claude, Gemini.
Mentions working with YouTubers such as MrBeast and Yomy Denzel (as examples of expertise).

This video serves as a practical guide and mindset shift for anyone wanting to leverage AI more effectively by focusing on context, not just prompt phrasing.