![[The AI Show Episode 142]: ChatGPT’s New Image Generator, Studio Ghibli Craze and Backlash, Gemini 2.5, OpenAI Academy, 4o Updates, Vibe Marketing & xAI Acquires X](https://www.marketingaiinstitute.com/hubfs/ep%20142%20cover.png)
![[FREE EBOOKS] The Kubernetes Bible, The Ultimate Linux Shell Scripting Guide & Four More Best Selling Titles](https://www.javacodegeeks.com/wp-content/uploads/2012/12/jcg-logo.jpg){kind=logo}
![From drop-out to software architect with Jason Lengstorf [Podcast #167]](https://cdn.hashnode.com/res/hashnode/image/upload/v1743796461357/f3d19cd7-e6f5-4d7c-8bfc-eb974bc8da68.png?#)
![When is multiple validation layers of protection necessary? [duplicate]](https://cdn.sstatic.net/Sites/softwareengineering/Img/apple-touch-icon@2.png?v=1ef7363febba)
.png?#)
.jpg?#)
_Christophe_Coat_Alamy.jpg?#)
![Rapidus in Talks With Apple as It Accelerates Toward 2nm Chip Production [Report]](https://www.iclarified.com/images/news/96937/96937/96937-640.jpg)
Prompt Engineering For AI Model
Prompt engineering in 2025 has evolved significantly, with each AI model—OpenAI’s ChatGPT, DeepSeek, Google Gemini, and GitHub Copilot—having distinct strengths and weaknesses. To develop expertise in prompt engineering across these models, it’s essential to understand their underlying architectures, capabilities, and ideal prompting techniques.
Prompt engineering in 2025 has evolved significantly, with each AI model—OpenAI’s ChatGPT, DeepSeek, Google Gemini, and GitHub Copilot—having distinct strengths and weaknesses. To develop expertise in prompt engineering across these models, it’s essential to understand their underlying architectures, capabilities, and ideal prompting techniques.
