Tony and I talk about some great current guidance about focusing on mastering our domains with AI, rather than being AI generalists. For both of us, our domain of expertise is cybersecurity, so we cover some ways we're using AI tools to make us better in our cyber tasks and projects.
This was inspired by an item in The Neuron newsletter that had these really interesting new thoughts on how we should not strive to be AI generalists. Some of its key points:
**Here’s the key points:**
- The performance gap between good and bad AI users is growing with each new model.
- Basic prompting gets basic results, even from advanced models.
- But expert prompting can squeeze 2-10x more value from the same AI.
- Your ability to ask good questions will soon matter more than the model you use.
**Now** **here's the key insight:** Ethan Mollick [argues](https://www.oneusefulthing.org/p/the-end-of-search-the-beginning-of?utm_source=www.theneurondaily.com&utm_medium=referral&utm_campaign=why-ai-skill-matters-more-than-ai-model) that while everyone's waiting for artificial general intelligence (AI as smart as humans in all domains), narrow AI is quietly revolutionizing specific fields.
For professionals, this means the opportunity isn't in becoming an “AI generalist”—**it's in mastering how AI can enhance your specific domain expertise.** The most successful AI users aren't trying to automate everything; they're becoming dramatically better at specific, high-value tasks.
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