The rise of generative AI has changed how many approach writing, design and coding. A simple prompt can now generate articles, images and code in a matter of seconds. However, a solid foundation or understanding of each of these crafts remains significantly important.
While being able to prompt Generative AI correctly and efficiently is a good skill, it shouldn’t be the only thing one is good at. Actual mastery of skills is just as important and should go hand-in-hand with expertise in prompting. Read on to find out why.
Actual mastery of skills should go hand-in-hand with generative AI
Why is mastery important?
In writing, a strong foundation helps users spot shallow arguments and unclear ideas. In coding, mastery aids in checking tech specs, debugging errors, and ensuring security. In design, you can only finetune a generated image and effectively remove any extra hands or fingers if you actually know how to edit and manipulate images.
These days, many users rely on AI tools without fully understanding the basics and therefore lack the mastery necessary to do the actions mentioned above. This practice may lead to content that lacks depth, images that look good at first glance but may have an extra tower or two (or worse, a flag that's missing some details) and code that doesn't actually do anything relevant.
A lack of mastery also means users might not catch subtle mistakes or biases in the AI's work. Over time, this could erode trust in both the tools as well as those who rely too much on said tools (making it harder for the rest of us who do use AI tools ethically). Mastery and prompting skills must therefore work together to ensure that AI outputs are not only generated quickly but are also refined and validated for quality.
mewtru chimes in about her misadventures with "vibe coders"
The Power (and Responsibility) is… Yours?
While most of the responsibility for maintaining a good foundation in skills and generative AI prompting together falls to educators, those who are just catching up and upskilling on their own should realize that the responsibility to ethically and effectively use generative AI is also theirs. Employers looking for that next genAI 'genius' should also look beyond just the AI qualifications and focus on their mastery of the foundations or basics as well.
If not, we may all end up with a lost generation of prompters who can’t explain why their generative AI did what it did or how to improve it on their own. While this might be a somewhat preachy exaggerated response, if we continue down this path we may just end up with plenty of master prompters but no one to come up with the next generation of prompting tools, eventually leading to an overall decline in progress.
This is a prompt that I often use to test for hallucinations in Gen AI. If you're a real master TechNaver, can you spot the tech spec hallucination? (hint: the answer is at the bottom)
On the other hand, this would not be an issue as long as there's at least one person with mastery who is in a position to validate and double check the results of all the other users. However, the road to mastery often takes years of experience and not everyone can commit to this.
In that sort of situation, it would be crucial for management and people in power to make sure that there is actually a master on hand doing the double checking or that double checking is an essential part of using Generative AI results. We always assume that there could be a hallucination when using Generative AI ourselves, but we understand that people can get complacent.
What do you think? Do you agree that a strong foundation and mastery of skills are essential for anything involving generative AI? Share your thoughts in the comments below and stay tuned to TechNave.com for more introspection into the latest tech trends.
Quite obviously, the Samsung Galaxy Tab A9+ should not be in this list at all as it has an 11-inch display. If you didn't know your tech specs and tablets, you might not be able to spot this.
Of course, you can always do a fact check and the AI will usually pick up on this. But, if you don't have this culture of double-checking Generative AI results, this mistake might just slip through the cracks... especially if you get complacent.
COMMENTS