I think exactly like that whenever I hear people, perhaps students, freshers and those not into ML, taking Prompt Engineering so seriously as a career by just looking at the marketing gimmicks.
As you rightly mentioned, Prompt Engineering should be present in our arsenal as a tool, not as an arsenal per se.
In short, Prompt Engineering alone can be a Job, not a Career.
There is a new trend on the market called no code ai engineers. I hope people don’t fall for this one as it would be a painful realization for folks in long term.
True. This trend contradicts my observations. Real enterprise Gen AI projects require more software development and DevOps skills than traditional ML projects. However, such fads promote it otherwise with "no-code AI Engineers".
Reminds of days when folks got into devops without building the foundations on Linux, Networking, Troubleshooting and Systems Engineering in general. Leading to so many folks who start scrambling as soon as their Kubernetes pod crashes not knowing what to do next.
I am going to share this with my community of devops folks interested in learning MLOps and I believe it would help them build the right foundations.
ML is going the same way. I would interview so many folks who would talk about deep learning, neural networks, etc. but would not know how Linear regression works, forget about explaining backpropagation.
Being a devops guy all my life, these names (Linear Regression, Back propogation) are flying above my head . But I get the point :) You are doing great work @Rahul. I like your writing. I want to understand world of ML and now LLM and then AI Engineering :) in order to bring devops principles and technologies to operationalize stuff. I am learning a lot from your articles. Cheers !
I think exactly like that whenever I hear people, perhaps students, freshers and those not into ML, taking Prompt Engineering so seriously as a career by just looking at the marketing gimmicks.
As you rightly mentioned, Prompt Engineering should be present in our arsenal as a tool, not as an arsenal per se.
In short, Prompt Engineering alone can be a Job, not a Career.
There is a new trend on the market called no code ai engineers. I hope people don’t fall for this one as it would be a painful realization for folks in long term.
True. This trend contradicts my observations. Real enterprise Gen AI projects require more software development and DevOps skills than traditional ML projects. However, such fads promote it otherwise with "no-code AI Engineers".
Reminds of days when folks got into devops without building the foundations on Linux, Networking, Troubleshooting and Systems Engineering in general. Leading to so many folks who start scrambling as soon as their Kubernetes pod crashes not knowing what to do next.
I am going to share this with my community of devops folks interested in learning MLOps and I believe it would help them build the right foundations.
ML is going the same way. I would interview so many folks who would talk about deep learning, neural networks, etc. but would not know how Linear regression works, forget about explaining backpropagation.
Being a devops guy all my life, these names (Linear Regression, Back propogation) are flying above my head . But I get the point :) You are doing great work @Rahul. I like your writing. I want to understand world of ML and now LLM and then AI Engineering :) in order to bring devops principles and technologies to operationalize stuff. I am learning a lot from your articles. Cheers !
Thanks Gourav. Keep reading