Looks good !!

Hasgeek Ai Community - https://hasgeek.com/generativeAI

what differentiates a normal prompt engineer from super. A few things i can think of - Cross LLM experience - Understanding how to accuracy faster - Expereince with LLM Tools

Anyhting else come to mind ?

I can agree thats going on these days. But important questions is whats the future hold for this.

Agreed, question is what is the timeline for this? 2year or 5 year or much later ?

It is already starting. But most of those predictions may be widely applicable in 2-10 years.

It seems like all of these things will be feasible to some degree within a couple of years. It's hard to predict how long it will take for them to be robust and widely deployed.

What about from LLM App development role prospective ? Similar to a backend or frontend enginnering ?

Followup - How many prompt engineers would be needed in next 2 years of time ?

Sugarcane AI provides an Open Source Microservices Framework for cross-LLM workflow/plugin development, allowing developers to prioritize business logic over LLM selection, cost, and performance.

Framework comprises - LLM as a Service for Data Scientists, empowering data labelling and fine-tuning - Prompt as a Service for Prompt developers, streamlining prompt management - Workflow as a Service for Plugin developers to construct workflow plugins, facilitating the distribution of LLM, Prompts, and Plugins via APIs.

The Open Source framework encourages collaborative dataset development and enhances reusability of prompt packages and fine-tuned LLMs, facilitating sharing and monetization on an open marketplace.

Is there any way to see the trace on a website ?