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devilankur18

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Ask HN: How user behaviour have evolved in post ChatGPT world?

1 points·by devilankur18·3 lata temu·0 comments

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1 points·by devilankur18·3 lata temu·0 comments

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1 points·by devilankur18·3 lata temu·0 comments

Top Problems with LLM App Development

2 points·by devilankur18·3 lata temu·3 comments

Ask HN: Prompt Engineering: A Skill or Role? Whats the Future?

8 points·by devilankur18·3 lata temu·11 comments

Show HN: Open-Source Microservices Framework for Cross-LLM Apps

sugarcaneai.dev
10 points·by devilankur18·3 lata temu·2 comments

comments

devilankur18
·2 lata temu·discuss
Looks good !!
devilankur18
·3 lata temu·discuss
Hasgeek Ai Community - https://hasgeek.com/generativeAI
devilankur18
·3 lata temu·discuss
where problem do you think take the most time ?
devilankur18
·3 lata temu·discuss
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 ?
devilankur18
·3 lata temu·discuss
I can agree thats going on these days. But important questions is whats the future hold for this.
devilankur18
·3 lata temu·discuss
Agreed, question is what is the timeline for this? 2year or 5 year or much later ?
devilankur18
·3 lata temu·discuss
What about from LLM App development role prospective ? Similar to a backend or frontend enginnering ?
devilankur18
·3 lata temu·discuss
Followup - How many prompt engineers would be needed in next 2 years of time ?
devilankur18
·3 lata temu·discuss
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.