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@ -11,11 +11,7 @@ Browsing the database of theresanaiforthat.com, we can observe around [7000 new,
It seems it has never been easier to create a startup, build an app, and go to market… and fail. It seems it has never been easier to create a startup, build an app, and go to market… and fail.
Decades of technological advancements have led to small teams being able to do in 2023 what in 2015 required a team of dozens. AI apps currently being pushed out still mostly feel and perform like demos.
Yet, the AI apps currently being pushed out still mostly feel and perform like demos.
The rise of this new profession is perhaps signaling the need for a solution that is not yet there — a solution that in its essence represents a Large Language Model (LLM) — [a powerful general problem solver](https://lilianweng.github.io/posts/2023-06-23-agent/?fbclid=IwAR1p0W-Mg_4WtjOCeE8E6s7pJZlTDCDLmcXqHYVIrEVisz_D_S8LfN6Vv20) — available in the palm of your hand 24/7/365.
To address this issue, [dlthub](https://dlthub.com/) and [prometh.ai](http://prometh.ai/) will collaborate on a productionizing a common use-case, progressing step by step. We will utilize the LLMs, frameworks, and services, refining the code until we attain a clearer understanding of what a modern LLM architecture stack might entail. To address this issue, [dlthub](https://dlthub.com/) and [prometh.ai](http://prometh.ai/) will collaborate on a productionizing a common use-case, progressing step by step. We will utilize the LLMs, frameworks, and services, refining the code until we attain a clearer understanding of what a modern LLM architecture stack might entail.