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· 10 min read

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Large Language Models have shown the world its incredible versatility. One of its most remarkable powers is to turn fuzzy human language into executable code. This not only helps engineers improve their productivity but also enables non-technical people to achieve what used to require help from developers.

Generating analytical data queries is one of the most popular use cases of LLM-based code generation. What can be cooler for business analysts than to ask a question in plain human language and get a visualization in seconds? Traditionally, only big boys like PowerBI and Google Sheets could offer features like that, but now LLM has democratized AI capabilities and lowered the bar. In this post, I'll demonstrate a simple implementation and will also cover an important but often overlooked topic: access control.

· 6 min read

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I initially tried GitHub Copilot, just briefly, around the beginning of 2022. It raised my attention partly due to its name - I hold a private pilot license and have always been an aviation enthusiast. At that time, I found the idea intriguing, but the product usability was not so satisfactory: both in terms of speed and quality of generation. I started to reuse it about three months ago, and now it has become indispensable to me and worth every penny of that $10/mon that I pay.

What makes me a happy customer? Let's figure it out.