6 posts tagged with "ai"

Few developers like writing document​

If you have ever worked as a developer in a large company, you know that coding is just one small part of the daily responsibilities. One of Google's full-stack software engineers, Ray Farias, once estimated that developers write about 100-150 lines of code per day at Google. While this estimate may vary across different teams, the order of magnitude matches my observations as a developer at Microsoft.

"Programming is dead."

A friend said so when he heard I was working on dev tools. It was right after LLM’s coding abilities shocked the world. He felt it pointless to continue building tools for human programmers anymore when AI is taking over this profession. You'll never be wrong by predicting without attaching a time frame. Dead when? At least for the time being, the emergence of generative AI has introduced more work for programmers, some more difficult than before.

Whether AI will replace human developers is too big a topic to tackle. However, we can keep an open mind and explore different roles that AI can play in software development. Let's conduct thought experiments to imagine what each means to us.

SQL databases have been powering the web since their inception. The combination of strict schema, ACID transactions, and strong integrity makes it still the best storage choice for many apps even today. Database systems, albeit sounding unfathomable and dull, have been a highly vibrant domain in the past few years. Lots of talents are devoted to it, open source projects are created one after another, companies have been striving to build profitable businesses, and VCs have been making bets on those who look like the next unicorns.

Under the flourishing surface, the new generation of modern SQL databases is renovating this 50-year-old technology and gradually reshaping how we build web applications - what we do with it, how we manage it, and the way we program against it. This series of articles tries to explore this topic from multiple fronts, including:

• #1 Serverless & Edge
• #2 New Ways to Program
• #3 Better Developer Experience
• #4 Into The AI Era (this post)

Now we've come to the last part of this series. Let's get hold of the hottest trend of the year - AI, and see how modern databases enable easier development of AI-powered applications.

Don't Reinvent the Wheel​

As software developers, we are all familiar with the phrase "Don't reinvent the wheel". However, I have heard many complaints that the Javascript world seems to do the exact opposite. 😂

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.

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.