alt Hacker NewsI hope and believe that some great companies and teams will use LLMs to build higher quality software.
We built Electron because writing UIs using native desktop frameworks is tough. Is it still tough? Surely LLMs make it easier to use and so we will end up with faster and more native feeling applications.
What about having a couple of ideas of what might make a feature feel good? Well now you can make multiple prototypes fast and pick the best one. Your users get the best one.
I hope to build software this way in the future.
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Cross-platform widget engines (Tk, GTK, Qt, wxWidgets, etc…) long predate Electron and have always been robust, stable, well documented, and easy to use. It's not creating a single application for multiple native desktop environments that was difficult, it's writing a single application as both a web interface and a native desktop environment on any platform that's difficult.
Because CSS is constantly changing, inconsistently implemented, and difficult to use, it can't easily be targeted by widget engines (although Qt has tried, and maybe others) and web browsers already exist, so webview environments like Electron are the quickest way to get a cross-platform installable application that can also be hosted on a web server. I wouldn't really call it native though.
It will be a push and pull and I'm curious where we'll be in a couple of years.
I can fly at 100mph if I let AI run loose and with a bit of steering I can get it to output what I'm looking for and generally pass verification and tests.
If I care about the code though, and I want to keep it maintainable, the amount of time and tokens I need to spend correcting and iterating on the output quickly eats through much of the initial time I saved, to the point where I'm unsure if I'm actually saving much time at the end of the process.
With hobby projects I lean on quality more, and the async nature of AI also makes this much easier to make progress without needing my full attention to do so.
In the corporate world, there's both the pressure to accelerate with AI, but also maintain code and product quality. The dials of one way or the other are more obvious now, but I don't believe it's possible to do both with the current models and harnesses without exponential cost.
What is interesting though, is I'm now leaning towards faster models rather than smarter ones.
Intelligence lets me bite off larger chunks of work at once, and trust the model to behave without having to watch it intensely, but doesn't seem to drive down the number of iterations required to hit my desired quality.
Faster models means the iterations I'll have to go through regardless will complete much faster and gets me closer to a proper flow state. Models will keep improving, but maybe we're getting near "smart enough" and the race will pivot to performance > intelligence.
>We built Electron because writing UIs using native desktop frameworks is tough. Is it still tough? Surely LLMs make it easier to use and so we will end up with faster and more native feeling applications.
We built Electron because web devs were a dime a dozen. It was an economic decision, not a technical one.
You would think so. But it seems all that everyone is obsessed with is increasing the velocity of enshitification in the hopes of becoming the next papa Elon
Idk, OpenAI themselves released some weird Electron app to replace their native version of ChatGPT on mac https://www.siliconreport.com/openais-chatgpt-mac-update-shi...