A series of posts on the decisions and trade-offs involved in being a tech lead:
I think good tech leads spend a lot of their time somewhere in between the two extremes, adjusting the balance as circumstances demand.
Generated code is rather a lot like fast fashion: it looks all right at first glance but it doesn’t hold up over time, and when you look closer it’s full of holes. Just like fast fashion, it’s often ripped off other people’s designs. And it’s a scourge on the environment.
This is depressing.
Frankly, I’d rather quit my career than live in the future they’re selling. It’s the sheer dystopian drabness of it. Mediocrity as a service.
I tried the tab-completion slot machines; not my cup of tea. I tried image generation and was overcome with literal depression. I don’t want a future as a “prompt artist”.
I’m mostly linking this for what it says, but oh boy, do I love the way it says it with this wonderful HTML web compenent.
Want to use all those great features that have been in landing in browsers over the past year or two? View transitions! Scroll-driven animations! So much more!
Well, your coding co-pilot is not going to going to be of any help.
Large language models, especially those on the scale of many of the most accessible, popular hosted options, take humongous datasets and long periods to train. By the time everything has been scraped and a dataset has been built, the set is on some level already obsolete. Then, before a model can reach the hands of consumers, time must be taken to train and evaluate it, and then even more to finally deploy it.
Once it has finally released, it usually remains stagnant in terms of having its knowledge updated. This creates an AI knowledge gap. A period between the present and AI’s training cutoff. This gap creates a time between when a new technology emerges and when AI systems can effectively support user needs regarding its adoption, meaning that models will not be able to service users requesting assistance with new technologies, thus disincentivising their use.
So we get this instead:
I’ve anecdotally noticed that many AI tools have a ‘preference’ for React and Tailwind when asked to tackle a web-based task, or even to create any app involving an interface at all.
Here’s a thoughtful response from Chris to my post about Svelte, Astro, and React.
Two JavaScript frameworks—Svelte and Astro—share a philosophy, but take subtly different approaches.
Just what is it that I do, anyway?