The Recurring Cycle of ‘Developer Replacement’ Hype

How to Make Websites That Will Require Lots of Your Time and Energy - Jim Nielsen’s Blog

1. Install Stuff Indiscriminately From npm
2. Pick a Framework Before You Know You Need One
3. Always, Always Require a Compilation Step

What we talk about when we talk about AI — Careful Industries

Technically, AI is a field of computer science that uses advanced methods of computing.

Socially, AI is a set of extractive tools used to concentrate power and wealth.

Build It Yourself | Armin Ronacher’s Thoughts and Writings

We’re at a point in the most ecosystems where pulling in libraries is not just the default action, it’s seen positively: “Look how modular and composable my code is!” Actually, it might just be a symptom of never wanting to type out more than a few lines.

It always amazes me when people don’t view dependencies as liabilities. To me it feels like the coding equivalent of going to a loan shark. You are asking for technical debt.

There are entire companies who are making a living of supplying you with the tools needed to deal with your dependency mess. In the name of security, we’re pushed to having dependencies and keeping them up to date, despite most of those dependencies being the primary source of security problems.

But there is a simpler path. You write code yourself. Sure, it’s more work up front, but once it’s written, it’s done.

The Gist: AI, a talking dog for the 21st Century.

My main problem with AI is not that that it creates ugly, immoral, boring slop (which it does). Nor even that it disenfranchises artists and impoverishes workers, (though it does that too).

No, my main problem with AI is that its current pitch to the public is suffused with so much unsubstantiated bullshit, that I cannot banish from my thoughts the sight of a well-dressed man peddling a miraculous talking dog.

Also, trust:

They’ve also managed to muddy the waters of online information gathering to the point that that even if we scrubbed every trace of those hallucinations from the internet – a likely impossible task - the resulting lack of trust could never quite be purged. Imagine, if you will, the release of a car which was not only dangerous and unusable in and of itself, but which made people think twice before ever entering any car again, by any manufacturer, so long as they lived. How certain were you, five years ago, that an odd ingredient in an online recipe was merely an idiosyncratic choice by a quirky, or incompetent, chef, rather than a fatal addition by a robot? How certain are you now?

What I’ve learned about writing AI apps so far | Seldo.com

LLMs are good at transforming text into less text

Laurie is really onto something with this:

This is the biggest and most fundamental thing about LLMs, and a great rule of thumb for what’s going to be an effective LLM application. Is what you’re doing taking a large amount of text and asking the LLM to convert it into a smaller amount of text? Then it’s probably going to be great at it. If you’re asking it to convert into a roughly equal amount of text it will be so-so. If you’re asking it to create more text than you gave it, forget about it.

Depending how much of the hype around AI you’ve taken on board, the idea that they “take text and turn it into less text” might seem gigantic back-pedal away from previous claims of what AI can do. But taking text and turning it into less text is still an enormous field of endeavour, and a huge market. It’s still very exciting, all the more exciting because it’s got clear boundaries and isn’t hype-driven over-reaching, or dependent on LLMs overnight becoming way better than they currently are.