I'm a marketer. I write a lot. GPT-4.5 is really good at natural sounding writing. It's nearing the point where it would be worth $200/mth for me to have access to it all the time.
I used the GPT-4.5 API to write a novel, with a reasonably simple loop-based workflow. The novel was good enough that my son read the whole thing. And he has no issue quitting a book part way through if it becomes boring.
It's a comedic adventure novel set in the Minecraft universe.
Actually I forgot there's a second one he read all the way through, for which he defined the initial concept and early plot, but then the rest of the plot and the writing were all done by GPT-4.5.
The code is kind of basic, and each chapter is written without the full text of prior chapters, but the output isn't bad.
Very fascinating, I tried doing the same years ago with a simple Markov chain model. The biggest problem back then was inconsistency. I'd love to read a chapter of the Minecraft or hard magic / sci-fi books to check out the writing.
Not having access to earlier chapters is a terrible thing, but maybe possible if you aren’t too bothered by inconsistency (or your chapter summaries are explicit enough about what is supposed to happen I suppose).
I find the quality rapidly degrades as soon as I run out of context to fit the whole text of the novel. Even summarizing the chapters doesn’t work well.
Yeah this is true. I could have sent the entire book up until that point as context. But doing that 100 times (once per chapter) would have meant sending roughly 50x the length of the book as input tokens (going from 0% to 100% as the book progressed).
This would be fine for a cheap model, but GPT 4.5 was not cheap!
I would have liked to have fewer, longer chapters, but my (few) experiments at getting it to output more tokens didn't have much impact.
Yeah, that’s what I eventually ended up doing. Quality and cost both went through the roof. To be fair, Claude is good about caching, and with a bunch of smart breakpoints, you pay only 10% for most generations.
Well, an even better question might be: if everyone is the same, what does it take to be exceptional?
I'm firmly convinced that being able to troubleshoot code, even code generated by LLMs, and to write guidelines and tests to make sure it's functioning, is a skill of a shrinking pool
For smaller stuff, great. Everyone's the same. The second your application starts gaining responsibility and complexity, you're going to need to be able to demonstrate reproducibility and reliability of your application to stakeholders.
Like, your job increasingly will be creating interface checkpoints in the code, and then having the model generate each step of the pipeline. That's great, but you have understand and validate what it wrote, AND have a rich set of very comprehensive tests to be able to iterate quickly.
And as mentioned, on top of that, large swaths of the field of new people have their brains completely rotted by these tools. (certainly not all new/young people, but i've seen some real rough shit)
If anything, I see a weird gap opening up
- people who dont adopt these tools start falling out of the industry - they're too slow
- people who adopt these tools too early stop getting hired - they're too risky
- people who have experience in industry/troubleshooting/etc, who adopt these tools, become modern day cobol programmers - they're charging $700 an hour
the real question to me is this: does the amount of people taken out of the pool by being slow or risky due to these tools, outpace the reduction in jobs caused by these tools?
> I'm firmly convinced that being able to troubleshoot code, even code generated by LLMs, and to write guidelines and tests to make sure it's functioning, is a skill of a shrinking pool
I’m not sure the point you’re trying to make but I’ve had so many junior level interviewees and interactions where they are unable to do anything without an LLM coaching them the whole way. This is dangerous!
It’s like if I was hiring a mathematician. I’d expect them to use a calculator or CAS package but I’d also expect them to be able to do everything by hand. I wouldn’t ever waste their time by making them do that, of course.
I was trying to say that dropping old technologies isn't always bad.
> It’s like if I was hiring a mathematician.
Do you expect candidate to memorize all theorems up to date. Usually people forgetting things they don't actively use. But they are able to refresh their knowledge if needed. I've learned quite a lot, but no, I don't remember even key theorems from partial differential equations (used them in my diploma). I can refresh and relearn quickly, I'm sure.
Using LLM without understanding disqualifies the candidate, even monkey can do it. But if he deeply understands the subject and uses LLM for like handbook for minor details.. that's different.