And yes, you need something to start from, but if you ask it to "do something" and loop it to endlessly ("poking"), you will get some interesting outcomes. So yes you need some initial prompt or task, but that can be "do something" and if you keep asking it everytime it finishes to "do something more". I suspect it will not start saying "no" but rather... it will find some stupid meaning and then drift towards what ever goal it guesses you mean.

I'm unsure whether we agree or disagree on the topic.

However, I really doubt its cost effective to do anything like that with these models.

Regardless, working on the wrong things is time wasted. And again, I'm procrastinating here while waiting for Fable to run a benchmark on a few solutions to a problem I have. We can guess what would work, but we only know after the benchmark. A faster model, with fewer capabilities, would've been a much better choice this time... well, "git gud" they said... and live and learn! Faster model = less time for procrastination.

PS. AI models don't live and learn; the discussion about AGI is pretty pointless imo. It's a tool. Does it matter if it is AGI or not if it does what you want it to do? Does the IQ of your colleague matter if he's good at what he's supposed to do? Or bad? Well... I guess it does matter, as many people are up in arms about whether Astro is AGI or not. Personally, I think we're past the point for that debate. These are amazing tools.

Its about the same amount of population who have access to clean water and who have access to internet, and that's maybe about 75% of global population for both. Don't know how they overlap, but probably there is people who have no access to internet but have access to clean water and the other way around.

In absolute terms that is still billions of people. Billions.

Of course this is a bigger problem, as its now harder to distinguish content that is "AI slop" with "content co-authored with AI that is carefully reviewed" with a quick glimpse, and the "AI smell" is quite off-putting. My initial reaction was also negative, but after glimpsing it through and reading the summaries, I found it decent summary, which also... speaks of this thread, of the content of the blog post and everything about the discussion and the strong feelings people have developed around the use of LLMs.

Anyhow, it would be good to disclose the repo with the code for the statistics & use of LLM in the writing right up front. Which model, and why it was used to do the writing, etc. Its enough to say "I think it writes better than I do" or "I was in a hurry, sorry" or what ever, but it really should be disclosed. It reads more honest.

ps. really... that sideways scroll? plz fix it.

This probably is just culturally different understanding of the phrase, because US corporations indeed feel to act greedy, and there is no similar level of protection of the employees.

However, the thing is, in the long term, the business has to make profits to be sustainable. If the company does not make profits, it will die. Its the short term thinking that breaks down companies. You can maximize profits and be ethical at the same time, if the goal is to do it in the long term.

I do understand that the "maximizing profit for the corporation" is a synonym often for short term thinking and vulture capitalism, but for me it meant something else. This is actually quite fascinating now that I think of it, because this phrase means completely different things in different cultural contexts.

So I guess the trigger is that "maximize short term profits over long term sustainability" is the kind of company where I'd never work for.

This project has a "shared" backend for the content management and its completely self built. Because there are many clients who use it to edit things its feasible to pay for the hosting.

For a solo project, id be quite interested if someone would build a native editor that can be just hooked with git, so it would make it possible to run the site serverless. Maybe one already exists. "IDE" for static websites.

When you have complexity, multiple non techincal users who need to update content, and frequent changes, a CMS is currently a very good solution. But thats just a small fraction of websites.

Most of websites are small, 1-2 person companies websites, non-profts, etc., that are basically business cards. Contact details, possibly a contact form, and few pictures. Thats it. There are likely at least hundred milloin websites like that, which are infrequently updated.

Majority of those sites are powered by WP and various site builders, which is far more complicated than what they need. There has not been good option for non-techincal users that makes it possible to make good looking and functional sites.

Also, please keep it civil. This is not Facebook. People can have different opinions.

I know WordPress is going nowehere and if there is some special backend functionality, that is needed. But 95% of web does not need it.

A static site is always cheaper, and the bottleneck has always been that editing code is indimidating. Therefore, AI actually resolves a big problem here, and this is going to alter the future of platforms like WP.

I'm rather certain, though cannot prove it, that buying the same tokens would cost at least 10x more if bought from API. Anecdotally, my cursor team usage was getting to around 700$ / month. After switching to claude code max, I have so far only once hit the 3h limit window on the 100$ sub.

What Im thinking is that Anthropic is making loss with users who use it a lot, but there are a lot of users who pay for max, but don't actually use it.

With the recent improvements and increase of popularity in projects like OpenClaw, the number of users that are generating loss has probably massively increased.

1. She gets better all the time, and might be super popular in the future 2. Many writings became relevant only long after the death of the author

Anyhow, I have made few interesting observations, that might be true for the agents.md also:

Agents have trouble with these large documents, and they seem to miss many relevant nuances. However, its rather easy to point them to the right direction when all relevant information is in one file.

Another thing is that I personally prefer this style of documentation. I can just ctrl+f and find relevant information, rather than using some built in search and trying to read through documents. I feel that the UX of one large .txt file is better than the documentation scattered between multiple pages using some pretty documentation engine.

Im using it regardless. Ive just learnt to deal with these and keep an eye on them. When it creates a duplicate interface I roll back to earlier prompt and be more explicit that this type already exists.

I try to not argue whether something it does is wrong or right. There is not point. I will simply rollback and try with another prompt. Claude is not a human.

I just found OptaPlanner and subsequently TimeFold few months ago, as I was searching for a solution for my wife's veterinary clinics employee scheduling problem. The problem is not big enough for anyone to pay for the solution, but big enough to cause stress for whom ever is dealing with manually doings the shifts.

It was interesting that there were a lot of online SaaS providers that claim to solve the problem but they just simply are not configurable for all kinds of constraints of a real workplace.

Unfortunately I also feel partially same with TimeFold, because designing those constraints really requires changing the way of thinking of many problems. While the engine is capable of doing what ever, there is a steep learning curve to do it.

So while the article mentions documentation, I would say that the documentation is far from sufficient for wide adaption.

Personally, I would have really needed documentation about a mental model of thinking about the problem, and then a ton of examples how to solve real employee scheduling problems. Problem written in a format which the business people use and then translated into an elegant constraint rule explained step by step.

I had to invest more than 40 hours to get a working MVP that solves real problems, not just those that are already coded in the example code. Most people are not willing to do that.

What I'm trying to say is that to making planner software popular, it should be also usable for trivial projects. I understand that it's hard to focus on everything, but just providing more information about real use cases and how they were solved and how to think about the design problems would make the market bigger, and bring you a lot more customers in the long run.

I just wonder how I might contribute to improve the documentation. I probably don't have deep enough understanding of the correct solution, but I will look into it.