paol_taja

I use both, many times at the same time, on different projects.

One day one feels better than the other. Then, by the end of the day, the other feels better than the first. I have no idea why.

I still don’t have a favorite.

In the end, I think both are incredibly useful when I take the time to instruct them properly.

The problems come when I let them run wild.

I think two things can be true at the same time.

I believe Matt is right about the core issue in this fight. WordPress cannot become a place where large companies extract massive value from the ecosystem while ignoring the responsibilities that come with that position.

But I also think the way the fight has been handled created unnecessary damage and fear in the ecosystem.

The software is still incredibly resilient.

But trust in the project is more fragile than ever. I hope the people involved find a way to lower the temperature, because the plugin and theme ecosystem depends on it.

Why does it show the asteroid belt and not the Kuiper belt?

I hope my comment is on topic. If not, apologies. But I think I have some skin in the game here.

I could be the perfect example of someone overreaching. My coding skills are limited, but I’m also not stupid, and I don’t release anything I build without having it reviewed by an expert.

That said, IMHO, humans were already very good at producing garbage before AI.

I think the real distinction is not expert vs non-expert. It is whether the person using the tool has enough judgment and feedback loops to catch bad output.

In my field, AI lets me do much more than I could before. It also lets me explore areas I would normally not touch alone. But I still have my business partner, who is the stronger engineer, check everything I do before releasing anything.

That review step is very important. Without it, I would probably sometimes ship polished garbage.

I’m also not sure quality is as objective as people like to pretend it is. Some things can be tested. But even there, testing only reduces risk. It does not make software perfect. Vulnerabilities are often found years later, in code written and reviewed by experts, and running in production.

So maybe the danger is not AI. The danger is removing the review systems and pretending the output is expert-level just because it seems to be working correctly.

Nothing, absolutely nothing. But faster, with more confidence, and a subscription fee.

The fun part of AI coding agents is that they combine the confidence of a junior dev, the permissions of a senior dev, and the caution of a shell script from Stack Overflow. What could go wrong?

Finally! Startup equity was too simple... Now we can have founders trade part of their company for tokens in another company, whose valuation depends on everyone believing the tokens will someday be worth money. Finance is healing!

The funniest possible outcome is OpenAI going public and then having to explain to shareholders that the path to AGI requires losing more money than previously expected, but with greater confidence.

Finally, a way to lose money on AI startups without all the annoying friction of being an accredited investor.

Silicon Valley really does keep democratizing access to things.

Very reassuring. When billionaires tell retail investors not to worry about a bubble, history suggests everything is usually fine.

Especially when the bubble is mostly funded by other billionaires buying GPUs from each other and calling it productivity.

You guys made the classic SEO mistake of building a real community site instead of a Reddit thread, a coupon subfolder, or an AI summary.

Scherzi a parte, spero che possiate recuperare presto…

That pelican looks like it just sold a SaaS company and bought a bike because its therapist said it needed balance.

The "too dangerous to release" line was definitely a marketing stunt.

OpenAI already used the same playbook with GPT-2 in 2019, and some of the same people involved back then are now doing it again at Anthropic with Mythos.

Same safety-branding DNA, different company, and people are falling for it again.

I definitely double guess everything I do without it. The doubt creeps in fastest on the stuff I used to do without thinking.

I would write that like this: The "we've been telling ourselves we're getting better at prompting" line hit. I run a small team of 10, and Claude has been part of our workflow for months. Looking back, my prompts did not change nearly as much as the way I work changed. The shaping goes both ways, and I don't think the labs' evals are really built to see that.

I like the idea, but I always struggle with the practical side of this.

As a business owner, I don't really care where the company is based on paper if the product is worse, the support is worse, or the ecosystem around it is tiny.

I want better European alternatives, but they need to win on product too.

"Not American" is a decent reason to try something. It is not enough of a reason to keep using it for years.

I think this is mostly right, if we only mean "writing code." AI makes it much easier to write code in languages I would not have touched before. But the hard part is still deciding what should exist, what should not exist, which edge cases matter, how users will misunderstand the UI, and what mess you are leaving for future maintenance. So yes, AI weakens Python's "easy to write" advantage. But boring ecosystems, docs, deployment, debugging, and libraries still matter a lot. Even PHP still matter a lot to me...

If your app could track things like anxiety and worries, help you find the root cause, or train you not to let them wake you up at 3 a.m., I would pay as much as I could afford for it. :-(

Sleep is my biggest concern right now.