I’m currently working on two projects/clients one using Claude, one using Codex. I have a strong preference for the latter, but not because I think it is much more intelligent or writes much better code. It is simply because I find the way of interacting with it more pleasant: more literal, mechanical, makes fewer assumption and or double checks, and is less proactive in my experience. At least until some updates over the last few weeks.

But if AI doesn't lead quickly to vast large scale replacement of workers as promised, I could definitely see the C-suits and their gaggle of consultants starting to ask questions about token pricing.

Obviously, a deterministic tool is preferable in general, but it is not always worth bothering with for a one off task.

Worth noting, a significant chunk of those runs involved the agent waiting for the compiler, linters, type checks, and test suites, as well as updating journals. It’s not the agent sputtering out code for eight hours straight.

And naturally I spend more time on manual verification in the end as much less of it is happening during the coding process.

I wonder if a small part of this is more and more business and product people actually trying to incorporate AI into their daily workflows. I have seen this in both small companies I work for. People were very excited about getting Claude Cowork a couple of months ago, and while they use it daily, I would say they are rather underwhelmed compared to the magic they were expecting. Complaints include the output being mediocre and verbose, it getting the most basic things wrong, hitting token limits all the time, and people going back to doing things themselves because it is faster.

Sure, there is some degree of holding it wrong in the beginning, but people are realizing that maybe, just maybe, there is still somewhat of a gap between what AI CEOs, LinkedIn grifters, and YouTube AI supplement peddlers claim and reality.

Not advocating punching the police as a default, but in my opinion, protests need to be disruptive if they're going to get anyone's attention at all. I don't really see what a few people standing on the sidewalk with cardboard signs are supposed to accomplish.

Long before LLMs, programmers regularly and massively underestimated how hard it is to automate other people’s work. Knowledge workers often think carpenters just bang nails into wood, while blue collar workers think knowledge work as sitting in front of a screen copying values from Excel on the left into a form on the right while sipping a latte.

Only like 2.5 years ago, I thought programming would be one of the last knowledge worker jobs to be significantly affected by LLMs, not one of the first. I think AI models will continue to be very impactful. But for quite a while, they may mostly turn knowledge work into a last mile problem rather than eliminating it.

I used DeepSeek, Kimi, GLM, Qwen, and MiMO against GPT-5.5 high as reference, all running in Pi harness without anything installed.

So far, Kimi and MiMO look the most promising to me. I haven’t tested them rigorously enough to make a strong statement, but my first impression is that, in practice, all those models may be less behind on typical daily tasks than people think.

They are a bit “work hard, not smart". Getting to same-ish results more slowly and using more tokens, but at a fraction of the price

https://www.aisi.gov.uk/blog/our-evaluation-of-openais-gpt-5...

On the other hand, with the internet inevitably becoming swamped by AI generated content, I can definitely see a de-digitalization of art moving into offline spaces. At least for independent work, you don’t necessarily need mass appeal or exposure, but rather access to individuals and small groups with an actual willingness to pay for art.

Recently, I had a more pleasant experience using LLMs with Go. It reminds me a bit of Python 2.x, when the community seemed, in my view, more focused on embracing a stupid simple language, with everyone trying to write roughly similar "Pythonic" code.

At least at the entry level. Once you want to go in depth, the outcome in my experience is the same as with LLM use on any topic depends heavily on the domain knowledge of the prompter and their ability to steer it.

For the former, greenfield projects, LLMs are easily a 10x productivity improvement. For the latter, it gets a lot more nuanced. Still amazingly useful in my opinion, just not the hands off experience that building from scratch can be now.

Of course, it requires some discipline to not just yolo the prototype into production when that’s not appropriate.

I use LLMs all day every day, but measuring someone or something by the number of lines of code produced is still incredibly stupid, in my opinion.

That’s how I feel about a lot of AI-powered development. Just because you can have 10 parallel agents cranking out features 24/7 and have AI write 100% of the code, that doesn’t mean you’re actually building a product that users want and/or that is a viable business.

I’m currently in this situation, working on a greenfield project as founder/solo dev. Yes, AI has been tremendously useful in speeding things up, especially in patching over smaller knowledge gaps of mine.

But in the end, as in all the projects before in my career, building the MVP has rarely been the hard part of starting a company.

But yes, the more specific you get and the more moving pieces you have, the more you need to break things down into baby steps. If you don’t just need it to make A work, but to make it work together with B and C. Especially given how eager Claude is to find cheap workarounds and escape hatches, botching things together in any way seemingly to please the prompter as fast as possible.

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Among the traditional artists I follow, maybe 1 out of 10 posts is directly about selling something. With AI artists, it’s more like 9 out of 10.

It might take a while for all the grifters to realize that making a living from creative work is very hard before more genuinely interesting AI art starts to surface eventually. I started following a few because I liked an image that showed up in my feed, but quickly unfollowed after being hit with a daily barrage of NFT promotions.