11–20 of 349 posts
It also reduces my hesitation to get started with something I don't know the answer well enough yet. Time 'wasted' on vibe-coding felt less painful than time 'wasted' on heads-down manual coding down a rabbit hole.
Earlier quoted context omitted.
Unlike many claims that AI works that are clearly bogus, this actually seems quite credible, because TFA describes in detail many problems encountered, which could have easily lead to a failure of the project, if not properly addressed. There is no doubt that when used in the right way an AI coding assistant can be very helpful, but using it in the right way does not result in the fantastic productivity-increasing fa…
> More important is whether the productivity improvement is worth a subscription price. Nothing that I have seen until now convinces me about this. On the other hand, I believe that running locally a good open-weights coding assistant, so that you do not have to worry about token price or about exceeding subscription limits in a critical moment, is very worthwhile. This is one thing I also wonder about. If it's a rea…
For now, there is a lot of unpredictability in the future cost of AI, whenever you do not host it yourself.
If you pay per token, it is extremely hard to predict how many tokens you will need. If you have an apparently fixed subscription, it is very hard to predict whether you will not hit limits in the most inconvenient moment, after which you will have to wait for a day or so for the limits to be reset.
Recently, there have been a lot of stories where the AI providers seem to try to reduce continuously the limits allowed by a subscription. There is also a lot of incertitude about future raises of the subscription prices, as the most important providers appear to use prices below their expenses, for now.
Therefore, while I agree with you that when something provides definite benefits you should be able to assess whether paying for it provides a net gain for you, I do not believe that using an externally-hosted AI coding assistant qualifies for such an assessment, at least not for now.
This is a great article. I’ve been trying to see how layered AI use can bridge this gap but the current models do seem to be lacking in the ambiguous design phase. They are amazing at the local execution phase.
Part of me thinks this is a reflection of software engineering as a whole. Most people are bad at design. Everyone usually gets better with repetition and experience. However, as there is never a right answer just a spectrum of tradeoffs, it seems difficult for the current models to replicate that part of the human process.
Ideally: local; offline.
Or do I have to wrestle it for 250 hours before it coughs up the dough? Last time I tried, the AI systems struggled with some of the most basic C code.
It seemed fine with Python, but then my cat can do that.
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90 percent of the things users want either A) dont exist or B) are impossible to find, install and run without being deeply technical.
These things dont need to scale, they dont need to be well designed. They are for the most part targeted, single user, single purpose, artifacts. They are migration scripts between services, they are quick and dirty tools that make bad UI and workflows less manual and more managable.
These are the use cases I am seeing from people OUTSIDE the tech sphere adopt AI coding for. It is what "non techies" are using things like open claw for. I have people who in the past would have been told "No, I will not fix your computer" talk to me excitedly about running cron jobs.
Not everything needs to be snap on quality, the bulk of end users are going to be happy with harbor freight quality because it is better than NO tools at all.
The 8-year wait is the part that stands out. Usually the question is "why start now" not "why did it take 8 years". Curious if there was a specific moment where the tools crossed a threshold for you, or if it was more gradual.
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It's funny that he used Claude instead of gemini for this. Idk if his company is happy with free advertisement of a competitor
https://techcrunch.com/2025/03/11/google-has-given-anthropic...
They don't care. They want software engineers replaced by any means necessary. They know generative AI isn't a big business, that is why they slowwalk it themselves.
Replacement won't work of course, that is why marketing blog posts are needed.