Comment by tezza | Hacker News Reader

Comment by tezza | Hacker News Reader

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check the backlinks[1][2] in the article before you start throwing around accusations. I am not (yet) a person that has advanced notice and access to models.

Fable just got announced and I did a rush out article because people are curious. I released the post mere hours afterwards and it takes time to create the output, slice into videos, make a wordpress article on top of taking my son to basketball training and eating dinner. I’m in London and this was all happening at 1am.

If you check the links my previous articles have all the juicy stuff you are criticising me for not having with little preparation.

How is a side by side direct comparison NOT precise?

[1] first in series from 2025: https://generative-ai.review/2025/05/vibe-coding-my-way-to-e... . This has all the background you are talking about in the Appendix

.

[2] https://generative-ai.review/2026/05/vibe-coding-my-way-to-e... . Second in series 2026 has a side by side table of what changed. This is what is possible with more than a few hours advanced warning.

I did browse and check the links. This was the first link I went to: https://generative-ai.review/2026/05/vibe-coding-my-way-to-e... as it's the main one on the page, and I saw more qualitative stuff without quantitative stuff.

I just read the extra link you provided which has some more information, thank you. Sorry, but the links confirm my points. You're not giving any quantitative analysis of your use of the different LLMs or your process. Your "sciencey appendix" is all about the domain science of pyramids, nothing to do with how or what you put into the LLMs, or any quantitative analysis of the code put out.

I'm sorry, your response has just proved the point that frustrated me: you've either lost or never had the capability to recognise a decent quantitative assessment of technical software creations.

Your entire site is obssessed and fixated on the impressive looking outputs of LLMs, rather than actual quantitative assessment of the quality of the outputs. This is the killer problem of AI: it looks like it's good, and a lot of the time, things that look good are good. It's very easy to make stuff on a computer that looks good but isn't for various reasons, and I nothing in what you've said here suggests that you fully grasp that. Sorry again to be harsh here, this is just my opinion, and we're probably going to have to agree to disagree.

There are benchmarks if you want quantitative results. Mine is qualitative, and clearly billed as such. Comparison and contrast still possible.

My good lord Tezza. You still have claim and composed response after that sort of insults being throw at you. Haven't seen one this bad for quite sometime on HN. I hope you have a great day.

Fair comment, it wasn't my intent to insult - I can completely see how it could come across as a lot more personally and insulting than I intended - sorry Tezza. I hope it's understood my frustration is not at the person or content itself (which I'm sure are both genuinely interesting and decent in the right places!) just the voluminous, qualitative and domain specific nature of the it in response to a request for quantitative stuff.

I hope you were both able to have great days since!

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