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I have used skills like impeccable, ui-ux-max, and many, many others and they all seem to converge on the same thing. They are good to help out with some inconsistencies, accessibility, streamlining, but the design itself is the same unless you are extremely explicit.

It at least tries to attack the convergence directly by keeping a log of past builds in .hallmark/log.json and hard-fails a run that repeats the last few page structures or themes. While it still admits its nav-rotation rule is "the single most-violated rule in practice"...

Pretty much my experience as well.

At the end of the day you pretty much gotta direct and iterate over and over.


I have tried all possible ways: skills, shuffle.dev ai editor, moonchild.ai, giving screenshots of existing sites as a sample. I don’t count Lovable or Figma html2figma plugin or figma2code plugin etc.

After burning a lot of time and endless tinkering, I have realized that the only way to speed up the process is draw on paper into the most detail you can, then redraw into figma or penpot (architects that draw more nicely, can scan images) and then to prompt a LLM (multimodal one that can ingest images).

This may lead to less sloppy design.

I have tried impeccable, jakubkrehel skills, and many others.

LLMs still put something AI-ish into design anyway, you can feel it. So first faster step with less iterations is simple drawings and design logic by hand. (There was a study that said that drawing by hand uses different brain ways than drawing with mouse - this is the reason behind artists’ use of large scale tablets and multitouch pens.)



Frist three apps won't even load.


Did not feel as an upgrade to me at all, felt way slower at the same quality level as 4.8 to me.


What are your uses for it? If you don't mind sharing.


Writing blog posts and HN comments about how awesome OpenClaw is its #1 utility.


For me, personal home IT “chores” that I’ve put off for years. I can do them, but god what a pain in the ass to spin up a VM, configure Prometheus, configure grafana, configure a bunch of collectors for my WiFi and network infrastructure, and then spend a night or three tweaking dashboards and re-learning promql or whatever.

I just end up never doing it. Got it done in a couple hours with openclaw.

I’m sure there are much better ways to do that, which I will now learn in time due to the initial activation energy being broken on the topic. But for now, it’s fun running down my half decade old todo list.


I haven’t found ANY uses for it where it actually did what it was supposed to do.


I wonder about this as well. I see people breathlessly talking about how it manages their inbox or checks flight statuses, but how often should you need a bot for these things?


And then you have to remind it frequently to make use of the files. Happened to me so many times that I added it both to custom instructions as well as to the project memory.


Would love to check it out too once you put it up.


Here's a sneek peak into how it looks like/what it is. If there's still appetite for the source code, I'll probably drop a gh link by the end of the week: https://streamable.com/amdz92


Could you share some suggestions or links on how to best craft such very precise prompts?


Wasn't me but I think the principle is straightforward. When you get an answer that wasn't what you want and you might respond, "no, I want the answer to be shorter and in German", instead start a new chat, copy-paste the original prompt, and add "Please respond in German and limit the answer to half a page." (or just edit the prompt if your UI allows it)

Depending on how much you know about LLMs, this might seem wasteful but it is in fact more efficient and will save you money if you pay by the token.


In most tools there is no need to cut-n-paste, just click small edit icon next to the prompt, edit and resubmit. Boom, old answer is discarded, new answer is generated.


That's what I have been doing. The poster made it sound like they had some magical way of prompting very precisely.


It's called "prompt engineering", and there's lots of resources on the web about it if you're looking to go deep on it


You sit on the chair, insert a coin and pull the lever.


I feel quite comfortable in Excel - used various tools like Power Pivot, Power Query, OLEDB, created my own functions, Python within Excel, etc. - but Airtable felt so confusing and limiting. Other former colleagues also struggled with Airtable; maybe it was not explained to us correctly.


Ah, the very extensive study with 16 developers. Bulletproof results.


Compared to "it's just a skill issue you're not prompting it correctly" crowd with literally zero actionable data?


Yeah, we should listen to the one "trust me bro" dude instead.


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