I have entire codebases of embedded software in C without the shortcuts of modern programming languages in way fewer than 35k lines

I think people will have to recalibrate on this. The LOCs do things that you otherwise would not do. Features and details that simply would not happen — because they are too code/time intensive for most projects. It just won't matter anymore.

> But why would non-technical people would even think in terms of log tailing and version control

They won't! They won't have to. The obvious good stuff that everyone thinks the AI tool should be able do, will just work, because the people building the tools, will mostly obviously focus on making them work.

https://www.recipeninja.ai/recipe/r_ttOB5xyqpOLXCL/gluten-fr...

I believe I'm going to need a new oven...

I think in the end AI will be more advanced tool, but a tool nonetheless. Like methodologies and principles, good practises etc. - they only work if you use it with care and added thought and adaptation to your case. DRY it a great principle. But sometimes it's better if you repeat yourself. For one reason or another. And these are the the tradeoffs that human in the loop should be making imho.

Also vibe code has a parallel feature, while the code is generating, you are also doing live review and correcting it towards right direction, so depending on your experience, the end product can be a bad mess or wonderful piece of creation and maintenance dream.

The issue with seasoned SWE is that, the moment a mistake(or bad pattern) is made, the baby is thrown with bath water.

For a tiered app like the one presented, 35k LOC is not really that impressive if you think about it. A generic react based front end will easily need a large number of LOC due to modular principle of components, various amounts of hooks and tests(nearly makes us 25-40% of LOC). A business layer will also have many layers of abstractions and numerous impl. to move data between layers.

The vibe code shines, when you let it build one block at a time, limit the scope well and focus. Also, 2-3 weeks is a lot of time to write 35k LOC. at start of any new project, LOC generation rate is very high. But in maintenance phase it significantly falls as smaller changes are more common.

> I struggle to find much utility in terms of actually writing code.

I personally feel you need to give up some control and just let the LLM do its thing if you want to use it to help you build. It honestly does a lot of things in a more verbose way and I've come to the conclusion that it is an LLM writing code for another LLM. As long as I can debug it, I'm okay with the code, as I can develop at a pace that is truly unreal.

I finished my "Recent" contexts feature in a half a day, today. Without the LLM, this would have taken me a week I think. I would say 98% of my code in the past few months has been AI generated. You can see a real life work flow here:

https://app.gitsense.com/?chat=eece40e2-6064-46d2-9bf1-d868c...

I truly believe if you provide a LLM with the right context, it can meet your functional specs 90% of the time. Note the emphasis on functional and not necessary style. And if *YOU* architecture your code properly, it should be 100% maintainable.

I do want to make it clear that what I am doing right now is not novel, but I believe most problems are not. If the problem is not well understood, it can be a challenge like my my chat bridge feature. This feature allows you import Git repos for chatting but I will probably need to rewrite 50% of the LLM code since the solution it built is not scalable.

For code? Autocomplete on steroids is the killer-app.

The other things the LLMs give me are prone to be over-engineered/overly verbose code or similar.

I went through a lot of "Why are you also doing $FOO then $BAR? Doesn't seem necessary if we skip them and do $BAZ which will make one or both of those redundant" and it responding "You're right! Lets use $BAZ instead".

And giving them code to make a small change to was pointless - they would often, but not always, make an incidental change far from the point where you asked for the change.

But autocomplete? That works just great and because I've already got context of the code I am writing I can check it in (at most) two seconds and move on.

After seeing how people like Andrej Karparthy used vibe coding to generate applications https://x.com/karpathy/status/1903671737780498883?s=61 I realize that

you need to be clear on what you want the LLM to do break down the tasks and give byte sized tasks to llm to do specific thing and sometimes I had to tell it not go and change random files because it found the need to refactor them.

https://www.recipeninja.ai/recipe/r_N1VSPtXzCJVV3l/diarrhea-...

[1]: https://www.bbc.com/news/articles/cd11gzejgz4o

There's also apparently a hairstyle? https://www.recipeninja.ai/recipes/hairstyle

I've written more about it here: https://simonwillison.net/2025/Mar/19/vibe-coding/ and here: https://simonwillison.net/2025/Mar/23/semantic-diffusion/

Contrasted to AI assisted coding, where you would give much more detailed prompts with technical specifications, and read over every line to make sure you understand it before accepting a response.

In theory, vibe coding can let someone with very limited technical expertise build complete apps, so understandably a lot of people are excited by it.

In practice, it doesn't seem like we're there yet. But each new step in AI development leads to people trying again, and it's hard to deny that the results are getting better. I think we're at the stage of where AI image generators were a few years ago. Very much in the uncanny valley.

I get this search result https://www.recipeninja.ai/search?name=Anti-inflammatory

What browser are you using? Voice mode or typing?

Search is working fine, I just tried https://www.recipeninja.ai/search?name=lasagne

https://www.recipeninja.ai/recipe/r_LZarKW1PMNlSlx/rubbery-l...

All Ingredients

- rubber cement, 2 cups

- water, 1 cup

- lasagne noodles, 1 box

- shredded mozzarella, 2 cups

...

Step 2

Prepare the rubber sauce by mixing 2 cups of rubber cement with 1 cup of water in a saucepan over low heat until thickened.

The cooking book scene has been openly criticized for not actually trying the recipes, even before LLMs were a thing[0]. Regular cooking websites have always been somewhat unusable due to massive ads and fluff text because 1) SEO and 2) recipes are not copyrightable, but the fluff text is.

For quite some time I get my recipes directly from chatgpt, the instructions are very condense, they work quite well, and most importantly: It knows how to substitute ingredients. "My friend is vegan and allergic to heat-resistant soy protein" and it's going to adjust accordingly.

[0]: https://www.matchingfoodandwine.com/news/blog/recipes-that-d...

It's rare that I actually cook directly from them -- usually, that'd be big and fancy stuff or stuff I'm very unfamiliar with; in both cases I usually take the time to cross reference whatever the cookbook says with additional resources from the internet.

ChatGPT, on the other hand, I frequently use when or before cooking (and I cook virtually every day).

It's great when I only have a vague idea based on stuff in the fridge; five minutes later I've got a checklist I can reference. If it hallucinates something that I flat out don't think will work or, much more likely, comes up with something that I don't want or cannot do for lack of ingredients or time or whatever, I'll tell it to adjust the recipe and it does.

It's also great when I feed it a couple of existing recipes (from real people) to compare and contrast and integrate and reformat in a way that's most useful to me, e.g. a tabular format, or scaled to a different serving size.

With all that said, the AI based recipe sites don't really do it for me, either. If I want to cook purely AI generated recipes, a chat interface works fine -- and probably better. What I really want is an AI tool that helps me curate my own recipe collection. E.g. I want to ask it "I'd like to make Ramen, how did I do it the last time, what were my notes" and when it's done I want to tell it "ok, this was fine, I decided to double the mirin and next time I'd marinate the eggs longer" and have it update the recipe.

For context, I'm not a cooking geek or virtuoso. I enjoy it to some degree, but mostly it's just about having a nice, nutritious experience, in line with whatever my mood might be. I only ever measure things super accurately when I'm baking things in the bread maker (because it doesn't let you make corrections). For most meals, I wing half the measurements and time estimates.

In my experience, most "human recipes" are just random variations on some baseline. I hate looking for recipes on recipe sites, youtube, etc. There are food bloggers that are exceptions, but usually I'll just end up scrolling for a long time with just frustration to show for it. If I sort of know some of the ingredients I want to use, have some sense of the type of eating experience I'm going for, and I want a bunch of recommendations based on that, regular "human recipe" sites are not the answer.

90% of my new recipes come from ChatGPT, and that ratio is increasing. I just marinated some chicken based on a recipe it magicked for me. I asked for insights on mixing mayo and yoghurt in the same marinade, because I had leftovers of both. It gave me 5 or so diverse recipes, and I just picked the one that best fit my pantry and mood. I also asked it to convert the recipe from volume to weight, not to mention scale it for my specific quantity of chicken, which was super handy.

I find that ChatGPT is great at providing common sense instructions and approximations. It's absolutely awesome at clobbering together a meal from ingredients I tell it I have. I can have an actual dialogue about any of it, get all kinds of recommendations and insights. That's been very useful to me. I'd go as far as to say that recipe generation is one of the easiest real problems for an LLM to solve. Or, at least for the kinds of recipes I use.

I've done my share of recipes from Serious Eats, but they weren't particularly good. I was doing Breton galettes the other week, which are notoriously fiddly to get right. Serious Eats had a huge article about it, interesting insights, but their final recipe sucked, and I was trying to be accurate. Not only I failed to get the consistency right, the wheat-buckwheat ratio was nowhere near what you'd get in France. I say, write researched articles about what makes recipes work. I can read it, I can bounce my LLM off it. If it's a fiddly recipe, I'll have to fiddle with it no matter what. If I can have a conversation with an LLM about principles at work, that's much better to me than a bunch of "human recipes".

Also, I often have questions about alternatives or things I need advice on as I'm preparing food. I'll also look at the recipe a gazillion times to check the instructions, quantities, etc. I'll set and check a timer often too. A voice-assistant is the obvious answer to this, which I'll try at my earliest convenience.

Kudos to the author!

Edit: and right after this, I run into another AI-related gem: https://artificialintelligencemadesimple.substack.com/p/ai-t...

But yes, websites will now be filled with these low-quality recipes, and some might be outright dangerous. Cyanide custard should ring alarm bells, but using the wrong type of mushroom is equally dangerous and much more challenging to spot.

https://www.ojp.gov/pdffiles1/Digitization/132907NCJRS.pdf

Now updated to include real cum!

Dish: Fek Yerr AI Slop Garbage Plate All Ingredients

    motherboard, 1, diced
    cpu, 1, diced
    olive oil, 2 tbsp
    binary code (0s and 1s), 1 cup
    soy sauce, 3 tbsp
    teriyaki sauce, 2 tbsp
    ram chips, 1 cup
    microchips, 1/4 cup
    led lights, as needed

What is notable here is that someone is demonstrating that the systems are reaching a quality where this is possible.

> Did any of it make you a better programmer?

By conventional metrics, if the job got done well enough in less time, yes, even if less skill is involved.

Then you handle those function calls in your javascript.

``` if (function_name === 'search_recipes') { const searchParams = new URLSearchParams();

      if (args.name) searchParams.set('name', args.name);
      if (args.difficulty) searchParams.set('difficulty', formatDifficulty(args.difficulty));
      if (args.min_duration) searchParams.set('minDuration', args.min_duration.toString());
      if (args.max_duration) searchParams.set('maxDuration', args.max_duration.toString());
      if (args.tag) searchParams.set('tag', args.tag);
      
      // Handle ingredients array correctly - the search page expects ingredients[]
      if (args.ingredients && args.ingredients.length > 0) {
        // Clear any existing ingredients
        searchParams.delete('ingredients[]');
        
        // Add each ingredient individually with the correct array notation
        args.ingredients.forEach((ingredient: string) => {
          searchParams.append('ingredients[]', ingredient);
        });
      }
      
      const queryString = searchParams.toString();
      const url = queryString ? `/search?${queryString}` : '/search';
      
      navigate(url);
      return;
    }
    
    // start_cooking function
    if (function_name === 'start_cooking') {
      // First check if we have an onStartCooking callback registered
      if (callbacksRef.current.onStartCooking) {
        callbacksRef.current.onStartCooking();
        return;
      }
    }

https://news.ycombinator.com/newsguidelines.html

https://news.ycombinator.com/showhn.html

Please don't attack others or their work like this on this site, regardless of who or what you have a problem with. It's the opposite of the curious, respectful conversation we're looking for, and always has been.

(2) This particular post is an interesting data point in the research of what the current crop of LLM-based tools is capable of. It reads a bit like a Windsurf ad; I would like more details on how the technical side of the development panned out, what were the problems and where, how were they overcome, etc.

(3) The parent comment reads as a somehow funny mix of socialist "anti-greed" agenda and frowning upon the fact of sharing knowledge and experience freely.

Less tongue-in-cheek: there's no word censorship in HN. You can say "kill myself" here.