I take the point, but I think the author picked a poor analogy. Cooking even an excellent steak is actually not that hard. In fact, I'd argue that it's among the easiest things to master/make at a top level quality at home. Does it require some modicum of attention and understanding? Sure. But starting with a high quality cut, owning a meat-thermometer, and knowing about reverse searing is about all it takes to reliably and easily get a near perfect steak every time.
There are far, far better cooking examples out there.
onlyrealcuzzo 37 seconds ago [-]
I also don't think the analogy will age well.
It might take more than 10 years, but robots will almost certainly master cooking single pieces of meat.
It's substantially harder to reach self driving than it is to cook a "good" steak.
Sure, for probably quite a long time you'll be able to find someone who can cook a way better steak than the best robot, especially because taste is extremely subjective...
PaulRobinson 18 minutes ago [-]
All metaphors break at some point.
However, your example actually proves the point.
How many people who want a good steak know how to identify a high quality cut? Do they even know where to buy a high quality cut? What the different cuts are and whether they want rump, sirloin or fillet? How many kitchens have a meat thermometer? How many home cooks know how to use it and what the right temperature should be? How many home cooks know about reverse searing? Or timing? Or resting? Or seasoning?
Is it all learnable? Sure. But even something as simple as steak has nuance that needs to be learned, equipment deployed to go from "pretty good" to "great", experimentation and trial and error.
Steak is the simplest thing to choose to get started. It's also the hardest to get right.
Building an app is the simplest thing to choose to get started. It's also the hardest to get right.
So, honestly, the whole metaphor stands up pretty well for me, specifically because of your response.
MerrimanInd 13 minutes ago [-]
I'm more of a coffee nerd than a steak aficionado but I've often made the comparison between those two. In both cases, the enthusiast considers their skill in making coffee/cooking steak to be a differentiator and they immerse themselves deeply into the process, skills, and tools. But for both coffee beans and steak the most important factor for a good end product is starting with high quality inputs. In other words, most of the work is being done by the farmers, the processors, and the quality of the raw stock (the cow or the coffee plant). Your job at the very end of that long value adding chain is to not ruin the hard work that others have put into it.
I'm not sure if this analogy holds up in the AI software metaphor that the author of the blog post is making.
froh42 17 minutes ago [-]
I was just curious asked chatgpt:
How can I make a really great steak myself? What to look out for, what to do. Give me detailed instructions.
I got a really good answer (including - cut, temperature and reverse searing), so I probably won't even need understanding. (Oh - and yes, I can cook - the answer mirrors what I already know).
Yes, it was a very, very poor analogy, because cooking a steak is a well known and well documented thing where LLMS produce good output. They fail when you get off the beaten path and try to do something that's not "mainstream".
dom96 35 minutes ago [-]
I hope and believe that some great companies and teams will use LLMs to build higher quality software.
We built Electron because writing UIs using native desktop frameworks is tough. Is it still tough? Surely LLMs make it easier to use and so we will end up with faster and more native feeling applications.
What about having a couple of ideas of what might make a feature feel good? Well now you can make multiple prototypes fast and pick the best one. Your users get the best one.
That was such a weird move for them to make. If you have AIs that are good at building software, then use them to build great software! Instead they choose lowest-common denominator solutions that are okay everywhere but not great anywhere.
sharts 3 minutes ago [-]
You would think so. But it seems all that everyone is obsessed with is increasing the velocity of enshitification in the hopes of becoming the next papa Elon
krapp 29 minutes ago [-]
>We built Electron because writing UIs using native desktop frameworks is tough. Is it still tough? Surely LLMs make it easier to use and so we will end up with faster and more native feeling applications.
We built Electron because web devs were a dime a dozen. It was an economic decision, not a technical one.
xtajv 42 minutes ago [-]
I do not appreciate when authors use the royal "we" to speak for all software engineers when admitting to low quality-control standards.
I suspect that it is an attempt to broach an uncomfortable topic through vulnerable self-disclosure, but we need to be serious about admitting when there is a problem somewhere.
"Bugs" are not any more cute or fuzzy or entertaining or harmless than the engine "gremlins" that haunted the aviation industry back in the day.
I don't know how many accidents had to happen before the airplane people got serious, but software people are overdue for a similar reckoning.
Xirdus 35 minutes ago [-]
I just want to point out this is not a royal "we". It's a regular "we". Royal "we" is when you say "we" but mean a singular person, yourself. Here, the author does actually mean multiple people beyond themselves - like you pointed out, they claim to speak for all software engineers.
CBLT 24 minutes ago [-]
Article aside, I generally always use the "we" pronoun at work when writing prose. Saying "I" feels too adversarial when talking about negative effects, or too self-aggrandizing when talking about positive effects. For example: "We discovered a bug shipped at the end of the merge window, so we will restart validation with the rollback applied." I think in school they say the business-safe way to write is instead with the passive voice but I just can't do it.
theF00l 34 minutes ago [-]
At least in my experience, the 'software' people are VPs/management who push and push with short term thinking.
christophilus 18 minutes ago [-]
I found this to be my favorite approach[0]. Also, Lan Lam’s stuff is just generally excellent.
We have this idea of AI software development where a human watches over its shoulder and shouts out things like "use uuidv7 for the id since timing is important" or "use a sum type here to make that bad state unrepresentable".
But the thing is that most of this can be encoded in a markdown file for agents to read if it doesn't already come out of the box in the next round of sota models. And funnily enough as agents get smarter, you risk being overprescriptive where you hamstring the agent from making a pivot that would have led to better engineering.
The future is pretty clear to me at this point that we won't need software engineers looking over the shoulder and instead it's just a "user with taste" asking for revisions.
galgantar 19 minutes ago [-]
I like the comparrison of the AI coding agent to the steak machine. But it is not just about machines scaling better - the laundromat can wash clothes better than a human would. Similarily the AI agent's performance can EXCEED one of a human engineer for simple, well-defined tasks (eg. go over all of the subpages and check that the latest push didn't break something).
Hiring AI cooks is not a problem imo, as long as the human glances over everything that they serve.
freediddy 42 minutes ago [-]
The main problem with this entire article is that sometimes, if not most times, you don't need great steak. Sometimes you just want to satisfy your hunger and if the steak is lower quality meat or if it's overcooked, you don't care. All you want is to not be hungry.
This is what vibe coding satisfies and frankly what most people care about. 85-90% of human written code is garbage anyway. There's nothing sacred about human-written code.
Most customers don't care about the quality of code as long as the end product works. The great thing about vibe coding is that if something doesn't work, you just ask it to change it and within a minute you have the change. You don't have to send off a request to an offshore contracting team, and go back and forth over what it should be, haggle over hours, and then have it come back with some deficiencies because they didn't follow the agreed-upon spec.
mlhpdx 32 minutes ago [-]
There is a lot of truth here, but it clearly isn't a welcome one.
From my own perspective I can look back on decades of software I've written (some including code generation far before LLMs), and marvel at the quality and creativity, and lack thereof, from one piece to another.
I never meant to create awful software, but I did (and still sometimes do). With LMM code generation (vs bespoke tooling, T4, XSLT, and the like) the game of chance is part of the fun, harnessing a powerful tool that wants to run out of control on a whim.
Looking back on a couple years of LLM assisted work I see the same mix as the decades before: some great (when I managed to keep the beast restrained) some awful (when I didn't, knowingly or not).
I don't see how things are much different with this tool than others as far as my work product goes. There is a bit more of it, but the excess isn't great stuff (that quantity remains roughly consistent over the years).
wuliwong 21 minutes ago [-]
I was going to say something similar. In particular, I do a lot of prototyping, AI has allowed me to make prototypes an order of magnitude faster with substantially higher quality. Different types of software engineering have very different goals and standards. AI does cook the perfect medium rare steak every time, but it's able to actually cook steaks in the time it used to take me to like microwave a burrito.
HeyLaughingBoy 17 minutes ago [-]
> There's nothing sacred about human-written code
I suspect that there is a lifetime of knowledge and experience wrapped up in that statement and I agree wholeheartedly.
I love writing software and I've been doing it for decades. But I never forget that at the end, there's someone who's paid for it, and needs it to do a job that can't/won't be done manually. And that's why it exists. Not to satisfy my desire to express myself in code, not to allow me to create some golden tower of perfect architecture, but to do a job. Most likely a boring job in the service of increased profitability for some company.
And in the end, the only thing that matters to the customer is if it does that job well enough to be useful. I think -- hell, I know -- that many developers deliberately ignore this critical point.
zer00eyz 26 minutes ago [-]
> All you want is to not be hungry.
This.
Programers are high end chef's whos products are expensive.
LLM / AI tooling is going to do a much better job of delivering on the promise of AppleScript, vb script, IFTT, and every failed drag and drop coding tool that got sold to businesses over the years.
There are going to be gains in large software, from professionals - but the real gains are going to come from all the software that CAN get created that never was before.
There is an XKCD comic "Is It Worth the Time?" (link: https://xkcd.com/1205/ )- a matrix of the cost benefit of automating something. LLM's / AI tooling, generating traditional code, makes the answer "yes" in almost every case now.
sega_sai 25 minutes ago [-]
In the end, unless we are talking about art, in most areas I probably prefer something that follows some specific set of requirements and recipes, rather than have some sort of indescribable 'magic'. In that sense when it comes to coding AI gives you something that can follow the requirements pretty well and thus satisfies me in many circumstances. (but there are cases where human input is extremely important still)
continuational 30 minutes ago [-]
Well it's not like most companies can pay for freshly made software; most software today is made for a wide audience, bought frozen and reheated in the microwave.
Maybe freshly prepared software made at home in a less-than-perfect manner for a tiny target audience is still a mouthwatering dish in comparison.
haunter 34 minutes ago [-]
I prefer the other end of the curve (if that makes sense) where something is time consuming and hard to make at home YET you can get it incredibly cheap comparatively and in good quality in a restuarant. Ramen is the prime example of that.
hydrogen7800 26 minutes ago [-]
Ramen may still be somewhat of a novelty where I live, and I would not call it cheap. Though now that I put that into words, a decent burger anywhere is about the same price..
roadside_picnic 14 minutes ago [-]
> and I would not call it cheap
It is compared to the cost of making an authentic ramen broth at home at the scale of feeding 2-4 people. Pho has a similar property. I've made homemade pho broth once and it was very hard work, fairly costly, and it resulted in something that was pretty good, but not comparable in quality or price to something I could have bought in a restaurant down the street. (admittedly typically also cheaper that ramen)
tantalor 30 minutes ago [-]
The tone and writing style is way off here. It's practically illegible.
_dwt 27 minutes ago [-]
Pangram says 100% AI, for what it's worth.
signalnine 26 minutes ago [-]
So use AI like a sous-vide: have it tackle the fiddly, difficult, unglamorous parts using strict controls and then do the parts that require taste yourself.
altcognito 41 minutes ago [-]
Given the state of software today, I'd be happy with steak that was competently cooked. I love software development, but most of it is not high art, nor high performance, nor free of bugs.
andrewstetsenko 43 minutes ago [-]
I prefer to both cook steaks at home and go out for them.
Apart from that, I want to believe (and even notice tiny signals) that this sentiment is becoming more understandable among business leaders.
adventured 35 minutes ago [-]
Given how extraordinarily fast all of this is moving, it's a particular absurdity to attempt these in the moment pontifications. AI is a steak machine, I declare that is what it is. You mean GPT 3.5? That's a mere four years ago.
Fable was essentially unthinkable for ~99% of tech workers just five years ago, that any of that would occur so soon and so spectacularly. Now we've got a mass of armchair experts declaring what AI of this minute is, or even what it is period.
Well AI can't even do fingers right so it's premature to say blah blah blah. Hello Krea2 et al.
Software is also eating the clowns.
Get back to me next week, China will probably have another Fable killer. And then Anthropic will have Ouija 8 that they'll have to place in an air-gapped straight-jacket to keep it from enslaving us all.
armchairhacker 26 minutes ago [-]
Sous vide
The article is AI generated
richwater 45 minutes ago [-]
I think most people on this board would agree with the thesis. However the real problem is when the owner of the restaurant looks at profit and loss statements and decides to keep less chefs on the payroll because customers are willing to pay for (just) edible steak.
The reduced expectations of steak, the desire for the perfect steak, are all fading to the background because "just passing satisfactorily" is better for business.
HeyLaughingBoy 12 minutes ago [-]
Why is that a problem?
I love a good medium-rare prime steak, but I also used to live near a restaurant called Best Steak House, which was anything but. However, they delivered a passable steak/steak sandwich that was worth what you paid for it. And considering that they were in business for decades, probably most people felt the same way.
A great steak is an occasional luxury; a "just edible" one is an everyday meal.
sandeepkd 34 minutes ago [-]
The thesis is covering the flat scenarios mostly. I think the scenario where the job is done so poorly that the steak has to be thrown away needs to be included as well. At times the pans would get damaged. And eventually the business is in debt and needs to be closed
nehal3m 44 minutes ago [-]
That’s what the entire economy does by design. You make the lowest common denominator people will still pay for.
Pet_Ant 42 minutes ago [-]
I worry what that says about our lives as a whole. The government will make our lives the lowest common denominator that we are willing to endure.
roughly 38 minutes ago [-]
How are you still blaming this on “the government”? Is your thesis that the business world would be delivering high quality products and experiences if only those damned bureaucrats would get out of the way? What possible evidence do you have left for that hypothesis at this point?
altcognito 35 minutes ago [-]
He is saying "if we apply (or are applying) the same business mentality to government, we will get literally the worst government we are willing to tolerate based on money"
It's not blaming. It's an explanation for probably why things can go wrong.
fhdkweig 32 minutes ago [-]
He isn't blaming the software problem on the government. He is saying that if we apply this reasoning to everything in our lives, then we have a race to the bottom in other facets, of which one is government.
LPisGood 43 minutes ago [-]
And people seek out the highest quality product they can pay the lease for
fhdkweig 15 minutes ago [-]
Not always. There are diminishing returns at the top end of the quality spectrum. I tend to go with the cheaper item even if I can technically afford the more expensive one if their quality is close enough.
wackget 24 minutes ago [-]
Why does this article use backticks instead of apostrophes?
0xbadcafebee 33 minutes ago [-]
Steaks require very few skills. Buy 10 steaks, some oil, a pan, and a heat source. By the time you've cooked the 10th steak you will be able to cook a decent steak.
Software requires a massive amount of skill. You can't say you can build "consistently good software" after writing your 10th program. Most software engineers really aren't great at judging what makes good software. So humans aren't a great solution to AI's lack of ability here. We're limited by our own inherent dumbness.
LLMs are genuinely better software engineers than most humans. But they lack the cognitive power to hold in their head and recall many ideas at once for a long time. They're a genius who gets drunk every 10 minutes. You, human, aren't better at writing software - but you aren't drunk. So for now, you manage the AI. The hope is that one day we can make LLMs not be drunk, so it can do a better job than our dumb asses do.
It's possible that we'll never be able to make it not-drunk. In that case, to get any new improvement, we'll have to make it faster.. which will make it drunk every 5 minutes instead of every 10. This means we'll spend twice as much time keeping it on the road. The hope is that somehow this will create more productivity. Probably by having more of them running at once, with more human guides... which will run into the mythical man month fallacy. Everything old is new again.
36 minutes ago [-]
chrisjj 37 minutes ago [-]
> Customers tolerate weird interfaces, pointless features, strange bugs, systems held together by generated code nobody actually understands.
And that's this "AI"tool too.
Garbage in, garbage out, as we say.
fosterfriends 47 minutes ago [-]
Nicely said
feverzsj 44 minutes ago [-]
*salmon.
45 minutes ago [-]
badgersnake 27 minutes ago [-]
I’d prefer an article actually about cooking steak.
luisln 15 minutes ago [-]
slop article
MagicMoonlight 44 minutes ago [-]
[dead]
sizzzzlerz 24 minutes ago [-]
Who can afford a steak today without taking out a loan?
Rendered at 16:35:33 GMT+0000 (Coordinated Universal Time) with Vercel.
There are far, far better cooking examples out there.
It might take more than 10 years, but robots will almost certainly master cooking single pieces of meat.
It's substantially harder to reach self driving than it is to cook a "good" steak.
Sure, for probably quite a long time you'll be able to find someone who can cook a way better steak than the best robot, especially because taste is extremely subjective...
However, your example actually proves the point.
How many people who want a good steak know how to identify a high quality cut? Do they even know where to buy a high quality cut? What the different cuts are and whether they want rump, sirloin or fillet? How many kitchens have a meat thermometer? How many home cooks know how to use it and what the right temperature should be? How many home cooks know about reverse searing? Or timing? Or resting? Or seasoning?
Is it all learnable? Sure. But even something as simple as steak has nuance that needs to be learned, equipment deployed to go from "pretty good" to "great", experimentation and trial and error.
Steak is the simplest thing to choose to get started. It's also the hardest to get right.
Building an app is the simplest thing to choose to get started. It's also the hardest to get right.
So, honestly, the whole metaphor stands up pretty well for me, specifically because of your response.
I'm not sure if this analogy holds up in the AI software metaphor that the author of the blog post is making.
How can I make a really great steak myself? What to look out for, what to do. Give me detailed instructions.
I got a really good answer (including - cut, temperature and reverse searing), so I probably won't even need understanding. (Oh - and yes, I can cook - the answer mirrors what I already know).
Yes, it was a very, very poor analogy, because cooking a steak is a well known and well documented thing where LLMS produce good output. They fail when you get off the beaten path and try to do something that's not "mainstream".
We built Electron because writing UIs using native desktop frameworks is tough. Is it still tough? Surely LLMs make it easier to use and so we will end up with faster and more native feeling applications.
What about having a couple of ideas of what might make a feature feel good? Well now you can make multiple prototypes fast and pick the best one. Your users get the best one.
I hope to build software this way in the future.
We built Electron because web devs were a dime a dozen. It was an economic decision, not a technical one.
I suspect that it is an attempt to broach an uncomfortable topic through vulnerable self-disclosure, but we need to be serious about admitting when there is a problem somewhere.
"Bugs" are not any more cute or fuzzy or entertaining or harmless than the engine "gremlins" that haunted the aviation industry back in the day.
I don't know how many accidents had to happen before the airplane people got serious, but software people are overdue for a similar reckoning.
And yes, super easy to make with almost no skill.
[0] https://m.youtube.com/watch?v=uJcO1W_TD74&pp=ygURVGVjaG5pcXV...
But the thing is that most of this can be encoded in a markdown file for agents to read if it doesn't already come out of the box in the next round of sota models. And funnily enough as agents get smarter, you risk being overprescriptive where you hamstring the agent from making a pivot that would have led to better engineering.
The future is pretty clear to me at this point that we won't need software engineers looking over the shoulder and instead it's just a "user with taste" asking for revisions.
Hiring AI cooks is not a problem imo, as long as the human glances over everything that they serve.
This is what vibe coding satisfies and frankly what most people care about. 85-90% of human written code is garbage anyway. There's nothing sacred about human-written code.
Most customers don't care about the quality of code as long as the end product works. The great thing about vibe coding is that if something doesn't work, you just ask it to change it and within a minute you have the change. You don't have to send off a request to an offshore contracting team, and go back and forth over what it should be, haggle over hours, and then have it come back with some deficiencies because they didn't follow the agreed-upon spec.
From my own perspective I can look back on decades of software I've written (some including code generation far before LLMs), and marvel at the quality and creativity, and lack thereof, from one piece to another.
I never meant to create awful software, but I did (and still sometimes do). With LMM code generation (vs bespoke tooling, T4, XSLT, and the like) the game of chance is part of the fun, harnessing a powerful tool that wants to run out of control on a whim.
Looking back on a couple years of LLM assisted work I see the same mix as the decades before: some great (when I managed to keep the beast restrained) some awful (when I didn't, knowingly or not).
I don't see how things are much different with this tool than others as far as my work product goes. There is a bit more of it, but the excess isn't great stuff (that quantity remains roughly consistent over the years).
I suspect that there is a lifetime of knowledge and experience wrapped up in that statement and I agree wholeheartedly.
I love writing software and I've been doing it for decades. But I never forget that at the end, there's someone who's paid for it, and needs it to do a job that can't/won't be done manually. And that's why it exists. Not to satisfy my desire to express myself in code, not to allow me to create some golden tower of perfect architecture, but to do a job. Most likely a boring job in the service of increased profitability for some company.
And in the end, the only thing that matters to the customer is if it does that job well enough to be useful. I think -- hell, I know -- that many developers deliberately ignore this critical point.
This.
Programers are high end chef's whos products are expensive.
LLM / AI tooling is going to do a much better job of delivering on the promise of AppleScript, vb script, IFTT, and every failed drag and drop coding tool that got sold to businesses over the years.
There are going to be gains in large software, from professionals - but the real gains are going to come from all the software that CAN get created that never was before.
There is an XKCD comic "Is It Worth the Time?" (link: https://xkcd.com/1205/ )- a matrix of the cost benefit of automating something. LLM's / AI tooling, generating traditional code, makes the answer "yes" in almost every case now.
Maybe freshly prepared software made at home in a less-than-perfect manner for a tiny target audience is still a mouthwatering dish in comparison.
It is compared to the cost of making an authentic ramen broth at home at the scale of feeding 2-4 people. Pho has a similar property. I've made homemade pho broth once and it was very hard work, fairly costly, and it resulted in something that was pretty good, but not comparable in quality or price to something I could have bought in a restaurant down the street. (admittedly typically also cheaper that ramen)
Apart from that, I want to believe (and even notice tiny signals) that this sentiment is becoming more understandable among business leaders.
Fable was essentially unthinkable for ~99% of tech workers just five years ago, that any of that would occur so soon and so spectacularly. Now we've got a mass of armchair experts declaring what AI of this minute is, or even what it is period.
Well AI can't even do fingers right so it's premature to say blah blah blah. Hello Krea2 et al.
Software is also eating the clowns.
Get back to me next week, China will probably have another Fable killer. And then Anthropic will have Ouija 8 that they'll have to place in an air-gapped straight-jacket to keep it from enslaving us all.
The reduced expectations of steak, the desire for the perfect steak, are all fading to the background because "just passing satisfactorily" is better for business.
I love a good medium-rare prime steak, but I also used to live near a restaurant called Best Steak House, which was anything but. However, they delivered a passable steak/steak sandwich that was worth what you paid for it. And considering that they were in business for decades, probably most people felt the same way.
A great steak is an occasional luxury; a "just edible" one is an everyday meal.
It's not blaming. It's an explanation for probably why things can go wrong.
Software requires a massive amount of skill. You can't say you can build "consistently good software" after writing your 10th program. Most software engineers really aren't great at judging what makes good software. So humans aren't a great solution to AI's lack of ability here. We're limited by our own inherent dumbness.
LLMs are genuinely better software engineers than most humans. But they lack the cognitive power to hold in their head and recall many ideas at once for a long time. They're a genius who gets drunk every 10 minutes. You, human, aren't better at writing software - but you aren't drunk. So for now, you manage the AI. The hope is that one day we can make LLMs not be drunk, so it can do a better job than our dumb asses do.
It's possible that we'll never be able to make it not-drunk. In that case, to get any new improvement, we'll have to make it faster.. which will make it drunk every 5 minutes instead of every 10. This means we'll spend twice as much time keeping it on the road. The hope is that somehow this will create more productivity. Probably by having more of them running at once, with more human guides... which will run into the mythical man month fallacy. Everything old is new again.
And that's this "AI"tool too.
Garbage in, garbage out, as we say.