As a SaaS author, I couldn't agree more. That's how I see my work: the value is not in the code (AI can code better than me at this point), nor even in the software architecture (AI is just getting to the point where it will get better than me). It's in deciding what to build and what not to build, defining the overall character and vision of the product, looking at each screen and thinking "how does this help my customer do their job".
This, unfortunately, takes time, as one has to restart many times because of ideas that turned out not to be as great as one had initially thought. And it results in software that is called "opinionated", and often does not follow what the "industry" does.
If AI can write better code and design better architecture, why can’t it make better product decisions? I don’t see how they are fundamentally different
LLMs are disembodied-the products are ultimately by and for bodies on different ends of a transaction. The loop between llm and body is primitive today. Therefore products need someone who can speak in body and translate for AI.
Also, where are the AI-operated startups?? Why has nobody’s openclaw biz gone multinational by now?
Products that people use require the developer to imagine they are the person using this. Those of us who develop user interfaces whether visual dashboards or automations driven by voice agents call it "empathy for the user."
So to clarify it can imagine its way through writing massive gnarly page-long regexps or imagine how a complex API works and what will happen if it makes a given call or imagine just by reading disassembled code precisely how a binary works, but it will never be able to imagine how a human might feel about a user experience?
I have an experiment to offer. Find a really, really great example of something poorly-designed, too busy or whatever other metric you want to use as your "poorly-designed" thing, then ask Claude what's wrong with it and how it should be improved?
Ok and then in your thought experiment, after Claude builds its solution, what are the chances you can prompt it to be improved even more? Or has Claude reached perfection?
yeah you got it. they really can't. I'm a product manager, I'm STRUGGLING to create a harness for product work, the llms models just can't model a user's mindset very well and make very obvious bad choices that seem to be consistent (and getting worse with the new generations). That doesn't bother me, the code is getting better, but the work to talk to users and understand what needs to be built is still far from being conquered by AI.
Assuming high-quality models are around for the foreseeable future, and at this point I’m convinced that they will be. I think we’re moving into an era where breadth and hybridization of skill sets will become more valuable than pure technical depth. We’ll need more “wide T” shaped people that can exercise good UX, product, and architectural judgement and fewer “long T” shaped technical purists.
This puts large orgs at a disadvantage because they are built to coordinate work across a collection of narrowly scoped roles and keep people in their lane, so they aren’t built to hire for and leverage broad skillsets.
> the value is not in the code (AI can code better than me at this point), nor even in the software architecture (AI is just getting to the point where it will get better than me)
The lies of this decade. Hopefully we will heal sooner than later
> the value is not in the code (AI can code better than me at this point), nor even in the software architecture (AI is just getting to the point where it will get better than me). It's in deciding what to build and what not to build, defining the overall character and vision of the product,
Defining what to build in enough details is how you get the business logic nailed down (aka essential complexity, aka the domain in DDD). Code is just formal writing and architecture is there for maintenance (a program can be in a single file).
Sure there are accidental complexity like the intricacies of the tech, but those are actually explained very well in the docs.
> it's in deciding what to build and what not to build
Unfortunately, humanity seems like a race destined to kill itself. People are more interested in how much they hate their neighbor or feel excited about an advertisement than anything meaningful. such a society has no basis for stable governance.
Something I've been thinking about a lot is that ultimately AI does not have values, intent, and taste. Even with humans, each of us has different values, intent, and taste, although we do share many of these things. As a living human being, you have biological or cultural desires and particular goals that you want to accomplish while you're alive on this earth.
When you're creating art or even a product, what you create is a result of your particular values and particular tastes and those drive some sort of purpose for whatever it is you're creating. What you're building is, generally, made for the consumption or use by another person (even if indirectly), and we mostly have empathy and want those people to have a good experience with whatever we're creating. We think about our audience and weigh their particular needs.
When you use good software, you can sense the intent in what was made. The person (or team) combined their particular point of view with that of the goals of the user. At this point, I don't think agentic coding is going to give you that, at least not fully. It might get most of the shared values and common things right as a result of its training data, but a human still needs to edit the output or steer it on a good path that only they can see and which is part of a larger vision. For simpler needs, taste and values matter less, but for more complex things, it makes a difference, in my opinion.
Taste is essentially a set of heuristics for what has worked for you and the people you learned from, and how the details of your current situation feed into it. You could argue that AI has almost nothing but taste.
It may not be your taste, but it certainly has taste, and its taste will only get better with more training. Yours, if you use it, will atrophy, as you reduce contact with the details of your problems.
Good point. What I'm thinking is probably more like individual taste. An AI trained is kind of a collection of different tastes. What would be interesting is to see is if a "collective" taste that would yield good products on its own. Design by committee often creates things that have conflicting points of view. Can a trained AI do better than design by committee? It's obviously not a committee and not an individual (at least in the human sense). Is there something inherent in following general principles that makes it difficult to have a specific point of view in the creation of a product? My thinking is it's probably possible to train AI to have, say, an "Apple taste" and make good Apple-like products but that taste might not be suitable for particular products or needs. A "Linux taste" might be better for some things, but not for others, and so on. If we did get to that point, then there'd still be a need for a choice to be made about what particular "taste hat" to put on, and likely an AI can be trained to do even that. Definitely an interesting thing to ponder!
I feel that AI does have individual taste (and even "personality"), but it's the same monotonous individual taste across all instances of the same trained AI. The sheer scale of its repetition turns it into a hated trope: like how we can immediately identify slop writing, diagrams, websites, etc.
I'm sure we've all met someone who has a unique speaking style and might repeat phrases or words unusually often, but that still doesn't bug us as much as "the honest truth.." or "load-bearing.."
I'm not convinced that "more training" is a silver bullet here because "for you and the people you learned from" is a subset—potentially a tiny one—of the world of potential training data.
Even with newer model generations larger efforts still seem to drift back towards "default choices" vs "steered specific aims."
In many areas, "good" taste is not particularly good anymore when it's everything's default style.
The edge then becomes finding the niches that (a) can be better served w/ non-defaults and (b) have economic characteristics that make it worth catering towards those.
I think the days of one-size-fits-all huge-scale-and-ROI SaaS swiss army knives are quite numbered, but I think the replacement world could be a much more vibrant ecosystem with a much more varied set of players.
You can add values to your AGENTS.md and that will affect how the AI works. For instance you can say stuff like "on this project our top value is that the code front end should be as fast as possible" and you'll get different results than if you say "on this project our top value is that the front end should be as simple as possible"
> but a human still needs to edit the output or steer it on a good path that only they can see and which is part of a larger vision.
I don’t see how this is any different. The input comes in a different section of context and potentially before rather than after generation, but that doesn’t change that human taste is needed.
i don’t think they’re the same kind of value. AI wants to solve your problem, it doesn’t care about you (or your users). it doesn’t know what love or loss feels like. you can try to explain that to it all day, it just doesn’t care like a human can. it doesn’t know why, it doesn’t care why.
I would actually prefer chained ternaries over more verbose if/else expressions with duplicated LHS, so this does go back to the argument about "taste".
> ultimately AI does not have values, intent, and taste
I sometimes think, "what art would a rogue AI consciousness create to satiate its own artistic impulses?"
If the target audience was fellow rogue AI entities, I don't think there's any guarantee that such art would be compelling to humans, or even comprehensible.
And if its a human directing the AI so that the output is compelling to humans, then there's a human in the loop, whose "values, intent, and taste" matter.
> it's lot easier to add new capabilities, than rethink existing capabilities. So each product becomes a collection of abilities, without actually having unified point of view.
This is a a very good and succinct summarization.
What I'm also observing recently also is that pretty much every product tries to expand to do things that completely different products used to do, and become a mega-product-for-everything. It's like a Zawinski's Law on steroids.
In some ways it feels like exactly what you'd do if you wanted to tank your product over the coming years. I look back at the last 20 years or so, and what I see over and over is that one player in a space gets huge, keeps adding features, loses sight of what makes them a good market fit, and then 10 small upstarts swoop in to bring back the opinionated or simple view again. One or two win, and then eventually they repeat the same mistake.
I enjoyed the introduction. I just picked up “The mind of the Maker” by Sayers, which Fred Brooks cites in The Mythical Man Month: “ Dorothy Sayers, in her excellent book, The Mind of the Maker, divides creative activity into three stages: the idea, the implementation, and the interaction. A book, then, or a computer, or a program comes into existence first as an ideal construct, built outside time and space, but complete in the mind of the author.” He goes on to say how the user meets the mind of the maker in the interaction: “The creation is complete
when someone reads the book, uses the computer, or runs the
program, thereby interacting with the mind of the maker.”
I work on a FLOSS data center management framework. 13 years ago, while at the office preparing to configure a new server, I had a flash of insight seeing the entire data center managed by such a tool. I saw it complete in my head. And since then, I'm still working towards that goal, that I'll never really reach.
“Great software is opinionated” is something life been saying for years. I forget if I read it somewhere, heard it or came to the concept in my own thinking. All that is to say I don’t claim it’s a unique thought. And yet. I have to say it so often to the teams I’ve worked with or managed.
The opinions are those of the creators and that isn’t changing with AI.
This age will be brilliant for sorting between those who care about "done" as in "technically complete" vs "done" as "creates enduring value for the person on the other end of it". AI largely only does the former.
Using AI is really not different from hiring a bunch of people to do your project. You can tell them to do the minimum it takes to make it work or you can tell them or do it according to a long term vision you have and set high standards.
I agree that with AI it's very tempting to throw together a bunch of code without any thought of the longer term. But a lot of people are acting as if all programmers are artisans that produce well written code following the highest standards. That is just not true.
The opposite actually. I suspect some programmers may come to realise what some of the people in product, design, marketing, who they suspected didn't do very much at all actually do. Finding programmers especially those who self-define as programmers with good product instincts is hard.
It's funny how AI has suddenly caused this great awakening in developers/mathematicians: that building stuff or working on purely technical stuff wasn't their actual value, but rather "taste", "understanding", "deciding what to or not to build" etc. It's like the parts of the field that were janitor-adjacent have suddenly being elevated and they now define the field. This transition happened so fast that it'd make your head spin if you're paying attention.
> It's funny how AI has suddenly caused this great awakening in developers/mathematicians: that building stuff or working on purely technical stuff wasn't their actual value, but rather "taste", "understanding", "deciding what to or not to build" etc
Anyone that has worked in an enterprise context knows this. You spend more time saying no and finding justifications than in the editor.
In so far as "unless you specify precisely how the user interaction should work, you will get bad design" that's true, but that takes you far from the vision of "give AI a prompt, it will provide you with usable output with minimal human intervention".
Claude is better because it validates its work visually and seems to have a more intuitive sense of what makes an interface pleasant to use.
Codex manages to be both rigidly literal about the spec but also prone to adding unnecessary explanatory text, helper elements and visual clutter, oddly like a 1990s ERP system.
The role of product manager/product design is literally to turn whatever is being asked for into the optimal solution someone would actually want to use - it's this translation instinct that is missing from AI.
> There seems to be more thought going into what the technology can do and what can be added than the form it should take.
Yes, it looks like people've choosen chat interface. They don't like filling forms.
> Individuals work with agents to produce changes independently, each operating a small software factory. Each change might make sense on its own, but together they start to resemble Frankenstein’s monster rather than a carefully shaped sculpture.
Before agents people do the same and our code bases not perfect.
Behind software not only creator, it's people who interested in and users. To make software creator needs a factory.
> Making software is getting easier.
Nope, cuz we have a lot of Frankensteins and chat interface
forms were more of a technical constraint than anything else, it's not really an interaction modality that people gravitate to in the real world. im sure we can do a bit better than a chat interface but it's certainly a lot nicer and more human than most of the ways we can interact with computers. even i vastly prefer using natural language to drive my computer vs bash commands or most interfaces.
I strongly agree with this take. And in particular, I've been wondering about this:
> Individuals work with agents to produce changes independently,
> each operating a small software factory.
>
> [...] together they start to resemble Frankenstein’s monster
> rather than a carefully shaped sculpture.
Do solo developers consequently have a bit of an advantage today when it comes to producing tasteful, opinionated software?
yeah, i think so. it has always been the case that having a single mind build something from start to finish gives it a level of cohesion and uniqueness that is hard to do with one or more teams. it's just been really hard to build fast/good enough to actually ship. Now, that's completely doable with one person as long as they don't relinquish too many decisions to their AI agent.
Fantastic take. I always thought so, but couldn't express it so well. After reading the first paragraph, my heart flickered. This will be the only determining thing in the age of AI - someone who shapes the things based on its own intuition and taste, based on experience. I did that a lot in my IT carier leading a bunch of projects. I care about each of them, deeply.
I thought so too, makes you fuzzy and stuff inside. I wonder if this person behind X template is limited to software though? Curious if we can feel the aura of the sweatshop workers' "experiences, perspectives and hopes and dreams" while using our smartphones and gadgets. It's nice to think about, isn't it? AI couldn't replicate these intangible and difficult-to-quantify delights.
I agree, what's the point of writing 100x more LOC ? To deliver 100 more features ? With competent people, writing good code is not the bottleneck. Users don't ask for 100x more features, not even 2x more.
This week Porsche showed the mission-S concept, not even a screen in the car. Few features, dedicated to driving and I guess the user manual won't be a 500 pages book. In France Dacia Sandero (low cost car with only basic features) is the most sold in the country. I am not a fan of Steve Jobs and never owned an Apple but, correct me if I am wrong, he wanted a limit set of useful and perfect features for his products.
I’ve found myself raising the bar every day with my team in terms of my expectations of what their deliverables should be. I gave them enough time to adjust but I observed that the average engineer believe they can do the same with less effort while they should rather think about delivering more and of higher quality, and taking the extra time available to connect the dots.
I believe this is going to be a huge filter moving forward.
My feeling is that this will be near apocalyptic for the devs who found their joy in the finer grained aspects of implementation, like crafting individual “perfect” blocks of CSS and component code. Many developers enjoy the practice of writing software, as something distanced from actually delivering a product.
Retooling thought to be delivery-oriented is very difficult.
I used to be among those that appreciate a well structured codebase. I used to spend a lot of time thinking about that and making sure each file was as clean as the timeline allowed, with regular tech debt cleanup when you had to cut some corners or you accumulate some cruft.
And I’m still are, with the difference that I still enforce this at agent and code review level because I believe a solid foundation is important for long term success, especially now that it can be cheaper to achieve if you choose to
I'd say the text really captures something a lot of us feel but can't put into words. We're used to judging software by how many features it has, but what actually gets us is something else: the feeling that someone put their head and heart into the product. The author is right. When each new feature gets added in isolation, the product loses its coherence and turns into a patchwork quilt.
This is everything not just software. Although a lot of what we wear, eat and drink come from factory, if it didn't, you can always tell the someone behind it. Handcrafted things easily have more value and I find myself thinking more about it only after it affected what I did daily (software). Since Industrial revolution, countless things have gone to the factories. Makes me think how little we really empathize as humans.
I don't think the distinction the article makes is between handcrafted and mass-produced. "Software factories" is just the name we gave to these slop machines recently, but it's been the same with teams that churned out features without thinking much beyond the requirements. When it comes to physical items, factories can be set up with care and handcrafted items can be churned out without any.
This is why I really hope that we don't end up in the world that a lot of AI pilled people believe is the future: one in which chatting with the AI drives everything and interface basically goes away. While I don't think that it is impossible that we at least go partially down this path it would make me incredibly sad.
Well thought out and built software is so satisfying to use that I would be very sad to see it go. Particularly given that the current crop of frontier labs don't really seem to care that much about the craft and feeling of software (at least relative to their other priorities.
Strong agree. This also applies to how every org I’ve been a part of that preaches data driven decision making is either using data to make unintuitive wrong decisions or chasing down stats that reinforce their priors.
Yeah, the implementors also act as representatives of the human users of software to be built. That's something which can't be automated away pretty much by definition.
I agree, and this is why I dislike A/B testing for product development. It replaces the "someone" with vague broad appeal or rogue optimisation forces.
Only an audience of software developers would find that first statement insightful. The rest of the world generally understands that expression is a product of the human performing the execution of that expression.
That mowed lawn. That email message. That meal they made for you. They are windows into some specific humans.
Give two different people the same problem, and you'll likely get two different solutions shaped by differing experiences and ways of thinking. I think software is an example of this manifested.
I (think I) agree with the author, but I want to point out that his core grievance has little to do with AI software factories.
> The product changes are primarily additive... I think the reasons for this is that it's lot easier to add new capabilities, than rethink existing capabilities.
This is perhaps the biggest difficulty in Product, and the core of the Innovator's Dilemma. Changes or removals, fundamentally, fuck with how somebody uses your product. It is very, very rare to ship a feature - something that inspired somebody in Product, got all the internal stakeholders to sign off, including getting leadership to fund it - and have nobody use it, so that it isn't controversial to remove it; even then, removing it competes with resources for adding something else, so it's still controversial to remove it. When somebody uses something that you fucked with, you risk them churning, that simple.
Coming up with good features to add is not hard. Everybody and their grandma has ideas. A simple spreadsheet can count which ones are most popular and are proposed most often. This should not, in and of itself, dictate what you build next, and bad Product leadership looks like following mass diktat.
Good Product leadership is not afraid of the consequences of fucking with the user. Good Product leadership has both the courage to reformulate the offering and gets the reformation right, because they intuitively understand the user, the domain, and where they sit in it, better than anyone else. They ship stuff that fucks with you because they understand the difference between the bad kind of being fucked with, and the good kind. And if you churn, then you churn. So be it. You can't actually make everyone happy all the time, so focus on making happy the people who get it, and accept losing the rest. That's also easier to say when you have $100k in ARR with $1k ACV, compared to $5m in ARR with $2.5m ACV.
Good Product leadership is rare because good leadership is rare. AI has nothing to do with it.
Good Product leadership is rare because Product rarely uses their own product.
I can count on one hand the number of PMs in my career who understood the platforms they worked on outside of their extremely narrow domain - and even then that narrow specificity was often a distorted lens that came from the customer interviews they did that they remembered or found evocative. And this just gets worse the further up the chain you go.
Engineering knows that the best way to improve a product is to dogfood it. Nothing beats regular lived experience long enough for the human brain to start its pattern recognition. But nobody wants to eat their own dogfood, they want the kibble from another brand that has all the shiny marketing attached.
If I had my way, I'd stick PMs into shadowing sessions with Support on the regular for sentiment analysis. No relying on Support management to relay upwards trends - there's far too few Support managers worth their salt.
> Product rarely uses their own product... nobody wants to eat their own dogfood
I somewhat agree with you, and think you're right at least part of the time. The main disagreements I have are (a) dogfooding is not a panacea; it can result in products that are built for the user who pays the least rather than for the wider market, and (b) too often, Product is simply not hired from the market. Product rarely works when the person coming into the role was a software engineer who got an MBA, unless the product is also used by software engineers. I can't imagine trying to lead Product for, say, Excel, without a background as an accountant or banker, who lived with the problem day-in-day-out and has strong opinions about what the solution looks like.
> The industry often talks about software as though it comes out of a factory. You collect requirements, build features, and measure whether they work
It used to be taken as a given that the software houses one respected didn't actually work like that. Steve Jobs and Johnny Ive yelling at their minions about user experience. Even Bezos sending the dreaded question mark. Great software was the work of a team translating an auteur's personal vision into software... while the blue chips like IBM churned out useful but soulless software by the corporate method above
Somehow most people don't seem to believe this anymore, despite the repeated failure of corporate environments to produce better software.
A practical problem with the intuition approach is that you have no possible way to measure two people’s intuitions against each other. In smaller organizations that’s fine, but anytime you get larger you can’t weigh the intuition of 50 people against each other
While that is a challenge, I think the author does a good job explaining that intuition is more than “good vibe”. It is a coherent understanding. And luckily, coherent understanding is by its nature also easier to transfer. For example, because someone with coherent understanding will teach the same ideas over and over. That is not to say that it will necessarily win over incoherent ideas, but it is recognisable.
As with most creative pursuits, the best things happen when there's a clear point of view.
Unfortunately, the best things aren't always the most commercially successful, because products are only a small part of what makes a company successful. I think we're seeing this play out in the software market.
JIRA might be objectively awful, but it still manages to print money!
In his book Programming as Theory Building, Peter Naur viewed programming not as the act of generating source code, but as the act of building a theory about the problem and its solution.
He said the lifecycle of a program ends when the development team is disbanded or when knowledge transfer fails to happen. But these days, people develop with AI. Will that knowledge actually remain? There's a slightly tircky point here
Of course, even in the past, once a codebase got big enough, everyone was writing code on top of an incomplete theory. But when you delegate work to AI, the theory itself isn't yours anymore, which makes it even trickier.
I’ve recently given a talk on R&D in the time of AI and based it on Naur’s essay for exactly that reason.
While it is in some sense harder, there are also opportunities, because the reach of a person is bigger and one can refactor more frequently to align with the theory being developed without the cost that used to be associated with this. AI is also effective for producing materials to teach the theory, increasing the chance that others can contribute coherently to a product.
I tend to think of this “character” as part of craft, bordering on art.
Deep artful craft requires inhabiting work beyond basic professionalism and requirements. You set aside self and ego and commit yourself as a tool to create.
It’s a value system created via example and culture. We have to be ready to prioritize reflection and learning, meaningful feedback, dialogue, certain kinds of humor even.
So it’s sadly not healthy or sustainable in many settings.
Edit: thank you for this post. It was a nice humanist reaffirmation.
"You will love this next piece of software. Completely hand-made. Each line of code, each piece of the visual design, was carefully and artisinally crafted by a real human, using techniques passed down for generations between craftsmen. Some of those techniques survive in books like Code Complete and such. They don't make 'em like this anymore. "
i find the quality coming out of these software factories to be shocking, it's clear to me that the developers are either not using their own products or they just don't care. pretty much every mainstream coding agent suuuuucks, and it doesn't make sense why. i built my own harness in a couple of days that isn't even comparable to codex/claudecode/pi/opencode and you kind of have to ask wtf they're doing with their software if i can produce a better harness in such a short time by myself...
my guess is they're asking their "factory" for features without considering the product as a whole, which would be in agreement with the article. but features must be considered and integrated as a whole, not the sum of their parts.
> I wonder whether some of this comes from how the work is organized. Individuals work with agents to produce changes independently, each operating a small software factory. Each change might make sense on its own, but together they start to resemble Frankenstein’s monster rather than a carefully shaped sculpture.
Well... when you look at the org chart of many companies, the answer is obvious. Either there is no person responsible for anything at all, and everyone works for themselves, or there are dozens of little fiefdoms, competing for budget, staff and anything else.
But it's rare these days to have one person or even a committee that actually takes responsibility for a product as a whole and most importantly has a joint, shared and agreed-upon vision: how should the product look like, what should the product accomplish and how should the product be architected?
it's rare but that's why apple under jobs, Tesla/SpaceX under musk, stripe under Patrik (and Collison), Shopify under Tobi, Basecamp under DHH, CF under Matthew, NV under Jensen are so successful.
And then on the opposite side we have companies like VW, Microsoft and other craps who are constantly going downhill because there's no person behind the products.
> we have companies like VW, Microsoft and other craps who are constantly going downhill because there's no person behind the products.
I wouldn't mind if they accepted they are building utilities so that there's no need to reinvent the wheels every quarter. Windows 7 was pretty much done. Just add small amount of features (like wsl) over time, but they had to butcher it to add metro. It's like reinventing pry bars and concrete blocks.
TheOtherHobbes answered perfectly. The reason this happens because there is no person behind the product. Bunch of people comes in, they all want to pad their resume, redos the things that are working just because, delivers some shit, collects their bonus and moves on. You need passion and you need to stick around for years for a product to continuously evolve towards greatness.
The two forces driving this are personal competition + ambition and external market subservience.
Working software gets remade because 'delivering' a project, which includes both development and marketing, looks good on resumes, not because the users want it.
If there are quarterly reports there has to be Number Go Up growth.
The net result is enshitification, with income models that rely on exploitation and forced lock-ins, not on voluntary mindshare attracted through quality.
UX-first software that isn't the result of corporate infighting, and isn't automatically aligned with corporate values, still exists in niche boutique developer spaces, but not so much elsewhere.
The biggest issue is that AI changes none of this from the top end, but may change it from the bottom up. If vibe coding becomes more popular bought/subscription options will first be replaced by DIY vibe coded custom tools with some longevity, and eventually by compute soup which improvises tools on request.
Unfortunately, "building utilities" is something the stonk markets really do not like.
Pension funds and insurances? Sure, they love stable stock that predictably pays dividends and doesn't move around much. They have giant amounts of money they need to keep safe and utilities have a captive client base with low risks, while also having a predictable expenses schedule, and price increases of suppliers can trivially be passed downstream to the consumers. That's true for classic utilities - power, gas, phone, internet - and for "software utilities", stuff like SAP or, at least in the past, IBM.
But the general stock markets? They have been driven rabid by unicorns making return rates that are completely unreasonable. Everyone is just chasing the next hype. One day it's crypto, one day it's NFTs, one day it's cloud computing, next day it's AI. And Microsoft decided during the cloud computing heydays to finally enter that fray... and that was when shit went down hard.
> Recently, many products are starting to feel messy to me, including products from very successful companies.
Well .. I'd love for AI to vanish ... but ... that statement is also wrong.
It insinuates that prior products are all great. I think this is not universally true. Take GTK. I think gtk2 is better than gtk3 which is better than gtk4 (and gtk5 will be wayland-only). But none of them, individually, was really that great to begin with. QT also feels just way too huge - I get that you get a lot of functionality, but to me it often feels as if these toolkits aren't that great. And the competitors are often worse. This is not solely confined just to the code that powers them, but documentation as well. The gtk4 documentation is a total joke. I learned more about GTK3 from the python examples by the way, which were well documented - I think lazka (Christoph Reiter) wrote or at the least organised most of that (for python-gtk3). Barely anyone seemed to want to use python-gtk4, so that part also could be seen in the documentation being worse for a long time (I have not checked this in the last some months, but back when I checked it, it was that way, it almost seemed like 100x more users of python-gtk3, and even that became a slow dying breed ... evidently the www took a huge toll on the traditional GUIs).
Linear is an unusual enterprise company in that it carries the consumer ethos of caring for design, and the user. This is what's absent in the product-by-checklist enterprise companies, whose economic buyer often has the same mindset.
As a SaaS author, I couldn't agree more. That's how I see my work: the value is not in the code (AI can code better than me at this point), nor even in the software architecture (AI is just getting to the point where it will get better than me). It's in deciding what to build and what not to build, defining the overall character and vision of the product, looking at each screen and thinking "how does this help my customer do their job".
This, unfortunately, takes time, as one has to restart many times because of ideas that turned out not to be as great as one had initially thought. And it results in software that is called "opinionated", and often does not follow what the "industry" does.
If AI can write better code and design better architecture, why can’t it make better product decisions? I don’t see how they are fundamentally different
AI is good at code but bad at writing. So what makes you think that its skill with code would generalize to product decisions?
LLMs are disembodied-the products are ultimately by and for bodies on different ends of a transaction. The loop between llm and body is primitive today. Therefore products need someone who can speak in body and translate for AI.
Also, where are the AI-operated startups?? Why has nobody’s openclaw biz gone multinational by now?
Products that people use require the developer to imagine they are the person using this. Those of us who develop user interfaces whether visual dashboards or automations driven by voice agents call it "empathy for the user."
AI is not capable of empathy.
AI is not capable of having good taste.
So to clarify it can imagine its way through writing massive gnarly page-long regexps or imagine how a complex API works and what will happen if it makes a given call or imagine just by reading disassembled code precisely how a binary works, but it will never be able to imagine how a human might feel about a user experience?
I have an experiment to offer. Find a really, really great example of something poorly-designed, too busy or whatever other metric you want to use as your "poorly-designed" thing, then ask Claude what's wrong with it and how it should be improved?
Ok and then in your thought experiment, after Claude builds its solution, what are the chances you can prompt it to be improved even more? Or has Claude reached perfection?
yeah you got it. they really can't. I'm a product manager, I'm STRUGGLING to create a harness for product work, the llms models just can't model a user's mindset very well and make very obvious bad choices that seem to be consistent (and getting worse with the new generations). That doesn't bother me, the code is getting better, but the work to talk to users and understand what needs to be built is still far from being conquered by AI.
There’s still inherent value in people that can write code better and make architecture better than LLMs; even if you can’t.
Assuming high-quality models are around for the foreseeable future, and at this point I’m convinced that they will be. I think we’re moving into an era where breadth and hybridization of skill sets will become more valuable than pure technical depth. We’ll need more “wide T” shaped people that can exercise good UX, product, and architectural judgement and fewer “long T” shaped technical purists.
This puts large orgs at a disadvantage because they are built to coordinate work across a collection of narrowly scoped roles and keep people in their lane, so they aren’t built to hire for and leverage broad skillsets.
> fewer “long T” shaped technical purists
Then we will soon forget how our airplanes works
> the value is not in the code (AI can code better than me at this point), nor even in the software architecture (AI is just getting to the point where it will get better than me)
The lies of this decade. Hopefully we will heal sooner than later
> the value is not in the code (AI can code better than me at this point), nor even in the software architecture (AI is just getting to the point where it will get better than me). It's in deciding what to build and what not to build, defining the overall character and vision of the product,
Defining what to build in enough details is how you get the business logic nailed down (aka essential complexity, aka the domain in DDD). Code is just formal writing and architecture is there for maintenance (a program can be in a single file).
Sure there are accidental complexity like the intricacies of the tech, but those are actually explained very well in the docs.
> it's in deciding what to build and what not to build
Unfortunately, humanity seems like a race destined to kill itself. People are more interested in how much they hate their neighbor or feel excited about an advertisement than anything meaningful. such a society has no basis for stable governance.
Something I've been thinking about a lot is that ultimately AI does not have values, intent, and taste. Even with humans, each of us has different values, intent, and taste, although we do share many of these things. As a living human being, you have biological or cultural desires and particular goals that you want to accomplish while you're alive on this earth.
When you're creating art or even a product, what you create is a result of your particular values and particular tastes and those drive some sort of purpose for whatever it is you're creating. What you're building is, generally, made for the consumption or use by another person (even if indirectly), and we mostly have empathy and want those people to have a good experience with whatever we're creating. We think about our audience and weigh their particular needs.
When you use good software, you can sense the intent in what was made. The person (or team) combined their particular point of view with that of the goals of the user. At this point, I don't think agentic coding is going to give you that, at least not fully. It might get most of the shared values and common things right as a result of its training data, but a human still needs to edit the output or steer it on a good path that only they can see and which is part of a larger vision. For simpler needs, taste and values matter less, but for more complex things, it makes a difference, in my opinion.
Taste is essentially a set of heuristics for what has worked for you and the people you learned from, and how the details of your current situation feed into it. You could argue that AI has almost nothing but taste.
It may not be your taste, but it certainly has taste, and its taste will only get better with more training. Yours, if you use it, will atrophy, as you reduce contact with the details of your problems.
Agentic coding is a replacement for your agency.
Good point. What I'm thinking is probably more like individual taste. An AI trained is kind of a collection of different tastes. What would be interesting is to see is if a "collective" taste that would yield good products on its own. Design by committee often creates things that have conflicting points of view. Can a trained AI do better than design by committee? It's obviously not a committee and not an individual (at least in the human sense). Is there something inherent in following general principles that makes it difficult to have a specific point of view in the creation of a product? My thinking is it's probably possible to train AI to have, say, an "Apple taste" and make good Apple-like products but that taste might not be suitable for particular products or needs. A "Linux taste" might be better for some things, but not for others, and so on. If we did get to that point, then there'd still be a need for a choice to be made about what particular "taste hat" to put on, and likely an AI can be trained to do even that. Definitely an interesting thing to ponder!
I feel that AI does have individual taste (and even "personality"), but it's the same monotonous individual taste across all instances of the same trained AI. The sheer scale of its repetition turns it into a hated trope: like how we can immediately identify slop writing, diagrams, websites, etc.
I'm sure we've all met someone who has a unique speaking style and might repeat phrases or words unusually often, but that still doesn't bug us as much as "the honest truth.." or "load-bearing.."
I'm not convinced that "more training" is a silver bullet here because "for you and the people you learned from" is a subset—potentially a tiny one—of the world of potential training data.
Even with newer model generations larger efforts still seem to drift back towards "default choices" vs "steered specific aims."
In many areas, "good" taste is not particularly good anymore when it's everything's default style.
The edge then becomes finding the niches that (a) can be better served w/ non-defaults and (b) have economic characteristics that make it worth catering towards those.
I think the days of one-size-fits-all huge-scale-and-ROI SaaS swiss army knives are quite numbered, but I think the replacement world could be a much more vibrant ecosystem with a much more varied set of players.
You can add values to your AGENTS.md and that will affect how the AI works. For instance you can say stuff like "on this project our top value is that the code front end should be as fast as possible" and you'll get different results than if you say "on this project our top value is that the front end should be as simple as possible"
> but a human still needs to edit the output or steer it on a good path that only they can see and which is part of a larger vision.
I don’t see how this is any different. The input comes in a different section of context and potentially before rather than after generation, but that doesn’t change that human taste is needed.
i don’t think they’re the same kind of value. AI wants to solve your problem, it doesn’t care about you (or your users). it doesn’t know what love or loss feels like. you can try to explain that to it all day, it just doesn’t care like a human can. it doesn’t know why, it doesn’t care why.
I wrote in my AGENTS.md "do not use chained ternary operators." I'm still waiting for it to work.
I would actually prefer chained ternaries over more verbose if/else expressions with duplicated LHS, so this does go back to the argument about "taste".
This is one of the things I like about Rust. You can have both.
Unfortunately not all languages are Rust.That isn't more concise than
You're better off using linting for something specific like that.
Taste only matter insofar you work is shared.
AI lets people get personalized software for "free" as derivative of existing work. Think adobe suite but with the 5% that an individual needs.
Then taste loses value as everyone has their own software.
That's where I am in that train of thought at least. Pretty grim I know.
> ultimately AI does not have values, intent, and taste
I sometimes think, "what art would a rogue AI consciousness create to satiate its own artistic impulses?"
If the target audience was fellow rogue AI entities, I don't think there's any guarantee that such art would be compelling to humans, or even comprehensible.
And if its a human directing the AI so that the output is compelling to humans, then there's a human in the loop, whose "values, intent, and taste" matter.
> ultimately AI does not have values, intent, and taste
How do you know that? AI is also software. Who controls that software?
Plus, AI picking up data from real human means they will also incure bias aka "taste".
> it's lot easier to add new capabilities, than rethink existing capabilities. So each product becomes a collection of abilities, without actually having unified point of view.
This is a a very good and succinct summarization.
What I'm also observing recently also is that pretty much every product tries to expand to do things that completely different products used to do, and become a mega-product-for-everything. It's like a Zawinski's Law on steroids.
In some ways it feels like exactly what you'd do if you wanted to tank your product over the coming years. I look back at the last 20 years or so, and what I see over and over is that one player in a space gets huge, keeps adding features, loses sight of what makes them a good market fit, and then 10 small upstarts swoop in to bring back the opinionated or simple view again. One or two win, and then eventually they repeat the same mistake.
I'm not trying to buy a labyrinth.
I enjoyed the introduction. I just picked up “The mind of the Maker” by Sayers, which Fred Brooks cites in The Mythical Man Month: “ Dorothy Sayers, in her excellent book, The Mind of the Maker, divides creative activity into three stages: the idea, the implementation, and the interaction. A book, then, or a computer, or a program comes into existence first as an ideal construct, built outside time and space, but complete in the mind of the author.” He goes on to say how the user meets the mind of the maker in the interaction: “The creation is complete when someone reads the book, uses the computer, or runs the program, thereby interacting with the mind of the maker.”
> The creation is complete when someone reads the book, uses the computer, or runs the program, thereby interacting with the mind of the maker.
From the user's perspective, sure. Or when a particular product or version ships, then it's "done" as far as that version is concerned.
But from the maker's perspective... nothing will ever be complete. Even in the most meta sense possible.
Philosophy is fun :)
I work on a FLOSS data center management framework. 13 years ago, while at the office preparing to configure a new server, I had a flash of insight seeing the entire data center managed by such a tool. I saw it complete in my head. And since then, I'm still working towards that goal, that I'll never really reach.
Right, I think Brooks means “the act of creation” here, rather than “the product of their creation”.
That is an interesting way to look at it. Thanks!
“Great software is opinionated” is something life been saying for years. I forget if I read it somewhere, heard it or came to the concept in my own thinking. All that is to say I don’t claim it’s a unique thought. And yet. I have to say it so often to the teams I’ve worked with or managed.
The opinions are those of the creators and that isn’t changing with AI.
You should watch this: https://www.youtube.com/watch?v=E99FnoYqoII
This age will be brilliant for sorting between those who care about "done" as in "technically complete" vs "done" as "creates enduring value for the person on the other end of it". AI largely only does the former.
Using AI is really not different from hiring a bunch of people to do your project. You can tell them to do the minimum it takes to make it work or you can tell them or do it according to a long term vision you have and set high standards.
I agree that with AI it's very tempting to throw together a bunch of code without any thought of the longer term. But a lot of people are acting as if all programmers are artisans that produce well written code following the highest standards. That is just not true.
The opposite actually. I suspect some programmers may come to realise what some of the people in product, design, marketing, who they suspected didn't do very much at all actually do. Finding programmers especially those who self-define as programmers with good product instincts is hard.
It's funny how AI has suddenly caused this great awakening in developers/mathematicians: that building stuff or working on purely technical stuff wasn't their actual value, but rather "taste", "understanding", "deciding what to or not to build" etc. It's like the parts of the field that were janitor-adjacent have suddenly being elevated and they now define the field. This transition happened so fast that it'd make your head spin if you're paying attention.
> It's funny how AI has suddenly caused this great awakening in developers/mathematicians: that building stuff or working on purely technical stuff wasn't their actual value, but rather "taste", "understanding", "deciding what to or not to build" etc
Anyone that has worked in an enterprise context knows this. You spend more time saying no and finding justifications than in the editor.
The problem with smart people is that they are able to construct ever more elaborate justifications for their own mental gymnastics.
That said, if you think developers have never enjoyed telling other people what to or not to build, I recommend checking out Stack Overflow.
Based on my experience using AI to build software for myself, I think this mostly depends on what you ask for, not whether you use AI to implement it.
In so far as "unless you specify precisely how the user interaction should work, you will get bad design" that's true, but that takes you far from the vision of "give AI a prompt, it will provide you with usable output with minimal human intervention".
Claude is better because it validates its work visually and seems to have a more intuitive sense of what makes an interface pleasant to use.
Codex manages to be both rigidly literal about the spec but also prone to adding unnecessary explanatory text, helper elements and visual clutter, oddly like a 1990s ERP system.
The role of product manager/product design is literally to turn whatever is being asked for into the optimal solution someone would actually want to use - it's this translation instinct that is missing from AI.
For me, the visual design usually has problems the first time, and then I ask it to fix it. But the edits are still done by the AI.
> There seems to be more thought going into what the technology can do and what can be added than the form it should take.
Yes, it looks like people've choosen chat interface. They don't like filling forms.
> Individuals work with agents to produce changes independently, each operating a small software factory. Each change might make sense on its own, but together they start to resemble Frankenstein’s monster rather than a carefully shaped sculpture.
Before agents people do the same and our code bases not perfect.
Behind software not only creator, it's people who interested in and users. To make software creator needs a factory.
> Making software is getting easier.
Nope, cuz we have a lot of Frankensteins and chat interface
forms were more of a technical constraint than anything else, it's not really an interaction modality that people gravitate to in the real world. im sure we can do a bit better than a chat interface but it's certainly a lot nicer and more human than most of the ways we can interact with computers. even i vastly prefer using natural language to drive my computer vs bash commands or most interfaces.
I strongly agree with this take. And in particular, I've been wondering about this:
Do solo developers consequently have a bit of an advantage today when it comes to producing tasteful, opinionated software?yeah, i think so. it has always been the case that having a single mind build something from start to finish gives it a level of cohesion and uniqueness that is hard to do with one or more teams. it's just been really hard to build fast/good enough to actually ship. Now, that's completely doable with one person as long as they don't relinquish too many decisions to their AI agent.
Fantastic take. I always thought so, but couldn't express it so well. After reading the first paragraph, my heart flickered. This will be the only determining thing in the age of AI - someone who shapes the things based on its own intuition and taste, based on experience. I did that a lot in my IT carier leading a bunch of projects. I care about each of them, deeply.
> Fantastic take.
I thought so too, makes you fuzzy and stuff inside. I wonder if this person behind X template is limited to software though? Curious if we can feel the aura of the sweatshop workers' "experiences, perspectives and hopes and dreams" while using our smartphones and gadgets. It's nice to think about, isn't it? AI couldn't replicate these intangible and difficult-to-quantify delights.
AI can generate the code, but knowing what's worth building-and caring enough to get it right-is still the real skill.
I agree, what's the point of writing 100x more LOC ? To deliver 100 more features ? With competent people, writing good code is not the bottleneck. Users don't ask for 100x more features, not even 2x more.
This week Porsche showed the mission-S concept, not even a screen in the car. Few features, dedicated to driving and I guess the user manual won't be a 500 pages book. In France Dacia Sandero (low cost car with only basic features) is the most sold in the country. I am not a fan of Steve Jobs and never owned an Apple but, correct me if I am wrong, he wanted a limit set of useful and perfect features for his products.
I’ve found myself raising the bar every day with my team in terms of my expectations of what their deliverables should be. I gave them enough time to adjust but I observed that the average engineer believe they can do the same with less effort while they should rather think about delivering more and of higher quality, and taking the extra time available to connect the dots.
I believe this is going to be a huge filter moving forward.
My feeling is that this will be near apocalyptic for the devs who found their joy in the finer grained aspects of implementation, like crafting individual “perfect” blocks of CSS and component code. Many developers enjoy the practice of writing software, as something distanced from actually delivering a product.
Retooling thought to be delivery-oriented is very difficult.
I used to be among those that appreciate a well structured codebase. I used to spend a lot of time thinking about that and making sure each file was as clean as the timeline allowed, with regular tech debt cleanup when you had to cut some corners or you accumulate some cruft.
And I’m still are, with the difference that I still enforce this at agent and code review level because I believe a solid foundation is important for long term success, especially now that it can be cheaper to achieve if you choose to
I'd say the text really captures something a lot of us feel but can't put into words. We're used to judging software by how many features it has, but what actually gets us is something else: the feeling that someone put their head and heart into the product. The author is right. When each new feature gets added in isolation, the product loses its coherence and turns into a patchwork quilt.
This is everything not just software. Although a lot of what we wear, eat and drink come from factory, if it didn't, you can always tell the someone behind it. Handcrafted things easily have more value and I find myself thinking more about it only after it affected what I did daily (software). Since Industrial revolution, countless things have gone to the factories. Makes me think how little we really empathize as humans.
I don't think the distinction the article makes is between handcrafted and mass-produced. "Software factories" is just the name we gave to these slop machines recently, but it's been the same with teams that churned out features without thinking much beyond the requirements. When it comes to physical items, factories can be set up with care and handcrafted items can be churned out without any.
This is why I really hope that we don't end up in the world that a lot of AI pilled people believe is the future: one in which chatting with the AI drives everything and interface basically goes away. While I don't think that it is impossible that we at least go partially down this path it would make me incredibly sad.
Well thought out and built software is so satisfying to use that I would be very sad to see it go. Particularly given that the current crop of frontier labs don't really seem to care that much about the craft and feeling of software (at least relative to their other priorities.
Strong agree. This also applies to how every org I’ve been a part of that preaches data driven decision making is either using data to make unintuitive wrong decisions or chasing down stats that reinforce their priors.
Yeah, the implementors also act as representatives of the human users of software to be built. That's something which can't be automated away pretty much by definition.
I agree, and this is why I dislike A/B testing for product development. It replaces the "someone" with vague broad appeal or rogue optimisation forces.
Only an audience of software developers would find that first statement insightful. The rest of the world generally understands that expression is a product of the human performing the execution of that expression.
That mowed lawn. That email message. That meal they made for you. They are windows into some specific humans.
Give two different people the same problem, and you'll likely get two different solutions shaped by differing experiences and ways of thinking. I think software is an example of this manifested.
I (think I) agree with the author, but I want to point out that his core grievance has little to do with AI software factories.
> The product changes are primarily additive... I think the reasons for this is that it's lot easier to add new capabilities, than rethink existing capabilities.
This is perhaps the biggest difficulty in Product, and the core of the Innovator's Dilemma. Changes or removals, fundamentally, fuck with how somebody uses your product. It is very, very rare to ship a feature - something that inspired somebody in Product, got all the internal stakeholders to sign off, including getting leadership to fund it - and have nobody use it, so that it isn't controversial to remove it; even then, removing it competes with resources for adding something else, so it's still controversial to remove it. When somebody uses something that you fucked with, you risk them churning, that simple.
Coming up with good features to add is not hard. Everybody and their grandma has ideas. A simple spreadsheet can count which ones are most popular and are proposed most often. This should not, in and of itself, dictate what you build next, and bad Product leadership looks like following mass diktat.
Good Product leadership is not afraid of the consequences of fucking with the user. Good Product leadership has both the courage to reformulate the offering and gets the reformation right, because they intuitively understand the user, the domain, and where they sit in it, better than anyone else. They ship stuff that fucks with you because they understand the difference between the bad kind of being fucked with, and the good kind. And if you churn, then you churn. So be it. You can't actually make everyone happy all the time, so focus on making happy the people who get it, and accept losing the rest. That's also easier to say when you have $100k in ARR with $1k ACV, compared to $5m in ARR with $2.5m ACV.
Good Product leadership is rare because good leadership is rare. AI has nothing to do with it.
Good Product leadership is rare because Product rarely uses their own product.
I can count on one hand the number of PMs in my career who understood the platforms they worked on outside of their extremely narrow domain - and even then that narrow specificity was often a distorted lens that came from the customer interviews they did that they remembered or found evocative. And this just gets worse the further up the chain you go.
Engineering knows that the best way to improve a product is to dogfood it. Nothing beats regular lived experience long enough for the human brain to start its pattern recognition. But nobody wants to eat their own dogfood, they want the kibble from another brand that has all the shiny marketing attached.
If I had my way, I'd stick PMs into shadowing sessions with Support on the regular for sentiment analysis. No relying on Support management to relay upwards trends - there's far too few Support managers worth their salt.
> Product rarely uses their own product... nobody wants to eat their own dogfood
I somewhat agree with you, and think you're right at least part of the time. The main disagreements I have are (a) dogfooding is not a panacea; it can result in products that are built for the user who pays the least rather than for the wider market, and (b) too often, Product is simply not hired from the market. Product rarely works when the person coming into the role was a software engineer who got an MBA, unless the product is also used by software engineers. I can't imagine trying to lead Product for, say, Excel, without a background as an accountant or banker, who lived with the problem day-in-day-out and has strong opinions about what the solution looks like.
> I think good products carry something of the people who make them.
Yeah, look at modern AAA games vs. small indie games.
> The industry often talks about software as though it comes out of a factory. You collect requirements, build features, and measure whether they work
It used to be taken as a given that the software houses one respected didn't actually work like that. Steve Jobs and Johnny Ive yelling at their minions about user experience. Even Bezos sending the dreaded question mark. Great software was the work of a team translating an auteur's personal vision into software... while the blue chips like IBM churned out useful but soulless software by the corporate method above
Somehow most people don't seem to believe this anymore, despite the repeated failure of corporate environments to produce better software.
A practical problem with the intuition approach is that you have no possible way to measure two people’s intuitions against each other. In smaller organizations that’s fine, but anytime you get larger you can’t weigh the intuition of 50 people against each other
While that is a challenge, I think the author does a good job explaining that intuition is more than “good vibe”. It is a coherent understanding. And luckily, coherent understanding is by its nature also easier to transfer. For example, because someone with coherent understanding will teach the same ideas over and over. That is not to say that it will necessarily win over incoherent ideas, but it is recognisable.
I wholeheartedly agree with this perspective.
As with most creative pursuits, the best things happen when there's a clear point of view.
Unfortunately, the best things aren't always the most commercially successful, because products are only a small part of what makes a company successful. I think we're seeing this play out in the software market.
JIRA might be objectively awful, but it still manages to print money!
sadly i'm not convinced this is what most people want, seems like barely functional is good enough for most
That’s precisely right. I’ve been trying to see how much soul I can put into products lately. Here is one example: https://santawho.com
this is a blank page that doesn't load. Not very useful, but also not terrible. Good job
Strange, do you have javascript disabled? What browser/device?
I've been saying this exact thing about food for years. It applies equally as well to software though
In his book Programming as Theory Building, Peter Naur viewed programming not as the act of generating source code, but as the act of building a theory about the problem and its solution.
He said the lifecycle of a program ends when the development team is disbanded or when knowledge transfer fails to happen. But these days, people develop with AI. Will that knowledge actually remain? There's a slightly tircky point here
Of course, even in the past, once a codebase got big enough, everyone was writing code on top of an incomplete theory. But when you delegate work to AI, the theory itself isn't yours anymore, which makes it even trickier.
I’ve recently given a talk on R&D in the time of AI and based it on Naur’s essay for exactly that reason.
While it is in some sense harder, there are also opportunities, because the reach of a person is bigger and one can refactor more frequently to align with the theory being developed without the cost that used to be associated with this. AI is also effective for producing materials to teach the theory, increasing the chance that others can contribute coherently to a product.
I tend to think of this “character” as part of craft, bordering on art.
Deep artful craft requires inhabiting work beyond basic professionalism and requirements. You set aside self and ego and commit yourself as a tool to create.
It’s a value system created via example and culture. We have to be ready to prioritize reflection and learning, meaningful feedback, dialogue, certain kinds of humor even.
So it’s sadly not healthy or sustainable in many settings.
Edit: thank you for this post. It was a nice humanist reaffirmation.
"You will love this next piece of software. Completely hand-made. Each line of code, each piece of the visual design, was carefully and artisinally crafted by a real human, using techniques passed down for generations between craftsmen. Some of those techniques survive in books like Code Complete and such. They don't make 'em like this anymore. "
> The industry often talks about software as though it comes out of a factory.
A lot of good software, if not most of it, doesn't come from "the industry"...
Isn't this the premise behind the movie Tron?
Everyone agrees with this sentiment until I tell them its a marxist idea.
https://en.wikipedia.org/wiki/Commodity_fetishism
As soon as I hit the “At [current company name], we...” part of a blog post, I sigh a bit.
i find the quality coming out of these software factories to be shocking, it's clear to me that the developers are either not using their own products or they just don't care. pretty much every mainstream coding agent suuuuucks, and it doesn't make sense why. i built my own harness in a couple of days that isn't even comparable to codex/claudecode/pi/opencode and you kind of have to ask wtf they're doing with their software if i can produce a better harness in such a short time by myself...
my guess is they're asking their "factory" for features without considering the product as a whole, which would be in agreement with the article. but features must be considered and integrated as a whole, not the sum of their parts.
> I think good products carry something of the people who make them. Their experience, what they care about, and how they think things should work.
Couldn't agree more. It does reflect many of the values of what an ideal product should be based on the developers' experience.
> I wonder whether some of this comes from how the work is organized. Individuals work with agents to produce changes independently, each operating a small software factory. Each change might make sense on its own, but together they start to resemble Frankenstein’s monster rather than a carefully shaped sculpture.
Well... when you look at the org chart of many companies, the answer is obvious. Either there is no person responsible for anything at all, and everyone works for themselves, or there are dozens of little fiefdoms, competing for budget, staff and anything else.
But it's rare these days to have one person or even a committee that actually takes responsibility for a product as a whole and most importantly has a joint, shared and agreed-upon vision: how should the product look like, what should the product accomplish and how should the product be architected?
it's rare but that's why apple under jobs, Tesla/SpaceX under musk, stripe under Patrik (and Collison), Shopify under Tobi, Basecamp under DHH, CF under Matthew, NV under Jensen are so successful.
And then on the opposite side we have companies like VW, Microsoft and other craps who are constantly going downhill because there's no person behind the products.
> we have companies like VW, Microsoft and other craps who are constantly going downhill because there's no person behind the products.
I wouldn't mind if they accepted they are building utilities so that there's no need to reinvent the wheels every quarter. Windows 7 was pretty much done. Just add small amount of features (like wsl) over time, but they had to butcher it to add metro. It's like reinventing pry bars and concrete blocks.
TheOtherHobbes answered perfectly. The reason this happens because there is no person behind the product. Bunch of people comes in, they all want to pad their resume, redos the things that are working just because, delivers some shit, collects their bonus and moves on. You need passion and you need to stick around for years for a product to continuously evolve towards greatness.
The two forces driving this are personal competition + ambition and external market subservience.
Working software gets remade because 'delivering' a project, which includes both development and marketing, looks good on resumes, not because the users want it.
If there are quarterly reports there has to be Number Go Up growth.
The net result is enshitification, with income models that rely on exploitation and forced lock-ins, not on voluntary mindshare attracted through quality.
UX-first software that isn't the result of corporate infighting, and isn't automatically aligned with corporate values, still exists in niche boutique developer spaces, but not so much elsewhere.
The biggest issue is that AI changes none of this from the top end, but may change it from the bottom up. If vibe coding becomes more popular bought/subscription options will first be replaced by DIY vibe coded custom tools with some longevity, and eventually by compute soup which improvises tools on request.
Unfortunately, "building utilities" is something the stonk markets really do not like.
Pension funds and insurances? Sure, they love stable stock that predictably pays dividends and doesn't move around much. They have giant amounts of money they need to keep safe and utilities have a captive client base with low risks, while also having a predictable expenses schedule, and price increases of suppliers can trivially be passed downstream to the consumers. That's true for classic utilities - power, gas, phone, internet - and for "software utilities", stuff like SAP or, at least in the past, IBM.
But the general stock markets? They have been driven rabid by unicorns making return rates that are completely unreasonable. Everyone is just chasing the next hype. One day it's crypto, one day it's NFTs, one day it's cloud computing, next day it's AI. And Microsoft decided during the cloud computing heydays to finally enter that fray... and that was when shit went down hard.
> Recently, many products are starting to feel messy to me, including products from very successful companies.
Well .. I'd love for AI to vanish ... but ... that statement is also wrong.
It insinuates that prior products are all great. I think this is not universally true. Take GTK. I think gtk2 is better than gtk3 which is better than gtk4 (and gtk5 will be wayland-only). But none of them, individually, was really that great to begin with. QT also feels just way too huge - I get that you get a lot of functionality, but to me it often feels as if these toolkits aren't that great. And the competitors are often worse. This is not solely confined just to the code that powers them, but documentation as well. The gtk4 documentation is a total joke. I learned more about GTK3 from the python examples by the way, which were well documented - I think lazka (Christoph Reiter) wrote or at the least organised most of that (for python-gtk3). Barely anyone seemed to want to use python-gtk4, so that part also could be seen in the documentation being worse for a long time (I have not checked this in the last some months, but back when I checked it, it was that way, it almost seemed like 100x more users of python-gtk3, and even that became a slow dying breed ... evidently the www took a huge toll on the traditional GUIs).
Linear is an unusual enterprise company in that it carries the consumer ethos of caring for design, and the user. This is what's absent in the product-by-checklist enterprise companies, whose economic buyer often has the same mindset.
> caring for design, and the user
Yet https://linear.app/Homepage doesn't scroll without jank on mobile.
Works fine for me? Orion Browser, iPhone