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.”
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.
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.
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.
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.
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.
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.
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!
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.
> 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.
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.
"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. "
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 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.
> 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.
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.
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.
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.
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!
Couldn't agree more. It does reflect many of the values of what an ideal product should be based on the developers' experience.
Yet https://linear.app/Homepage doesn't scroll without jank on mobile.
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?
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.
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.
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.