Yesterday I watched “Soul” to remind myself that maybe the purpose of life isn’t always finding some big purpose. It’s simply being present enough to enjoy being alive.
Kid Cudi will play Jean-Michel Basquiat in a self-written and directed film, out 2027.
"This film will be a love letter to Jean, the 80s and NY city," Cudi wrote via IG.
Someone behind the software
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. You might not know who those people are, but you can feel their perspective in the product.
The industry often talks about software as though it comes out of a factory. You collect requirements, build features, and measure whether they work. Follow the process and you should get a good result. Now we're talking automating this whole pipeline with agents.
But two teams can talk to similar customers, have access to the same technology, and make very different things. The difference comes from how they understand what they see and the style they go about building it. The founder background or company DNA also shapes this a lot.
At Linear, we have always valued intuition over process or data. I think people sometimes understand that as making decisions based on personal preference, without much thought or evidence. What we mean by it that your intuition develops through experience and understanding. You work on something, talk to customers, make mistakes, and learn what to pay attention to. The intuition is your point of view on something, and forcing to use your judgment, not hide behind faceless data.
Before we launched, we talked to people across companies and roles about how they worked. We had our own frustrations with this type software, but those conversations helped us understand what mattered beyond our own experience. Our perspective got better after those conversations.
So eventually the products develops a character through what its makers pay attention to, what they decide not to do and what they keep working on after it technically works. I sometimes think of this as the soul of a product. You feel that someone cares about how the whole thing comes together.
A feature can work perfectly well on its own and still make the product worse. Recognizing that requires some belief about what the product should be. Someone has to make the call, then stay close enough to customers to see whether they were right.
Recently, many products are starting to feel messy to me, including products from very successful companies. There seems to be more thought going into what the technology can do and what can be added than the form it should take. The product changes are primarily additive, not improving the core problem.
I think the reasons for this is that 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.
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.
Without the shared perspective,
soul, or thought, the product becomes an average of all those outputs. The choices that once gave it character are being diluted by day. More things work, but it becomes harder to feel someone or even something behind them.
Making software is getting easier. I hope that gives people more room to develop a perspective and follow it further. To understand a problem deeply and keep shaping an answer until the pieces belong together.
I want to feel the creator behind the software, not the factories.
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Some AI industry leaders are predicting white-collar bloodbaths.
Even the most inspirational advice to new graduates lands like a Band-Aid on a bullet wound.
Some thoughts on new grads, and finding a job in the AI wave:
angel thesis these days (advice I give to vc friends, and follow when I get a free moment from being heads down building!), jotted post 🏃:
- where does memory become a durable moat as personalization effects become the new network effects? (even amidst the endless data connectors that neutralize the advantage of normal data). relevant for consumer and the enterprise. also, what new tools will manage memory across different LLMs and enable portability?
- for enterprise products, who can leverage or build a better permissioning layer of the enterprise (and the incumbents that own an irreplaceable permissioning layer - who can see what with granularity and reliability - have a moat that will fend off the startups!)
- for both consumer and enterprise, who has or is building (or can transcend) defensible social and professional graphs? the relevance of search and agent recommendations will be determined by graph data (who you work with most often on particular topics, friends and relationships across different contexts, etc).
- interface innovations that transcend the skeuomorphic phase of AI. if the personified “chat phase” of AI is akin to the early days of iOS when the contact book had stitching etc, who is building entirely different interfaces that will make 1:1 chat look patronizing in retrospect?
- brands and mechanisms that signal human ingenuity and the investment of human time and energy in digital experiences. I believe that when anything becomes commoditized, we seek the more scarce and meaning-infused version of that thing, typically signaled by a brand. as software and content can be made by anyone, I anticipate an era of luxury software, world class brands for content, etc…
thoughts?
feedback/additions welcome.
Had the opportunity to contribute ideas to one of my favorite publications — @every 💌
We’ve got to start designing everything with agents in mind.
Because in addition to millions of humans, your customers will soon be billions of AIs that see the world in a totally different way.
Art is a translation problem. The role of an artist is to experience, perceive, and observe the world and then find a medium through which they can communicate or translate a point of view to a broad audience. The goal is to create something others can not only see but deeply understand. This requires two things: a) an interesting point of view to communicate — an insight, feeling, or understanding that adds something meaningful to our collective experience, and b) the technical ability to shape that insight into a form others can access. You need to know how to translate what's in your head for the rest of the world to understand.
That's art: a + b.
Craft focuses on technical execution. Art uses craft as a vehicle for translating a message. When the medium lacks a point of view, it matters less. Consider the distinctions: poetry versus sentences, film versus video, painting versus pictures, dance versus movement. The difference lies in the presence of a clear point of view—a perspective, something worth translating for others to understand.
Generative models and their impact on art making is that they can radically help with this translation problem. A new way to bridge the gap between vision and execution. AI can't help with how you see and experience the world. But it can aid you on translating it.
I guess I recommend: 1) having a point of view that's interesting and 2) know how to translate it into something meaningful. a+b.
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I've spent the last two days playing with Replit and my mind is blown 🤯
It reminds me of the first time I used WebFlow, but x1000.
Any time I've had an app idea, I've had to hire a developer.
Now I have a free AI developer. Sure, he's junior, but we can muddle through together and build some basic stuff.
It's crazy to project this forward and imagine how crazy it's going to be in 3-5 years. So much creativity is going to be unleashed by tools like this.