These days projects at @linear often start with 100+ customer requests and feedback. This is all automatically collected from sales and other customer interactions with Loops.
Skills are now a valuable form of software, like Emil's world-class design eng work. Projects like 𝚙𝚐𝚋𝚘𝚝, 𝚔𝚗𝚒𝚙, 𝚞𝚗𝚕𝚒𝚐𝚑𝚝𝚑𝚘𝚞𝚜𝚎 create amazing AI engineering loops.
Omarchy is not going to adopt a formal Code of Conduct because those turned out to be struggle-session processes in the last turning. But we are going to play nice. We're going to be courteous, professional, and composed in our direct interactions with users, competitors, and even haters. Because that's what's going to pave the path to the win.
But, simply just having your loops build everything without having some guardrails around the blast radius without having guardrails around how you think about quality, I think is a recipe for disaster.
So if you design call it loop, call it graph, call it workflow, it's kind of all the same. If you design something that gets a trigger or gets an input and does something for you and maybe there's a decision in the way, boom, there's your graph.
And I think there's a lot of room in a lot of domains for much faster validation models, possibly learned valu validation models that can uh you know get you a a approximation to the true answer much much more rapidly. And that changes how those experimental loops can be thought of and how quickly you can go around those loops.
I get really nervous about having different design languages or different types of user interactions and shipping Frankensteins, basically. So, designers need to then be the people we're hiring again for design systems thinking.
if you want to do loops engineering, you should build one loop at a time and you should keep them small and contained. Basically, I think everything except stop reading the code is really good advice.
You'll notice what I said was not use loops to ship the features that users want. We use loops to actually improve the codebase quality and we read all the code because we care about how it's architected and we care not just about the system architecture but what I would call the program design
So I think the the thing I'm most excited is actually like what we call like iterated loops or like slow loops where we basically have a cron job. We have the loop the the the structure of the loop is really easy. It's like run this llinter fix one thing commit and push and then we run that every night in our GitHub actions and we wake up every morning to one PR that makes the codebase a little bit better.
I think a lot of the things that people might say that like oh, it was a waste of time to learn this subject cuz I didn't actually use like those details on the job. I think that's a very wrong way to think about it. And I think that's what a lot of people are doing now with AI. Like hey, what what if I'm not going to be writing for a loops a couple years from now. Um I don't think those things are a waste of time.
we went from infrastructure is code to infrastructure is data and infrastructure is code is like if this do that um bring in this module for loops all this stuff and Kubernetes is like no no no you have to specify exactly the containers you want how much memory that they need and then we have the status field to tell you if they were running or not
one of the things that I noticed about computers and I think today with mobile phones, uh is that in many ways they isolate us from one another, right? They actually take us out of our social interactions.
That's the opening of "The Green Fields of the Mind," collected in this slim, wonderful volume. Recommended if you like thinking about America, baseball, and The Odyssey.
We should knock on more doors. We should do more in person. All the data I've ever collected shows everything closes at a higher rate if you go in person.
But even more important than efficiency, designed experiments can inform about causality, which is very difficult to determine from collected observed data.
The Weight is Mellia Mendes's award-winning webcomic, now collected in a massive, beautifully made graphic novel from Drawn & Quarterly. It will tear your heart out, it will send you to a dreamy world of pastoral utopianism, then it will tear your heart out.
My model is that research requires a mix of skills. The day-to-day coding and execution is crucial. But there's also a set of harder-to-learn conceptual skills, collectively called research taste. These skills take a long time to gain because they have poor feedback loops, but they take very little time to use.
it has to be consolidated because to basically make the money back on the pre-training and post-training process you need relatively few players that are collecting taxes you know from all the players on top or you just can't make the the math work.
I think the lesson from all of that is that humans talking to humans and being together in the real world or a virtual world, is a naturally empathetic medium, which naturally leads to bonding, and though conflict sometimes occurs, it's just generally so much more promoting of our social norms and good interactions between people and positivity promoting.
The key thing is, and this applies to any survey methodology, if you're going to change the method of surveying, all of your old numbers are invalidated. So, it's just a new baseline going forwards.
until there are feedback loops of open source AI, it seems like mostly an ideological mission. People like Mark Zuckerberg, which is like America needs this and I agree with him, but in the time where the motivation ideologically is high, we need to capitalize and build this ecosystem around, what benefits do you get from seeing the language model data?
What amazes me about these interactions is not just that Claude could help me solve the problems, but how it walked me through the process, explaining each step.
tech barons are ordinary mediocrities, no better and no worse than the monopolists that preceded them, and any differences come down to affordances in technology and regulation, not an especial wicked brilliance.
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