Xerox Parc is one of my favorite anecdotes. However it's not for UI, it's for how major companies like Xerox kill innovation by trying to make it fit to the form factor of their business.

A mouse and screen with a folder system was a way of humanizing the command line. The funny thing is as a developer, if I know what I want to do on the CLI it's faster than using a mouse and keyboard, because it's essentially shortening the length of time it takes me to communicate a complex idea to a computer and have it execute that.

The chat interface sucks, but it is pretty close to the ideal way of interacting with a computer. Talk to it. It shows you something. Talk to it again. That paradigm is pretty close to how we interact with humans. Talking and showing.

The reason why the UI sucks for AI right now is because AI sucks.

You shouldn't have to manage it as much as you do. But we have to manage it delivers about 90% of what it promises with the missing 10% being critically important.

It's extremely hard to create human bonds with a dementia patient. It's hard to hire an engineer that can't do math.

Solving memory for AI as well as non-stochastic output will leapfrog all of the problems most AI engineers are dealing with right now.

I generally build stuff with AI for 3 reasons: It solves a real problem right now, it's adding to some fundamental problem around the discipline, it's fun.

AI harnesses are pretty big right now, but they will likely get leapfrogged by a better algorithm. At the end of the day the best "harness" for AI is just trust.

Do we really want a complex harness for AI to manage it in a more time consuming way, or do we want to just trust that it can follow instructions and manage complexity on it's own.

The competitive issue around this is that everyone is working on AI right now, so it's realistic to expect a business landscape where harnesses and fundamental shifts in AI capability take turns leapfrogging each other. Temporary solve to current limitations. Paradigm shift in model behavior. It's behaving similarly to moore's law, but on a much faster scale that is harder to measure discretely.

In the spirit of Xerox Parc, I think the bigger innovation isn't reinventing a few things that we already have such as an OS and a chat interface and file management. But rather looking at things the same way those engineers did, which is what does the future of human interactions with machines look like.

If my computer actually had a brain, I would just talk to it, and it would show me things. It might 3D print something so I could try it in the real world. It might show me some things I could have shipped to my house. It might design a UI for me, pull some data etc. I wouldn't have to manage it because it would have access to a lot of fundamental business problems and solutions.

The issue with that way of interacting with computers is that's centralizing knowledge inside of a computer. Doing that erodes competitive business advantage. The two edges of the political spectrum where that works is monopolistic business practices and communism.

And that's actually what you're seeing a gigantic war over right now in AI. China pushing open weight models for free to undercut US AI dominance which requires an insane capital expenditure to keep afloat.

Realistically, I don't think the answer to a lot of these issues is to build a business. I think a lot of businesses built around AI will become irrelevant in months. Open claw is something that 10 years ago would have become a unicorn company. But it got eclipsed by a flood of agent harnesses. And Open claw itself was a leap frog of cursor which was less than a year old. Cursor itself now a part of SpaceX's trillion dollar play.

I just don't see software as a service being anywhere close to as lucrative as it used to be.

It's way more realistic to assume that China is going to undercut US AI prices until they find a way to run complex models on small amounts of compute, eventually wiping a significant amount of value from the US market. At the same time, a lot of the models like OpenAI and Deepseek will be using user input as training data to develop future projects.

It's hard to say when that will happen, but there's a realistic future where AI just cobbles together scalable performant SaaS in rust while running on a micro PC.

The bigger use problem at that point is that most people are really bad at making products. They're really bad at identifying problems, solutions, and use cases for things. Most people end up building one off solutions for temporary problems. Which is fair, because most people aren't engineers or product designers.

I suppose the biggest question in AI dev right now is something like: how can you in any way, quickly tell what you just did with an AI agent in a way that's visual and easy to understand. People call AI stuff slop because it spits out a bunch of output and people can't easily tell what the output is or if it does what it's supposed to. That's a pretty big problem.

It looks like you're building for folks who don't want to dive super deep into AI? In that case I'd gear your product more towards a "thing doer" rather than a complex thing you can crack open and get under the hood.

You generally solve that problem by doing the Amazon method. Start by selling books. Move to selling everything.

So the question would be, what's your Xerox Parc level belief on humans and computers and AI and would would be the first problem you'd solve using that paradigm.

Personally I feel like it's way more efficient to start building social groups right now instead of companies and products, because a lot of what we did on the scale of web 2.0 is just going to be trivial.