More directly, because I have a long term memory and do not have fundamental issues differentiating fact from fiction. Just because SOTA models know more trivia than I do doesn’t mean they’re nearly as intelligent in the thirty other ways humans are. They are a tool in your toolbelt. You use them for the things they make easier.

Weekend me before LLMs: Maybe I’ll chip away at that dependency injection library I’ve been working on. If I spend most of the day I could improve the user facing test framework.

Weekend me after LLMs: Let’s continue work to get Claude Code running in WebXR on a Quest 3 with app architecture modeled as a 3d construct. We’ve got deepgram hooked up for a better voice to text experience, but giving Claude a voice was a waste of time. Claude, continue to teach me about 3d rendering as related to our current challenges matching the fidelity of the built in browser.

They should pivot their cloud offerings toward research labs.

“Here’s 10 different clusters of analog compute you can rent for half the price of building it out yourselves. It doesn’t map to the math you’re using right now, but it looks much more like a human brain. Have fun!”

We do not yet have the next generation systems that will manage AI creation and maintenance of systems.

Humans have been making spaghetti code systems and maintaining them poorly for years. Best practices developed… eventually. But certainly not in the 70s and 80s. Spaghetti was the norm for quite some time.

The development paradigm has changed. Forever. You can’t expect yesterday’s tools for managing software development to succeed at this point. We’re still roughly on year one of this transformation.

The new bottlenecks are creating and enforcing boundaries in the code, identifying level of risk within a boundary, subjecting high risk areas to more intense human review and architecture reworks, and so so much more manual testing.

We need a new language for high level development that focuses on architectural constraints. We need analysis software that helps draw boundaries, identify what needs extended human attention, and helps us map and understand a rapidly developing code base. We need to standardize on the use of frameworks and languages like we have on assembly variants.

I’ll bring up a hacker news trope here. NaughtyDog’s GOAL was an amazing system that was a product of an underdeveloped ecosystem for game development at the time. They used lisp and assembly because you still had to write assembly for performance reasons then.

We are in a very similar period. The ecosystem is underdeveloped. We should be looking for new languages and tools to manage this.

CNC machines used to run from punch cards and then hand written NC code. Now we have advanced CAM software. (Which innovative people are actually running with LLMs!)