I'll note that, if it is true, the only other alternative is to ensure liability is held by whoever trained and/or provided the inference for the damage done by the model. This would effectively shut down open-weight models anyway.

...why are they all skewed, save for the buns that are already lopsided? Those I'll note are perfectly seated. Some are more skewed than others. Like the Big Mac is only slightly skewed.

Is there a pecking order to how skewed they are? Some social hierarchy of sandwiches?

It really is eye-opening how powerful it is once you connect your life to it. The biggest improvement is actually the trivial stuff — emailing contractors, accountants, etc. I no longer need to open another app, navigate six separate steps, and organize everything on the fly just to send one message. I stay in one place, organize my thoughts about what I’m trying to do, and the execution happens automatically.

For example, open claw will find the relevant threads, lookup the relevant details via web search, present them to me, give me a draft, I can review it, edit it, and send. 2 minutes instead of 20.

As a software engineer using AI daily, I think this is the real unlock — staying in a single context and not getting lost in the long tail of trivial details that fragment your attention before you ever get to the actual work.

The mental model shift is important too. It’s not that AI does all the work and we end up with agents emailing each other. It’s that AI automates the steps required to achieve your goals, so you can focus on the substance — like actually writing the email instead of navigating to the place where you write the email.

I also have GitHub and Vercel wired up, which means I can jot down an idea for a little productivity app for me and my family and it just appears a few minutes later, deployed and ready to use. That alone has been worth the setup.

System of record and all.

You want Medicaid? Tell everyone about your hemorrhoids first.

If I could have it read more of my project in a single gulp and produce the 10-1000 lines of code I want in a few seconds, I wouldn't need it to go off and write the thousands of lines on its own in the background. But because even trivial changes can take minutes by the time it slurps up the right context and futzes with the linter and types, that ideal pair programmer loop is less attractive.

Otherwise impressive.

In a world where AI can read our codebase, ingest a prompt, and quickly output "correct" if not clean and concise code, and then be able to iterate on code with more prompt, do we need all the same patterns we used to adopt when humans were painstakingly writing every line of code?

This reminds of of the CISC to RISC migration - now that computers are in the loop writing the tedious parts, we don't need to burden our codebase with patterns meant to relieve humans from the tedium.

I find myself, for instance, writing more long form, boring configuration files that once upon a time I would have built some abstraction reduce the boilerplate and verbosity. But now that co-pilot can just auto-complete the next section for me, why bother?