side note, I’ve been trying to remember when it launched internally if anybody knows. I feel like it was pre-COVID, but that’s a long timeline from internal use to public preview

immediately to a fantasy slippery slope argument, cool!

your argument seems to boil down to paid ads being the lifeblood of the flow of information. my argument is it corrupts that flow of information, and we’d be better without them —- everything would operate just fine. individuals and organizations would have better incentives to share valuable information, not what they get paid to. obviously there would be plenty of details and edge cases to work out, as with any policy in the real world

I’m not going to write out policy in HackerNews comments and play that game with someone who jumps to the “imagine this crazy world where the police start arresting all of us over free speech!” as their explanation for what would go wrong

> people can pay to have their messages displayed where they will be seen

…why? distribution of information is free across the world, which was not the case a century ago. let the message speak for itself

I ask again, what’s your actual argument against? you’ve seen things through ads you’ve liked? you think people should be allowed to pay to put their thumbs on the scale of the distribution of information? to what end?

- you don’t need to use Python (but Pythonic wrappers like Ibis exist; disclaimer I worked on Ibis, you can find my blogs on performance comparisons easily there); CLI, WASM, etc. w/o Python

- governance: DuckDB as OSS is setup in a more sustainable way (DuckDB Labs + DuckDB Foundation). while there is a VC-backed company (MotherDuck), it doesn’t employ the primary developers/control the project in the same way the Polars company does

- overall just simplicity and focus. tends to break less, solely focused on single-node, easy to extend, etc. — not trying to do a cloud product, distributing computing, supporting GPU execution

still doesn’t really prove much

- agents tend to need (already have) a filesystem anyway to be useful (not technically required but generally true, they’re already running somewhere with a filesystem)

- LLMs have a ton of CLI/filesystem stuff in their training data, while MCP is still pretty new (FUSE is old and boring)

- MCP tends to bloat context (not necessarily true but generally true)

UNIX philosophy is really compelling (moreso than MCP being bad). if you can turn your context into files, agents likely “just work” for your use case

where’s that info from?

very little software (or hardware) used in production is formally verified. tons of non-deterministic software (including neural networks) are operating in production just fine, including in heavily regulated sectors (banking, health care)

and once you get used to things being that fast, it’s hard to go back (analogous to what people say about high-refresh screens/monitors)

all that said the speed of the default mac terminal (and other emulators I tried) was always fine for me, performance was not why I switched to Ghostty

yes AI makes leaking keys on GH more prevalent, but so what? it’s the same problem as before with roughly the same solution

I’m saying neural networks being probabilistic doesn’t matter — everything is probabilistic. you can still practically use the tools to great effect, just like we use everything else that has underlying probabilities

OpenAI did not have to describe it as sycophancy, they chose to, and I’d contend it was a stupid choice

and yes, you can explain what went wrong just like you can with CPUs. we don’t (usually) talk about quantum-level physics when discussing CPUs; talking about neurons in LLMs is the wrong level of abstraction

oh I think I do get your point now after a few rereads (correct if wrong but you’re saying it should keep getting better until there’s nothing for us to do). “AI”, and computer systems more broadly, are not and cannot be viable systems. they don’t have agency (ironically) to affect change in their environment (without humans in the loop). computer systems don’t exist/survive without people. all the human concerns around what/why remain, AI is just another tool in a long line of computer systems that make our lives easier/more efficient