srock

Programmers today: "boo-hoo your language sucks! 😭" Dijkstra in the past:

@thenanyu @teej_m

When you hear or say “systems thinking”, what is the exact definition you’re thinking of in your head?

@crypt0lake Only 10% creating new ones?

90% of your time should go into optimizing your dev loop

@rob_mcrobberson For example quick syncs

writing code was always the easiest part of the job, all the hard parts still remain

@RadishHarmers Has yet to be disproven

Jacobian conjecture 2: It works for everything except that particular counterexample.

@mitchellh @almonk What is it fixing fast if it doesn’t break?

Quality software doesn’t break, doesn’t demand attention, knows its limits, and fixes fast. @almonk is a fine builder of quality software, recommend.

Life hack: you can correct anyone on anything if you prefix it with “erm actually” and do the redditor voice ironically

@TomLamparody @PBFcomics Erm actually wouldn’t that just mean there’s no perfect size

@PBFcomics If the universe is infinitely large and infinitely small, then we're the perfect size to experience the world we live in

@sadbryce Or they worked a job where they did troubleshooting over the phone

the biggest tell that someone grew up rich is they say “Correct.” when agreeing with you

@prasenx Med school

"get a cs degree" was the safe path for 20 years what's the safe path now

@oprydai A thought

what is a thought about a thought called?

@fchollet x.com/jiratickets/st…

@fchollet I agree what is frontier today will be cheap tomorrow. But by the time this frontier is cheap, the number goes up further. There’s a widespread belief (which I often disagree with) that bigger is better. Frontier labs will always attempt to pay to win.

All current debates about AI are predicated on the assumption that frontier AI training will always be expensive. But in the future, AI will not be based on the primitive stack of today, and both training and inference will be incredibly cheap.

@deanwball “(the CCP is very Yann Lecun-y in its views of AI)” as an aside to explain to tech bros the CCP

Some observations on Kimi: 1. It's a very good model! I don't think its performance can be explained away by distillation or anything like that. In agentic coding sessions, it seems pretty much on par with the best public models of Q1 2026. In my fairly limited use, it also seemed very token hungry. It's not obvious to me that this model is actually that cheap to run. 2. I am personally surprised the Chinese state continues to allow the open sourcing of models this good, given potential risks. To be clear, I *myself* might be fine with models presenting this level of marginal risk being open weight, but I am surprised that China is fine with it. I suspect the reason they are is 75% explained by strategic blindness/lack of AGI-pilledness (the CCP is very Yann Lecun-y in its views of AI). The other 25% or so is their lack of compute for customer inference (making China's open-weight strategy an unintended byproduct of US export controls) and the normal Chinese strategy of aggressive exports. For the companies, as opposed to the government, the decision to open source is partially ideological and partially because they are behind, and they know that very few people would pay for sub-frontier models from China. 3. Open-weight models are inherently decelerationist, and I'm continually surprised to see the so-called "accelerationists" so excited about open-weight models. I suspect the reason they are is that they know open-weight models are effectively ungovernable, and they simply like the overall cloak of ungovernability open-weight models create over the whole of AI. It's not a bad strategy; it reminds me of James Scott's recounting of the hill people in "the art of not being governed." Still, in the end, open-weight models deter further AI capex. 4. One probable outcome of an open-weight-model-dominant world is full AI communism, which is precisely what China proposes: rather than a market product, AI is a "public good" which will ultimately be provided by the state as a kind of "digital public infrastructure." This future strikes me as a dystopian hellscape, but I've never met an open-weight models advocate who doesn't ultimately concede this is where things end. You'd be surprised how many 'accelerationists' lobbied me, while I was in government, to support an eleven or twelve-figure federally funded data center so that startups could train models at a subsidy and then give them away for free. There was no other way for AI to progress, they said. Perhaps this is the logical end state of things. Nonetheless, I find myself surprised to see supposed accelerationists excited about such an outcome. I think many of them just don't know what they're doing. Many accelerationists do not view the creation and serving of frontier models as a legitimate business. 5. I would guess that the Trump Administration will at some point realize that their best strategy here would be to create large amounts of regulatory risk around the use of open-weight Chinese models. You don't need to "ban open source" (one of the dumber motifs of AI policy discussion). You just need to direct every agency to issue soft law that creates FUD. "A Federal Reserve Advisory Bulletin found that there may be backdoors in Chinese AI models." It needn't be that well justified. You just create enough regulatory risk that every regulated enterprise backs off. You probably don't want to create so much regulatory risk that you scare off the hyperscalers from serving Chinese models; this will just drive startups to sketchier providers. There's a happy middle ground here. I'd assume they will do some version of this. 6. It's probably true that open-weight models of this capability make the world a bit more dangerous, but not so much more that you'll really notice. At some point the models will be capable enough that you will notice. "A nonliving, invisible, dangerous, and infinitely self-replicating agent escaped from a Chinese lab," you say? Color me shocked.

@tenderizzation 😭

local llm enthusiasts be like: "there's actually a very competent inference machine hidden in your macbook that can serve near-frontier class open models!"

@leylndd Not if you’re dogfooding 🙃

is “sent using Claude” disrespectful?

@a16z @handotdev @mintlify @claudeai @cursor_ai @tryreplicas @Replit @Lovable @gumloop @greptile @SlackHQ @temporalio @parahelp_ai No agent to prevent him from posting grindslop I see

.@Mintlify grew 10x in a year. CEO @handotdev shared what's in their internal AI stack: Code: @claudeai @cursor_ai @tryreplicas Design: @replit @lovable Personal agents: @gumloop Code review: @cursor_ai @greptile Agent ops: @slackhq @temporalio Support triage: @parahelp_ai @plainsupport @linear Sales intel: @tryattention @salesforce @meetgranola Knowledge base: @notionhq @mintlify

@handotdev The pain cave doesn’t make you smile?