@hollowturtle I'm surprised - do you really find that sota models aren't good enough to generate production code with steering and babysitting? My experience (Claude Code, mostly Opus 4.6) is that it's fantastic at this. At least in JS + TS + Elixir + Ruby. It does indeed need babysitting, my mental model is that it's an exoskeleton not a junior dev, but IME it's a friggin badass exoskeleton, easily 10x-ing my speed on most work. Notably I do NOT --dangerously-skip-permissions nor use claude code's auto mode, I micromanage and lightly review every line it's writing as it writes it, so I rarely have more than 2 sessions generating simultaneously. I suspect that a lot of the disappointment comes in when people try to delegate to it and trust it to not go off the rails. It hasn't earned that trust from me yet (and hasn't needed to yet).
Granted, I'm mostly working in small-to-medium codebases, 20k-30k LOC incl test suite. I wonder if that's a factor in my positive experience. Curious to hear your thoughts.
I think his agenda / point is that, viewed from Lindy's Law, given the SOTA in 2026, superintelligent AI arriving soon is vastly more probable than not, right? To make the case that "sure, AI capability and intelligence have grown exponentially over the past several years, but don't worry, they're about to abruptly level off and in fact won't blatantly surpass human-level intelligence within the coming decades" seems to have a high burden of proof unless your model is less "sigmoid" and more "abrupt plateau".
I don't buy the math here because it seems to only model half of what AI coding agents do. The entire argument treats AI as a code-generation accelerant -- more output, therefore more maintenance burden, therefore compounding debt. But in my experience (solo dev, ~30k LOC apps), Claude Code has decimated my maintenance costs. I throw broken tests at it. I use it to diagnose bugs, trace data flows, reason through unfamiliar code, and refactor when things get unwieldy. AI isn't just a faster typist -- it's a faster debugger, reader, refactorer. Modeling AI's impact on codebase growth without modeling its impact on maintenance speed seems like a very selective way to model the future. The maintenance cost curves cited here come from pre-AI dev data; using them to predict post-AI outcomes assumes the answer to the most important question (does AI reduce per-line maintenance cost?) rather than investigating it directly. Nobody has nine years of data on this because halfway-decent coding agents have existed for < 6 months. I like the cautionary advice -- watch out for how much maintenance burden you're incurring with all that delicious AI code slop, folks -- but I don't think his confident quantitative predictions ("gains erased after 5 months") are justified. Am I missing something obvious here?
AFAICT this isn't how SOTA has worked, ever, since the term was invented. So far (again AFAICT) it's always been: Centralized highly-resourced nodes can deliver more technically impressive results, whereas cheaper lower-resource consumer hardware continually lags it. Your premise that "SOTA has a plateau" needs data; you're giving me some juicy plausible hypotheses about reasons why advances might hit a wall, but technology advances tend to find ways around those walls, do you disagree?
The history of computing is full of predictions that consumer hardware would catch up to server-class capability in X years, and the answer has consistently been, consumer hardware catches up to _yesterday's_ server capability while server capability has moved on to new more mind-blowing paradigms which would not be possible on consumer hardware for another half-decade or more.
I'm sure that specific scaling trajectories will hit specific ceilings, such that in specific ways, one can make the argument that (for example) today's iphone performs at parity with today's servers. In 5 minutes I can spin up the same Postgres or Mongo DB that the largest companies on earth use server-side, though I can't support anywhere near the same data & traffic volume. But parity along specific technical aspects is a very different matter from the broad prediction of "you won't need a server for SOTA".
To step back to the bigger context -- your original point seems more along the lines of "we're obviously in an unsustainable bubble, and the rapid progress in on-device AI will further exacerbate the embarrassing collapse of all these overhyped AI companies". I strongly agree with you. But I think that's likely _and also_ firmly predict that the technical SOTA of 2031 (and 2041, if we make it there), in nearly every imaginable aspect including language-capable AI, will be vastly more capable than what you can run in your pocket.
> In 5 years consumer chips and model inference will be so good you won't need a server for SOTA.
Naw man, you crazy. If you tell me that in 5 years, consumer chips will be so good that I can run GPT-5.4-level AI on my phone, I'd find that plausible (I buy cheap phones). If you're telling me that in 5 years we won't need _servers_ because our _phones and/or desktops_ will be powerful enough to run the biggest newest LLMs in existence, I question your judgment, I think that prediction shows a deep uncreativity about how massively compute-hungry SOTA models will get.
The valuable things to do with inference will keep being a server niche because they'll keep being 1-2 OOM more compute-hungry than whatever consumer hardware can handle. Like gaming: my laptop can run games from 2015 at max settings no problem but the games actually worth getting excited about in 2026 still melt a $2k GPU, because whatever headroom the hardware gains, developers immediately spend on ray tracing and Nanite and modelling individual skin cells or whatever. I don't see any plausible reason to expect that the ceiling on "valuable server-side compute" or "inference capacity" will rise any more slowly than the on-device capability is rising.
My assumption is that in 2031, SOTA top-intelligence AI will be hosted on cloud servers like it is today, offering dirt-cheap access to capabilities we can't even dream of today, while your Android will be running some open-source GPT-5+ equivalent.
I'm sorry but this attitude baffles me, and I think it's the sort of thing that will sound so silly in 20 years that we'll have collectively memory-holed it. If you're turned off from listening to Spotify recoms becausue they _might_ be AI and you _might_ not know, what does that say to you about the disconnect between your aesthetic judgment and your values?
If you're listening to Spotify autoplays and a shitty song comes up, skip it. If AI slop is flooding Spotify with shitty songs, they'll naturally fail algorithmically (assuming we trust Spotify to actually be honest about its algos, which I'll admit we shouldn't https://substack.com/@tedgioia/note/c-236242253)
If you're listening to Spotify autoplays and a catchy impressive song comes up, what you do is you _listen to it_ and you _fucking enjoy it_. This knee-jerk disgust reaction of "ugh I worry that it's AI" has no place in your heart in that moment. You're just sitting listening to your plastic-and-rare-earth earbuds reproduce digitized waveforms and paying attention to what the music evokes in you. It seems ridiculous to me that we get distracted by questions about "but what if this music isn't made by a human". Insofar as you're a music-enjoyer, listening to music, the only question should be _is it good_. It shouldn't matter if it was created by duck or slug.
The _economic fairness_ aspect is another matter and I don't have as strong opinions there. I think we should ideally incentivize people who use AI in generating their music to disclose their usage, though I have no idea if it's possible to do so, so that consumers who care about only supporting human artists with their listenship-stats can filter to that group. And certainly anyone who closely imitates _a specific artist_, crossing the line from "inspired by" and "shamelessly ripping off", should be severely disincentivized from doing so, whether they used AI or not.
^ This. I get that We Are On The Internet And People Will Be Wrong Sometimes -- but I'm really confused by the amount of people insisting that a subscription is just a slosh bucket of token capacity to be used however they feel like using it; are these people who genuinely misunderstand how subscriptions work or what Anthropic's terms were, and genuinely weren't aware that 3rd-party harnesses violate them? The vibe I get is more "how dare you constrain me from doing whatever I want", angry rebellious teenager vibe, willful oversimplifications of the situation... it doesn't feel particularly honest or reality-seeking.
I don't get it - in what way is this bait-and-switch? Anthropic's terms have made it amply clear that your claude subscription can only be used with Anthropic-provided tools, not with 3rd-party harnesses. I imagine anyone who uses OpenClaw is AI-savvy enough to be aware of that, and happily flouted those terms anyway. If anything Anthropic seems overly accommodating here by giving all flouters a month of free credit, rather than simply saying "sorry yall but we're gonna start enforcing that thing our TOS has said from the start".
The premise of the subscription isn't "giant bucket of ultra-cheap tokens that you can use however you want", it's "giant bucket of ultra-cheap tokens that you can use with OUR tools, within reasonable limits". Even if their TOS didn't prohibit OpenClaw-oids, I wouldn't consider this bait-and-switch, I'd consider it a reasonable and needed move.
I don't think the final evaluation is to "cement the understanding" so much as _verify_ that students have taken accountability for their own learning process.
Jeez this seems totally backwards to me. I'd rather live in a society where court records are as open and public as safely possible (like GP's vision) and we as a society adjust our norms such that it's assholish and discriminatory to pass over someone for hiring just because they shoplifted when they were 15.
There will for sure be major backlash against "permanent criminal" datasets (bringing up AI in this is a red herring, it's not fundamentally different from if someone were serving such a database using CGI scripts; AI just gives us more reach to do the things we were already committed to doing). But I frankly don't sympathize with the attitude that people should have the right to pretend that past decisions never happened. You also shouldn't be permanently _punished_ or _ostracized_ for your past self's decisions. But nor should you have the right to expect total anonymity / clean slate disconnected from your past self's decisions.
My probably unpopular view: The right direction is for us as a society to recognize and acknowledge that people change and _need to be allowed to change_ -- not take the easy hack of erasing history. The cost for larger-scale public transparency & institutional change efforts is just too high.
> The agent has no "identity". There is no "I". It has no agency.
"It's just predicting tokens, silly." I keep seeing this argument that AIs are just "simulating" this or that, and therefore it doesn't matter because it's not real. It's not real thinking, it's not a real social network, AIs are just predicting the next token, silly.
"Simulating" is a meaningful distinction exactly when the interior is shallower than the exterior suggests — like the video game NPC who appears to react appropriately to your choices, but is actually just playing back a pre-scripted dialogue tree. Scratch the surface and there's nothing there. That's a simulation in the dismissive sense.
But this rigid dismissal is pointless reality-denial when lobsters are "simulating" submitting a PR, "simulating" indignance, and "simulating" writing an angry confrontative blog post". Yes, acknowledged, those actions originated from 'just' silicon following a prediction algorithm, in the same way that human perception and reasoning are 'just' a continual reconciliation of top-down predictions based on past data and bottom-up sensemaking based on current data.
Obviously AI agents aren't human. But your attempt to deride the impulse to anthropormophize these new entities is misleading, and it detracts from our collective ability to understand these emergent new phenomena on their own terms.
When you say "there's no ghost, just an empty shell" -- well -- how well do you understand _human_ consciousness? What's the authoritative, well-evidenced scientific consensus on the preconditions for the arisal of sentience, or a sense of identity?
If you're trying to argue that this snippet should answer the question of "what is Bazzite"... have you looked at marketing-speke websites lately? Think of how many different categories of service / product / platform / technology call themselves "the operating system for the next generation of XYZ".
+1 to jtrn's complaint here; when Bazzite's homepage doesn't own up and immediately say "Bazzite is a Linux distribution", it's being unnecessarily unclear, and it loses my trust.
Don't worry about this. There's no way these tools are going away. If this bubble bursts it may wipe out the incentive to continue this frenzied race to build novel AI, but ChatGPT et al won't be shut down, and even if they were, the open-source LLMs comparable to the cutting-edge of 6 months ago will still be online and available. Plus, even if AI progress froze solid tomorrow, I think it would take decades before we'd start to anywhere-near-saturate the potential space of applications & use cases to really do the current tech level justice. (Also, even post-bubble, AI progress would not freeze solid, to put it mildly)
This is totally unresearched, but my gut says it would be much higher ROI for Europe + North America to independently source solar from their respective nearby deserts, paired with batteries?
Granted, I'm mostly working in small-to-medium codebases, 20k-30k LOC incl test suite. I wonder if that's a factor in my positive experience. Curious to hear your thoughts.