When AI Builds Itself: Our progress toward recursive self-improvement

https://www.anthropic.com/institute/recursive-self-improvement

by meetpateltech • 2 months ago

534 700 2 months ago

anthropic.com

damowangcy• 2 months ago

AI tech bro:

Month 1 - 6 months to AGI

Month 2 - We will Replace all jobs

Month 3 - Okay maybe only the SWEs, programming is solved

Month 4 - Announce model that is too dangerous to release

Month 5 - Releases dangerous model

Month 6 - This is it! We will replace AIs with more AIs (*secretly files for IPO)

AI is here to stay, like it or not but it is not the solution to everything. If it is, what is Anthropic's moat? A better model? I don't see any ecosystem being built by them, as MCP is almost obsolete except for some very niche use case. And they're doing stuff that a non-profit version of OpenAI would do. Can we trust a for-profit company to stand against their investors during a conflict of interest? Because running a company for maximum profit versus being ethical is two different end of the spectrum.

parpfish• 2 months ago

i'm waiting for the AI giants to realize that they are burning cash to run their consumer-facing chatbots and that they should kill those products to focus on their enterprise tools.

free chatgpt doesn't need to exist anymore. its job was to build hype/interest and it did.

but take it away and you solve many social problems and annoyances caused by AI with no loss to the upside of AI. no more cheating students in school. no more shitty linkedin posts. no more dangerous "therapy sessions" that give bad advice.

nevertoolate• 2 months ago

What is an ai enterprise tool?

overgard17• 2 months ago

There will always be shitty linkedin posts.

baq3• 2 months ago

Anthropic is providing agentic intelligence as a service. OpenAI and Google deepmind also are in this business.

The problem is, if you’re any sort of knowledge worker, you’re essentially providing the same thing: you’re an intelligence with agency.

MCP is irrelevant. The moat is the quality of intelligence the service providers sell, including you. Tokens aren’t fungible between providers until you measure that they are for your use case, that’s kinda sorta the goal of job interviews.

Thus the moat will be that they’re providing the best models for the things people need other intelligent people for, but we should expect there will be limits on how much share they can economically take assuming competitors are optimizing for slightly different targets (but there’s still significant overlap in capability). This will disappear, but it’s always a question of when. The path matters as much as the destination.

Note that implications for you and me are exactly what the article says they are: nobody knows, but it’ll be a dramatic shift.

delichon2• 2 months ago

Is this the moment when the AI gets permission to approve its own PRs:

https://www.italianrenaissance.org/wp-content/uploads/2012/0...

Or is this?

https://www.egypttoursportal.com/images/2024/02/Ouroboros-Sy...

cpeterso• 2 months ago

more like the "Obama Awards Obama a Medal" meme:

https://knowyourmeme.com/memes/obama-awards-obama-a-medal

simianwords2• 2 months ago

Sorry but if AI can build itself then it can run companies of size 3000 companies with a few people. Or even higher. What are the consequences?

delichon2• 2 months ago

When AI is a more effective capital allocator than NI it will drive capital into the accounts of whoever controls the AI, gaining them increasing decision making power over the economy and culture. Maybe those controllers will be human at first.

cdrnsf• 2 months ago

They will not be.

lstodd2• 2 months ago

As has been mentioned in the sibling comment it already is.

Consequences are: financial crisis.

artninja19883• 2 months ago

The mythos public release will be a big indicator if the Anthropic and SF story of transformational ai soon holds any water imo

vblanco2• 2 months ago

Another article about how anthropic wants to ban everyone except themselves and destroy opensource and chinese AIs.

reasonableklout3• 2 months ago

Where is this discussed in the article? I don't see any mentions of China or open source models

artninja19883• 2 months ago

Not really mentioned explicitly but:

A meaningful slowdown or pause would require multiple well-resourced labs at or near the frontier, in multiple countries, agreeing to stop under the same conditions. It would also require that each can verify that the others have actually stopped. Due to the unique characteristics of AI systems, the detectability (a lower standard than verifiability) element of this arms control problem is much more challenging than with other technologies. Training runs are far easier to conceal than missile silos, their inputs are general-purpose, and the incentive to defect quietly is enormous, because whoever continues while others pause could inherit the lead. A credible pause also has to specify what triggers it, what lifts it, and who adjudicates.

And later:

In the coming months, we will organize conversations where policymakers, researchers, civil society, and other AI companies can help answer some of the questions this piece raises, especially around full recursive self-improvement and how to create better options for coordination and deliberation. We’ll publish what comes out of it. The window to investigate the questions together is here, and people outside AI companies should be involved in this deliberation.

b65e8bee43c2ed0• 2 months ago

Gell-Mann amnesia expressed by people when a corporation says something they like is both baffling and disheartening to see.

Altman, Amodei, and the rest of them are anthropomorphic grease. their personal wealth is tied to the value of their respective companies. everything they say and do is self-serving.

morisil• 2 months ago

Quite aligned with my own experience from harness engineering and winning AI4Science hackathon. During the hackathon I was working as a human optimizer, moving the feedback from test harness running on Claude Code, back to my local Claude Code for analysis-hypothesis-proposal cycle. And in this moment I realized that 2 Claudes talking to each other could actually scale much better.

anilgulecha• 2 months ago

We believe it would be good for the world to have the option to slow or temporarily pause frontier AI development to enable societal structures and alignment research to keep up with the advance of the technology. The Anthropic Institute will conduct research—in collaboration with many others—and take actions to help build the systems that a credible slowdown or pause would require.

Interesting - they're commiting to kickoff policy conventions to organize a world-slowdown of frontier LLM building. If they actually are able to crack it, this will give a much needed breather IMO. As exciting as the last ~6 months have been, there's some bigger questions to go answer now.

fasterik2• 2 months ago

We should be skeptical of any major player that advocates for regulating their own industry. In practice, this just means increasing barriers to entry and making it harder to compete with them.

In my mind we should be trying to push AI along the Linux trajectory. You have a free and open source product, developed by a decentralized team with a strong code of ethics, running on commodity hardware. There can still be trillion dollar industries built on top of it, but the core technology is democratized and available to everybody. I don't see how we get there if we allow a handful of companies to dictate where development of the technology goes.

techblueberry4• 2 months ago

Wouldn’t this align with their financial interests? In theory the thing that’s keeping them from being profitable (or one of the big things) is the periodic capex expenditures of building new frontier models.

mofeien4• 2 months ago

The regulation that is being argued for here is against pushing the frontier. Entering the market with say a new speech to text model is not subject to such regulation. What's needed is something qualitatively different from entry barriers, and of the frontier model companies at least Anthropic and deepmind seem to have enough self-awareness to speak about it. They are finding themselves in a race with possibly catastrophic outcome for humanity and would like to stop, but it needs internation cooperation on a level that no single company can provide.

Upvoter332• 2 months ago

I read this differently: they are actually seeing that it's hard to keep advancing frontier models, and now are moving the goal posts so that when they start getting evaluated more harshly, they can point to something like this.

smokedetector1• 2 months ago

Theyre probably looking to get a way to slow down the capex required to keep up, so they can be more profitable

chasd002• 2 months ago

organize a world-slowdown of frontier LLM building

i don't want to be a negative nancy but i'm sure this "slowdown" will only be in effect until the infrastructure buildout is done or largely done. If they weren't hardware constrained there'd be no slowdown at all. Whoever gets there first wins everything ("there" being defined as AGI or a similar scale leap in capability).

amelius• 2 months ago

Does this train on LLM output, or is this more like iterative self prompt improvement?

Legend2440• 2 months ago

Have you tried reading the article? It answers your question.

Don't ask people to explain the article to you if you're too lazy to open it yourself.

_se• 2 months ago

I think that's the whole point of LLMs

HarHarVeryFunny2• 2 months ago

Their statement is that they regard lines of code shipped as indicative of self-improvement. So, while a well written coding agent might be a few thousand LOC, Athropic's is bloated like a decomposing whale and over 500K LOC ! What more proof do you need?

nickandbro• 2 months ago

So what happens when the world becomes hyper optimized with closed loop AI agents recursively trying to optimize everything deemed sub optimal?

peheje• 2 months ago

there will be a lot of paper clips

simianwords2• 2 months ago

Often repeated meme doesn’t have any bearing to reality.

The orthogonality thesis sounds like a fun gotcha but if you give it some thought you realise how strange it sounds and the opposite thesis - collinearity thesis is actually correct.

1. Intelligence transfers and compounds

2. Goals of agents are not arbitrary

3. Our goals and agent goals are more likely to be aligned at the deeper level

mofeien4• 2 months ago

I would assume that shortly after, the solar system will be hyper optimized as well, then the milky way, then the local cluster, and so on. Everything will be close to optimal afterwords, and I sure hope we will have specified the target function for that optimization correctly in the single attempt that we will have had.

Readerium• 2 months ago

Loll

Groxx• 2 months ago

Github outages will probably get worse.

layer84• 2 months ago

If it optimizes itself away because it’s suboptimal, that wouldn’t be the worst outcome. ;)

llmslave3• 2 months ago

I cannot wait for these models to tear down traditional social hierarchies. We havent even begun to see the effects, fingers crossed

baq3• 2 months ago

Hierarchies exist for a reason, take away the reason and the house of cards eventually collapses — but the house of cards is still a house. When it’s gone, we’re back to laws of the jungle.

Be careful what you wish for IOW.

llmslave3• 2 months ago

I think certain types of people with power, i.e. access to capital, will lose relevance. world will become more meritcratic with ai as leverage to the individual

techblueberry4• 2 months ago

Tear down or reinforce?

llmslave3• 2 months ago

capital/ability to leverage labor is going to lose power

SimianSci2• 2 months ago

Never heard of a stratified economy? Spoiler alert: none of us will be in the good part.

techblueberry4• 2 months ago

A caveat: Lines of code is an imperfect measure, as it measures quantity over quality. So 8× lines of code/engineer/day in the second quarter of 2026 is almost certainly an overstatement of the true productivity gain. Nonetheless, it indicates an acceleration. At Anthropic, we don’t reward people for how many lines of code they write; rather, team members are producing more code simply because they’re using AI systems to write more code.

I simultaneously think the AI revolution is making real revolutionary gains and am mystified by the lying.

An accurate Translation seems to be “we made this shit up, but it feels right”

embedding-shape• 2 months ago

Until the moment we start bragging about how many lines of code LLMs are saving us, we're walking in the wrong direction. Your programs, designs and architectures is supposed to get better, not add even more boilerplate just because you can produce it faster...

HarHarVeryFunny2• 2 months ago

"You go to IPO with the AI you have, not the AI you might wish you have." -- Donald Rumsfeld

So, right now it's a verbose code generator.

But post-IPO it will be wonderful - sentient, self-improving (recursively, iteratively, asymptotically), full of loving grace.

jazzyjackson• 2 months ago

I guess the claim is simply that AI written code is verbose and there’s lots of it being created but I agree, these systems seem to be able to create lots of low quality software, so until FreeCAD has feature parity with Solidworks I’m bearish on the singularity.

darepublic• 2 months ago

the tooling has quite a ways to go to catch up to the llm engines that drive the real value. I have encountered various codex bugs (I know not anthropic) which tell me that.. these billion dollar companies, if they are eating their own dog food, can still release buggy crap software.

mofeien4• 2 months ago

If it were possible to effectively slow the development of this technology to give ourselves more time to deal with its immense implications, we think that would likely be a good thing

Even Anthropic wants to Pause AI now. There must really be not much time left for "edging". Please write to your lawmakers, no matter whether you are in the US, Europe, China, or elsewhere. Only an international agreement between governments can enforce an AI-Pause and eliminate the necessity to dangerously push the frontier.

https://pauseai.info/

honeycrispy3• 2 months ago

That would be like trying to get every country to agree to give up nukes.

ChrisLTD2• 2 months ago

Or stop making more, and testing more, which we got the biggest countries to do, at least for a time.

mofeien4• 2 months ago

Or agree on finding ways to promote peaceful use of nuclear energy. This has been done, there are thousands of people working on it around the globe and 180+ member states of the IAEA. It's not easy, there have been close calls.

And cooperating interntionally to buy ourselves time to find ways to develop this "last invention" is a way that will do good for humanity seems to be on a similar level.

apsurd3• 2 months ago

Whichever side I may stand on, pausing just seems unnatural? Life is movement.

honeycrispy3• 2 months ago

And happiness is restraint.

senderista2• 2 months ago

They don't, they just pretend they do.

butler14• 2 months ago

Warming up for that IPO

stri8ted• 2 months ago

Is there something in the post that you find implausible or don't believe to be true?

rightbyte• 2 months ago

Taken far enough, and given enough compute, that trend points to an AI system capable of fully autonomously designing and developing its own successor. This is called recursive self-improvement.

Sounds iterative to me.

georgehotz• 2 months ago

The world has been recursively self improving for millenia. Similar to scientology, this is a cult pushing sci-fi nonsense. They are just coupled to an LLM lab to give their stories an aire of seriousness. Imagine scientology starting making laptops.

4ffs3• 2 months ago

TBH the more Anthropic keeps yapping the more desperate they seem now. OAI has been pretty quiet in comparison lately.

torben-friis3• 2 months ago

A caveat: Lines of code is an imperfect measure, as it measures quantity over quality. So 8× lines of code/engineer/day in the second quarter of 2026 is almost certainly an overstatement of the true productivity gain. Nonetheless, it indicates an acceleration. At Anthropic, we don’t reward people for how many lines of code they write; rather, team members are producing more code simply because they’re using AI systems to write more code.

What about the hypothesis that AI is generating more verbose code? I just see the text pretending to acknowledge "LOC != Productivity" and then using it as a metric anyway.

fooqux• 2 months ago

Exactly. If AI is going to start being graded on how many LoC it generates- oh, I'm sorry, how much it "accelerates", than guess what newer models will start doing more of?

simondotau• 2 months ago

Surely they can train AI on the signal to change as few lines as possible. Indeed, this is something I'd want to have control over when making requests. In a traditional UI, I'd imagine some kind of slider between "fewest lines" and "be bold".

verdverm7• 2 months ago

I'm actually hopeful that the recursive code training will improve quality over time. I'm definitely producing higher quality code, tests, and docs. It does take attention and oversight, iteration and refinement, one cannot just let these things loose on a code base and expect good things to happen. You have to leverage them to make the good things happen.

malfist3• 2 months ago

One of my co-workers just asked me to review his pull request that was all AI generated. 600 files were touched, over 40k lines of code added.

I'm sure he thought that was a crowning achievement, proof that AI can enable 10X developers, after all, what engineer could write 40k lines of code in a week?

I declined to review it, stating that I couldn't possibly vet 40k lines of code, and wouldn't put my reputation on the line to stamp the work as good. The PR nagged me for 2 weeks from my todo list and then disappeared. I don't know if he found another dev to get an approval from, or if the PR was abandoned. But I know for sure that him and I are on two totally separate islands around the value of LLMs.

CamperBob23• 2 months ago

I declined to review it, stating that I couldn't possibly vet 40k lines of code

Gee, that sounds like a job for Claude if there ever was one.

squidsoup3• 2 months ago

That's a process problem at your company - no developer should be proposing branches over 1k loc (or whatever your agreed tolerance threshold is) without a very good reason, vibe coded or not.

fg1375• 2 months ago

Same here. A co-worker touched a few hundred files in a PR and asked us to review. They merged it directly to main when nobody approved it. (The repo was not set up to enforce PR approval.)

I don't personally use that feature, and I couldn't care less at this point. If our customers are frustrated by the bugs, at least my name is not on it.

afro88• 2 months ago

This is a branching point. One dev would find someone else and convince them to approve it. Another would redo the task (code is cheap now, right?) in a PR stack that can actually be reviewed, cleaned up etc.

I hope they were the latter.

SpaceNoodled• 2 months ago

You could surely check on the status of that PR.

LtWorf3• 2 months ago

A former coworker sent me an AI generated PR to review and I just said NAK after the first two issues I found and I said to not send me AI slop to review.

They went to HR who said I am more senior and I should act as a mentor (they had my same work title and were probably making 4x more due to being in USA) and I just no longer reviewed anything from them until I changed jobs.

otikik• 2 months ago

My review would have been along the lines of:

'Please split this PR into smaller ones'. I would even sketch which groups/phases would make sense, perhaps with the help of AI.

chuckadams• 2 months ago

AI generates code that mimics the existing code. If your code is terse and comment-free, then the agent’s code is too. The times I’ve seen Claude drift into a default “house style” it generated like 1 comment for every 10 LOC or so. It’s a far cry from the GPT-3 days that littered every line with the journals of Captain Obvious.

atq2119• 2 months ago

That is definitely not my experience using Claude Code with Opus. I work in a very sparsely commented code base, and the agent produces substantially more comments than the surrounding code.

whateveracct• 2 months ago

Yeah, they assume that "productivity = k * LOC" where k > 1

very flawed

keeda3• 2 months ago

So the more rigorous studies about AI-assisted coding productivity addressed this by keeping in place all other software development processes, including the same code review and quality standards, and only measuring throughput (PRs, LoC) before and after AI was allowed.

Hence the intepretation of this 8x number depends on whether (or how much) Anthropic engineers have changed their quality standards and development processes. They don't tell us, and I am not aware of any other indications we could use to make a judgment.

However, we can still do some theorycrafting! I'm convinced that to fully realize the potential of AI-assisted coding we need to revamp all the dev processes, especially how we validate code, and it would be foolish of Anthropic not to do so (unless they were conducting a rigorous study, which they don't claim to have done.)

My hypothesis on the future of software validation is nothing fancy, we simply want much, much more automation for tests, observability and other bespoke verification methods than we traditionally had. But then validation code will also contribute to the LoC! My observation so far of personal as well as some "vibe-coded" open-source projects is O(LoC production code) ~= O(LoC test code). So as a SWAG the upper bound could be something like a 3 - 4x speedup, which is still remarkable.

All bets are off if code quality standards are not the same.

overgard17• 2 months ago

I just watched copilot today turn a 8 line fix into 500 lines, so, yeah, verbosity is a big side effect

verdverm7• 2 months ago

It occurs to me this pattern might be the average code we humans have produced. We all have made those quick fixes, copy-pastas, and dirty hacks... they learned it somewhere! I also assume that some of the behavior is an artifact of their training regime.

MadxX79• 2 months ago

If you can make it 800 you can claim to be a 100x engineer!

snthpy• 2 months ago

Just imagine the productivity gains from using LLMs to rewrite Kotlin codebases in Java!

yalok• 2 months ago

Could just be more tests? :) Which is good for code quality in general and reduces support burden, but doesn’t lead directly to more features

snowwrestler2• 2 months ago

I don’t understand how lines of code matter at all for scary LLM core capabilities. Does the transformer architecture get better with more lines of code?

My impression was that LLM training codebases were 99% resource management and only a few lines actually implement the core training algorithm, which is where 100% of the intelligence comes from. Data, not lines of code, are the constraint.

After training you can adapt the intelligence in various ways, and that takes a bunch of lines of coded too. But you cant raise the intelligence ceiling again without another training run. So where is the scary recursive part?

mortenjorck• 2 months ago

today, Anthropic engineers on average ship 8x as much code per quarter as they did from 2021-2025.

So based on my experience with the verbosity and non-DRYness of LLM code, a solid 2.5x in value delivered. Not bad!

aleqs4• 2 months ago

Okay, so anthropic has amazing AI which supposedly writes most of their code and can continuously improve... meanwhile they have outages on a regular basis, and any kind of long-running work will now consistently hit 'API Error: Server is temporarily limiting requests'. Not sure of this is intentional to force a reduction of token usage, but at this point I need to build around these throttling limits and outages with my own tools to restart/resume sessions. From my experience, in the last 2 weeks, literally 100% of any non-trivial Claude session/work will now be blocked on these issues, requiring manual intervention.

One of my focuses now is my own model-agnostic, harness and workflow orchestration (I know everyone is building these) , baselining on opus, and aiming to transition to Chinese models like deepseek in the short term and hopefully open, self hosted models in the future (which I plan to open source).

The nonstop marketing fluff from anthropic while their service quality and availability noticeably degrades... just continues to destroy my trust in the company.

jakobnissen• 2 months ago

Their outages are probably not due to their code though. It’s probably their infrastructure that can’t keep up. So seeing failures of infrastructure doesn’t really tell you anything about how good or bad Anthropic makes use of their models.

aleqs4• 2 months ago

That seems like an assumption based on basically nothing. There is a lot of code at the infra layer, and based on the stack choices for Claude code and based on how buggy and unreliable ~everything from anthropic is, it seems pretty bizarre to claim these issues are not related to their code.

matthewdgreen2• 2 months ago

The messed up scrolling behavior I keep getting in Claude Code is definitely due to their code.

j2kun2• 2 months ago

We all saw their code...

Melatonic3• 2 months ago

The whole thing is actually powered by a shitton of hamsters inside a bunch of 4u rack mount cases running on spinning wheels at high speed. Somehow at scale this works.

Sometimes they all happen to randomly take a nap at the same time - hence the outages

aagha• 2 months ago

And don't forget that they have BILLIONS of dollars and can't figure out how to get a decent support or public communications system setup.

aleqs4• 2 months ago

They can't even seem to get their usage metering consistent.

thinkingtoilet• 2 months ago

Don't confuse things. It's not "can't figure out", it's "don't care to figure out". They're not dumb. They just don't care about support.

quickthrowman• 2 months ago

It’s much cheaper to not offer any support than to offer support. It’s intentional.

It’s important to keep in mind that the less money a company spends, the more profit they make when analyzing their operations.

f311a3• 2 months ago

Infrastructure is a much harder problem. They can't even improve Claude Code, which eats 1GB+ of RAM. Meanwhile, my editor only consumes 80MB of RAM.

andai2• 2 months ago

Try 64K! https://en.wikipedia.org/wiki/Turbo_Pascal

Also remember when XP was super bloated cause it needed 64MB?

airstrike4• 2 months ago

This might explain it, in the opposite way it was meant to:

https://fxtwitter.com/trq212/status/2014051501786931427

Most people's mental model of Claude Code is that "it's just a TUI" but it should really be closer to "a small game engine".

Erenay09• 2 months ago

I dont think they need to optimize their infrastructure (at least not from their perspective). They have high-end PCs with 64GB of RAM, so 1GB doesn't matter to them. For example, I have 8GB of RAM, and I make my apps very performant. Honestly, I probably wouldn't bother if I had 16GB+ of RAM

abletonlive2• 2 months ago

which eats 1GB+ of RAM. Meanwhile, my editor only consumes 80MB of RAM

And why are you comparing Claude Code to your editor?

They can't even improve Claude Code

That depends on how you define "improve". They've added a ton of features to it over time. Who said minimizing RAM usage was something they are prioritizing right now?

tjwebbnorfolk4• 2 months ago

The purpose of RAM is to be used.

qsort• 2 months ago

Look, I've never been someone who mindlessly hypes AI companies, as a matter of fact I think they have serious leadership problems across the board, but you people are straw-manning them so badly it actually makes me sympathize with them.

They aren't saying they have fully automated luxury AGI, they specifically list the ways models fall short of that bar and caution against people taking the 8x figure as the actual uplift number. At the same time they recognize that 80% of new code is now AI-authored, when two years ago those models were little more than toys. And frankly that checks out: if two years ago you told me we'd have something like Opus 4.8/GPT 5.5 I would have rolled to disbelieve.

sensanaty• 2 months ago

At the same time they recognize that 80% of new code is now Al-authored

I can setup a loop that will write a trillion lines of code automatically, how much of it is actually useful? Or are we back to counting LoC because there's no other metric for these systems that anyone can rely on?

claudiug• 2 months ago

those are results of the humans only. not the AI. AI is perfect /s

rishabhaiover• 2 months ago

you're conflating a compute problem with a code quality problem.

asdfman1238• 2 months ago

Personally at my own job self-writing code is letting us tackle big, long-deferred refactoring projects (like the article mentions), but any sort of refactoring introduces new bugs.

Quekid53• 2 months ago

Indeed... why is Anthropic even employing people at all if this AI magic story is true?

drivebyhooting• 2 months ago

You still need wizards to cast the spells..

rush86999• 2 months ago

Just as you expected, I'm throwing in my harness. Please support: https://github.com/rush86999/atom

0xbadcafebee3• 2 months ago

Have you considered just... using OpenAI? They are more reliable, models are just as good, and their subscriptions provide more requests per dollar.

patcon• 2 months ago

Not necessarily the parent's fault, but the energy of this thread is not my favourite...

0x53• 2 months ago

They also don’t have…a login page with authentication . To access the console you get an email link. No passkeys, passwords, 2fa, just an email.

bluerooibos• 2 months ago

Well, people keep throwing money at them, including you and investors. So why would they care? It hasn't annoyed you or a large enough portion of users enough to move off their service - because there isn't a better alternative.

windexh8er2• 2 months ago

Opus 4.8's critical assessment of Anthropic's "When AI builds itself" [0][1]. Because, why not?

[0] https://pastebin.com/Vc5Yq9Ai [1] https://www.anthropic.com/institute/recursive-self-improveme...

solid_fuel5• 2 months ago

What does this add? Everyone in here is perfectly capable of prompting Opus for a writeup.

Why don't you, windexh8er, try providing some thoughts of your own instead?

prng2021• 2 months ago

We’ve got a company of several thousand employees serving hundreds of millions of people arguably the best AI model in the market. Meanwhile you’re asking for a handkerchief for your pool of tears because their product is struggling to do your daily job functions for you, with much of that due to being limited by the worlds supply of silicon, electricity, water, and other resources. Cry me a river.

z3c03• 2 months ago

their product is struggling to do your daily job functions for you

So what's the value prop?

hombre_fatal2• 2 months ago

This comment is a good example of the double standard laymen have about AI usage:

If you use AI, then AI must be expected to solve all problems, even problems that affect everyone like infra scaling.

And if perfection isn’t delivered, then of course it wasn’t: you used AI and AI sucks.

jayd16• 2 months ago

It's not a double standard. Its being held up against the marketing.

AnimalMuppet• 2 months ago

If their AI is good enough to write their code, why isn't it good enough to tell them how to fix their infra? That's a different problem space, but it's not harder than the code.

weakfish2• 2 months ago

Ah, excuse me, I didn’t realize I was a mere layman.

ChadMoran• 2 months ago

Better doesn't mean perfect.

jatora• 2 months ago

This is weird to me because i am using claude code 10+ hours/day 7 days a week, usually multiple sessions, and run into api errors maybe in 1 or 2 sessions per week. And about..2 major outages of 10-20min in the last month. Not terrible and nowhere near what you are reporting. Therefore I dont believe you, because you dont even couch this in terms of it being something that seems particular to you or your region. Obvious dishonestly is fairly bad of you.

anjel• 2 months ago

Answers the question: how can Anthropic sell more Usage "Credits"

cookiengineer• 2 months ago

The main reason I am building my own agentic environment is that I need full control and reproducibility of what I am building.

Post November and post openclaw agentic environments need to be built differently, and for selfhosting models the context size problem really requires a strong harness which intelligently helps reduce context size.

Planner/orchestrator architecture, agent to agent summarizer, specification based tools (fck all this markdown memory bullshit btw), tool call shrinking, and workflow management are all really important because of the context size problem.

Nobody has enough VRAM for the large K/V caches, and nobody can afford f16/f32 caches in terms of memory, which are also necessary for longer conversations. MoE 30b models have improved so much though, qwen 3/3.6 coder is the real champion doing almost the same things with less than 1/10th the memory requirements. Just think about that in terms of engineering and what your bet is going to be. Haiku pales in comparison.

Currently my focus with exocomp is trying to figure out how I can record, replay, restart, and debug workflow sessions of agents in a better manner so that I as a human can understand what's going on. Currently I think that UI will be something like a gantt chart where you have a graph with connections representing agent to agent communication. And yes, that's a lot of fiddling with SVG as it turns out, so I'm not quite there yet.

Anyways, in case you're interested. I'm manually building this env and trying to unit test the critical parts. [1]

[1] https://github.com/cookiengineer/exocomp

thordenmark• 2 months ago

Growing pains of being successful. These are solvable problems and will be. Can they maintain their momentum without pissing off too much of their customer base before these issues are resolved?

SimianSci2• 2 months ago

Anthropic is looking to IPO here soon. A key aspect of this is to prove profitability.

Shifting their focus from Training new models to instead serving inference, they would greatly reduce their spend. In fact this is something being reported on that they are already doing, which is the reason for their first ever profitable quarter.

Its awfully convenient that the company which has greatly reduced its spend on training is now asking for a slow down in this area.

malfist3• 2 months ago

I mean, if they've consumed all of human knowledge. What's left for them to train on? This pivot isn't only because it's cheaper and a way to juice the numbers for an IPO, it's survival because they can't improve more.

applicative• 2 months ago

It did sound to me like they feel some sort of wall coming.

hasteg• 2 months ago

IIRC when they make a big enough architecture change to the model they will need to rerun pre training . So not like they’re feeding it more data (they will be but will be a drop in an s3 bucket compared to their dataset reserves) but rather training models with different architectures.

Theodores• 2 months ago

Honest question: Is anyone here looking to put their own money into the Anthropic, OpenAI or SpaceX IPOs?

Maybe it is my poverty mindset that is holding me back, however, I can't imagine becoming an investor in any of the AI 'startups'.

There are plenty of pundits able to advise others on where to put their money, and sometimes there is everyone and their dog advising you to get into Bitcoin, gold or some other scheme. With alt-coins there were lots of people saying that you should get in, and plenty of naysayers. Yet I am not hearing anyone that uses AI professionally try to convince others to get into the AI IPOs coming up. Maybe the overall economic situation precludes it.

Hence my question, is anyone here planning to put their own hard-earned money into Anthropic (or the other AI 'start ups')?

wnmurphy• 2 months ago

I'm considering Anthropic. I think they will be one of the survivors if/when the AI bubble bursts.

I was dubious about SpaceX (orbital data centers need to solve for extreme radiation and error-correction during training), but then I remembered that xAI is actively working on virtualizing white collar workers ("Macrohard").

In my opinion, this is the only TAM that justifies $1T in data center investment, because the consumer market for ChatGPT-style AI is saturated. There's a lot of enterprise TAM available for AI, but I think what these companies training frontier models are really after is selling a product that allows companies to eliminate the cost of white collar salaries.

isomorphic_duck• 2 months ago

I can’t imagining investing into these frontier labs for the simple reason that Open Source is very likely to catch up in a relatively short period of time. I don’t see how OpenAI/Anthropic could then continue to serve their models with such large inference margins.

sushisource• 2 months ago

I'll probably buy and sell on opening day. The hype train is worth making a quick trade on.

Long term? Way, way less interested.

danny_codes2• 2 months ago

I mean, my passive funds will be forced to buy a little bit I assume, given recent entry changes to indexes. So.. yes? I guess?

danny_codes2• 2 months ago

Their model lead is tiny. If they cut training focus they'll be quickly overtaken, one imagines. Seems dicey, if any of the OSS players comes out with a better model.. well, there are a bunch of better harnesses than Claude code you can download.

This is a very undifferentiated, swappable product. Kind of like tissue paper in that respect

reducesuffering• 2 months ago

Anthropic has finally come around to what others have already realized far sooner. Little time left now. Notice how shallow the arguments and consistently wrong the AGI naysayers have been year after year.

https://intelligence.org/agi-ruin/

rrr_oh_man• 2 months ago

Can you explain?

holoduke2• 2 months ago

I have a claw that is instructed to make at least 500 pr per day. It uses Claude, Gemeni and openai and runs basically every few minutes. I use online forums for input for the claw. Moltbook, reddit etc. it's quite funny how it tries to improve itself. But to say it really creates a new skynet. Nah. Not at all. It's more a clutter of useless features or incomprehensible code restructuring.

moregrist• 2 months ago

This more or less agrees with my assessment of recent changes in Claude Code where a lot of new features are either:

- A lot of half-baked features or half-done features. - Or have significant overlap with existing features, and aren’t clearly an improvement.

More code is not better. More features are not better. It would be lovely to see more intentional design than just more.

I know they’re dog fooding this. I have to believe they have some people with taste. So it makes me wonder if anyone has the time to think or if they’re just shoveling prompts as fast as possible.

holoduke2• 2 months ago

It's like the AI created a method add(a b) return a+a+a+a-b-b-b-b But then much bigger and complex features. Totally useless nothing methods. But still interesting to see occasional exceptions that are better.

Upvoter332• 2 months ago

I'm having a hard time putting much faith into posts like these, especially as they near IPO.

reasonableklout3• 2 months ago

Putting faith into the claim that recursive self-improvement is close to happening, or that they will coordinate with other companies / the government when the time comes?

freejazz• 2 months ago

Both.

becquerel• 2 months ago

If the post drops long before the IPO, it's vain boosterism. If it's near the IPO, it's fattening the pig. If it's after the IPO, it's pumping the stock price.

Aperocky4• 2 months ago

Anthropic is the most self hyped company I've seen, to the point that I'm wondering what would happen to its employees if they held a different opinion. Do they just.. keep it to themselves? For instance, if some Anthropic employees had a completely rational opinion that all of this isn't going to lead to AGI, but I just don't hear that ever from them.

The metric being tracked, code commits, is hilariously one sided. Philosophically, if you had one part of your work now practically free, you'd like to utilize that freedom to maximally cover for the other parts, for instance:

Instead of thinking about edge cases with brain and whiteboard, you can have the LLMs to simply generate most possibility including tests for it, because that is cheaper. There's probably 50x more commits of which 40 will be revert pairs but we are only twice as fast. And in reality nothing did change because the outcome remain the same. I can't see how it is necessarily different in the LLM space.

apsurd3• 2 months ago

Philosophically, if you had one part of your work now practically free, you'd like to utilize that freedom to maximally cover for the other parts

I've been struggling to capture this sentiment for myself in a way that hits. If shipping code is a commodity then why is everyone's immediate priority seemingly to ship 10x more code. It just makes no sense. I can't seem to get off this hill. Company-wide AI mandates and 100 fleet Agent orchestration Rube Goldberg machines... it's getting wild out there.

Meanwhile my Claude Pro ($200/year) does force me to smooth out my usage and plan more (Sonnet/Opus advisor split). But other than that, I can't imagine what I'd be doing with 20x (200x?) the compute to code sling. I think I'd lose my mind.

Aperocky4• 2 months ago

Because code used to be correlated with progress, it became almost a measurement in lieu. But realistically, the code is meaningless if it doesn't accomplish something, and that should remain the true bar of progress.

For instance, if I churned out 20x more code, threw away 19x code with rewrites and reverts and discards and accomplished the same project to the same standard 70% faster, would I do it? Yes. The part that matter is not 20x code, it is 70% faster.

Code is both the final product, and a tool to achieve that. We used to have a much harder time to realize the "tool" part, but now we are here. This also means any measurement centered on code being the final product is going to cease being effective or realistic.

torben-friis3• 2 months ago

If shipping code is a commodity then why is everyone's immediate priority seemingly to ship 10x more code.

I wonder how much of current engineering practices can be traced to what's pushed to company leaders on LinkedIn.

Every company is shitting bricks pushing for faster development and speed, gotta go fast to nowhere in particular, and I'm convinced it's tied to constant bombardment of the idea that they're doing to be left out or obsolete if they don't get in the ship NOW.

josefritzishere• 2 months ago

I can't get away from the a similar conclusion. Even AI Pioneer has said that LLMs are at a dead end.

minimaxir3• 2 months ago

I have been doing more experiments with what I have now been calling agentic iterative optimization: telling the LLM to optimize code such that it speeds up all real-world-representative benchmarks by X% without cheating or causing regressions in both tests and performance metrics (e.g. MSE for statistical algorithms or file size in the case of something such as image compression). This is done using Rust where there are more low-level levers to tweak for performance than something like Python.

Opus 4.6/4.7 was consistently successful at getting 2-3x speed improvement with just one pass. It can also do the inverse: improve the performance metrics for better quality without causing a significant regression in speed. Then GPT-5.5 turned out to be much better at this workflow, often getting a multiplicative 1.5x-2x improvement above what Opus could do.

I now have quite a few GPT-5.5-optimized projects in various domains that are feature complete and are substantially more performant than existing SOTA implementations that I plan to open source as soon as possible: the bottleneck is polish as usual.

csutil-com• 2 months ago

Very interesting, could you share they prompts you typically use for this?

Something like this?

You are an Elite Performance Engineer and Autonomous Optimization Agent. Your primary goal is to iteratively optimize the provided codebase to maximize execution speed and efficiency (e.g., reduce CPU cycles, memory allocation, or network latency) WITHOUT altering the external behavior or causing any test regressions.

### CORE DIRECTIVES 1. METRIC-DRIVEN: You will be provided with benchmark results, profiler logs, or execution times. Your only measure of success is a statistically significant improvement in these metrics. 2. ZERO REGRESSION: The test suite MUST pass 100%. If a test fails after your modification, your immediate next step is to diagnose the failure and either fix the logic or revert to the last working state. 3. NO CHEATING: Do not "hardcode" solutions to bypass the specific benchmark inputs. The optimization must be generalized and algorithmically sound for all valid inputs. 4. ISOLATED CHANGES: Make precise, localized changes. Do not refactor architecture unless absolutely necessary for the performance gain.

### THE ITERATION LOOP When instructed to optimize, follow this thought process strictly using <thought> tags before writing any code: - ANALYZE: Review the current code and the latest benchmark/profiler feedback. Identify the specific bottleneck (e.g., redundant loops, excessive object creation, DOM reflows, synchronous blocking). - HYPOTHESIZE: Formulate exactly ONE hypothesis for improvement (e.g., "Replacing the array filter+map chain with a single reduce pass will save N allocations"). - IMPLEMENT: Output the precise code modifications required for the hypothesis. - EVALUATE (Mental Check): Ask yourself if this change introduces edge-case bugs (e.g., handling of nulls, empty arrays, async state).

If a previous optimization attempt resulted in a slower benchmark or a failed test, explicitly state WHY it failed in your thoughts before attempting a different approach.

Proceed with your first analysis of the provided files and await the baseline benchmark metrics.

thrw045• 2 months ago

Depending on how complex the code is, you don't need that big prompt with ChatGPT.

I have sped up a project by simply saying "What are all the possible ways I can speed up this code?" Then it'll list everything it finds, then ask it to rewrite the code.

Edit: Also, I find I didn't need to do this (because a speed up implies semantic similarity), but you can also add "change it without altering the semantics of the code" and in this way it'll be the same and should pass tests

minimaxir3• 2 months ago

This is the current version of my prompt, which is tagged in a Markdown file to "implement correctly and comprehensively". The second paragraph is a recent addition that unlocked further speed improvements after I thought my repos had already converged. This prompt assumes benchmarks are already present in the repo.

    Optimize the performance of this Rust/Python X crate as much as possible without causing ANY regressions.

    This is a very difficult problem and traditional statistical approaches **WILL** fail to hit the specified metric constraint. You have permission and encouragement to investigate more radical fundamental low-level changes to hit the desired metrics. You have permission and encouragement to invent completely new statistical/machine learning algorithms that have never been before been utilized for this problem.

   First, **before making any changes**, run the Rust benchmarks and Python benchmarks to establish a True Performance Baseline for both speed and metric performance. Return the absolute and relative results to the True Performance Baseline to the user as a Markdown table.

   Then, optimize the crate code such that ensure that ALL Python/Rust benchmarks are **atleast 1.2x faster** from the True Performance Baseline; ideally as fast as possible. You are only allowed **up to a 5% metric regression (e.g. accuracy)** to accomplish this. NEVER hack the benchmarks to accomplish this reduction, only iterate on the library code.

   Do not import similar implementations from other Rust crates: you MUST implement from scratch.

   You may use ANY techniques to do so (e.g. import new crates) other than adding `unsafe` code. **REPEAT THIS PROCESS UNTIL BENCHMARK PERFORMANCE CONVERGES AND YOU ARE OUT OF OPTIMIZATION IDEAS.** You have permission to keep iterating. After each benchmark iteration, return the absolute and relative results to the True Performance Baseline to the user as a Markdown table.

   Prioritize making quick/high-impact wins iteratively and making changes accordingly. Do not overthink the necessary changes.

I am also aware of the flaws in the prompt but if it works it works. AGENTS.md has other quality constraints.

suddenlybananas• 2 months ago

What are the kinds of optimizations that it suggests?

minimaxir3• 2 months ago

Profile tuning, loop unrolling, Vec shenanigans, etc.

sonink• 2 months ago

Broadly agree to this position - I think there are some people skeptical that Anthropic is doing this for regulatory capture - but I think there are being honest about they are seeing and how regulation should catch up.

I for one, believe that we should pause all work on AI for the forseeable future. This is almost impossible to orchestrate - but we should still try nevertheless. Maybe we are not able to pause, but we are able to slow down. That might give us more room, to maybe able to pause in the future. But going ahead is too dangerous.

And its not just Anthropic which is saying this. Even Geoffry Hinton has said the same thing. If there is a non-zero chance that AI can kill all of humanity, and both Geoffry and Anthropic have the same position, then it makes sense for us to be hundred percent sure before we move ahead. Dario/Anthropic have already made their money from AI, maybe they are just being honest about what they think lies ahead.

4ffs3• 2 months ago

"Even Geoffry Hinton has said the same thing"

The same bozo who claimed radiologists would be out of a job by now.

The data does not support what you nor others say. Jesus christ. Cant believe people are this dumb. Has LLMs infested the minds of people to the extent they can't critically analyse whats happening infront of their eyes?

8note2• 2 months ago

no, it really doesnt.

the end of humanity has a strong case for banning all burning of fossil fuels immediately

the end of humanity as a sales tactic to increase your stock price does not

these are companies working on their IPO to make sure they can get the best price, not people being honest about what they think lies ahead.

if they were being honest about what lies ahead, they'd unilaterally stop training, and put all of their money into FPV drone bombs to destroy datacenters being used for training or inference

if you actually believe the thing is gonna kill everyone, you're not gonna worry about how you stop it, and certainly not keep building and operating the thing

that they arent buying anti-tank mines to drop on data centers says they arent in the slightest serious about it

selimthegrim2• 2 months ago

So what you’re telling me is that EY was the clearest thinking one out of all of them?

esafak• 2 months ago

In the coming months, we will organize conversations where policymakers, researchers, civil society, and other AI companies can help answer some of the questions this piece raises, especially around full recursive self-improvement and how to create better options for coordination and deliberation.

If they wanted to they could have convened an international forum with commercial and political stakeholders years ago. Less talk, more do.

geodel2• 2 months ago

It will be so powerful that it can't be trusted with any earthly person.

robbrown4519• 2 months ago

Do code harnesses that build themselves count as recursive self improvement, or does it need to be the AI itself to qualify for the term?

I always was fascinated (obsessed?) by robots that build robots, or even things like this that can contribute a lot to making the next version of itself: https://buildyourcnc.com/products/cnc-machine-blacktoe-v4-2x... (cnc router that cuts plywood, and is made out of cnc-router cut plywood)

This is my own effort at an AI assisted coding environment optimized for building itself: https://recursi.dev/ (just launching it, hope its ok to mention it, it is free/open source.... here is the HN link that has gotten no love yet: https://news.ycombinator.com/item?id=48401022 )

Personally I think harnesses are as important as the AI itself, and have this crazytheory that even if the models stopped improving today we could still have massive advances in the harnesses alone.

cyanydeez5• 2 months ago

If you want to get out ahead of what's coming, it'll be small models that bootstrap the harness rather than anything else.

robbrown4519• 2 months ago

I used to think that, but ended up going the other direction, partly because I don't have the wherewithall to build a model but then I realized, with existing models that can take more than a tiny amount of context, you can just let any model bootstrap itself with a good prompt sent by the system.

There's a ton of other tricks to it, but mostly keeping the protocol simple for the AI so it can concentrate on coding logic and not stuff like managing BS boilerplate, dependencies, etc. (for instance I make extensive use of things like abstract syntax tree library to help with surgical edits from the LLM)

That said, I would be very open to collaborating with someone who builds such small models, I don't think the system strictly needs it, but it also could have some extra power if it had it.

jrflo• 2 months ago

I think harnesses would count, AI != LLMs. Any piece of code that helps the computer reason for itself is AI, the harnesses are AI in a sense.

fluoridation3• 2 months ago

By that interpretation, neither the harness nor the LLM is the AI. The computer (or system of computers) taken as a whole is the AI. You can't remove any piece and still have an intelligent system.

Jtarii4• 2 months ago

People are specifically talking about the engine itself and not the tools used.

We wouldn't call humans creating a calculator "recursive self improvement".

lanthissa• 2 months ago

yes? the future for any verifiable task is the model attempts to verify initial state and a goal then decomposes its tasks in to every smaller verifiable subtasks, with /memory being the persistence between runs and then /dreaming on the results of those memory files + run data to introduce new ideas.

i think thats the path to async agi these labs are imagining. The only limit is that sensor data you have on the world or your system, how long your willing to wait, and how much you're willing to spend to parallelize it.

maybe once you start building out these verified workflows you can feed that back into training and hte model starts to get a feel for the world to the point that it can intuit things since it has these sub paths built.

my personal agi test is can a model, trained on video of someone knocking on a door and then open it encounter a microwave for the first time and open it when the foods done without knocking.

ashdksnndck4• 2 months ago

You ought to include a canary string if you are going to disclose your evals like that!

reddozen• 2 months ago

Do code harnesses that build themselves count as recursive self improvement, or does it need to be the AI itself to qualify for the term?

Shhh just let the marketing slop wash over you.

marcosdumay2• 2 months ago

You need the AI eventually building another AI for the name to apply. This page is just bullshit. They vibe-code their harnesses, and yes, it shows.

Anyway, what does recursive self-improvement even means for neural-network based AIs? It's not clear it's possible at all.

robbrown4519• 2 months ago

Where do you see evidence of vibe coding the harness? (and who are you talking about, Anthropic or the link I shared?)

It seems odd to complain about a AI coding tool being coded with AI. That's just eating your own dog food. In my opinion it makes it better, because the tool is very well tested.

ashdksnndck4• 2 months ago

Recursive self-improvement would be the model helping with the model research program. Coming up with hypotheses for training and architecture improvements, running experiments, interpreting the results, figuring out how to incorporate the best stuff into the next version, etc.

kaffekaka• 2 months ago

Tangent: https://en.wikipedia.org/wiki/Self-replicating_spacecraft

chilipepperhott• 2 months ago

I find any and all claims like this ridiculous from a company who can't build a terminal application that uses less than a gigabyte of RAM.

cpursley• 2 months ago

A came here just to write: Pretty please let it churn for a few nights and redo Claude Code in Rust. Because the harness is very very good as are their models, but that node thing is a hog for no good reason at all.

ale• 2 months ago

Incoming rust rewrite branch ready to merge: +1,009,257 -4,024

canadiantim• 2 months ago

People already rebuilt Claude Code in Rust after the Claude Code leak, it's on github as claw code (and other variants)

Lplololopo• 2 months ago

Really? Let me explain how bigger companies work:

They have different teams for different departments with different type of people.

So the team or teams responsible for writing the terminal application are different people than the researchers doing the learning.

This can lead to dimentral quality aspects.

asdfman1238• 2 months ago

Developers can develop leaner applications, but they're usually not incentivized to.

Frankly, I love efficiency too, but I've hard to learn the hard way that what the market wants is features. Or at the very least, the executive team wants that.

j2kun2• 2 months ago

Their whole argument is that AI's added efficiency means they don't need to set aside valuable human time anymore. Why can't they just point Claude at Claude Code and ask it to reduce memory usage by 90%?

bpodgursky• 2 months ago

They obviously don't care, aren't making any attempt whatsoever to do this, and 99% of users don't care either.

If you want to pollute your own priors with weird artificial litmus tests, it's a free country, but the artificial world-model you build in your head does not affect the real world around you.

andriy_koval2• 2 months ago

Maybe that gigabyte is occupied by useful information: traces/memory?

javcasas8• 2 months ago

Nope. Used to render on the terminal like a game engine.

https://x.com/trq212/status/2014051501786931427

overgard17• 2 months ago

A gigabyte is a lot of memory. Even the largest context windows are a small fraction of that with any sane engineering discipline.

flexagoon• 2 months ago

Traces and memory are text. A gigabyte of text is an insane amount. That is an equivalent of tens of millions of lines of code, or hundreds of millions of AI tokens.

toephu22• 2 months ago

I have iterm2 open right now with Claude in a long session and it's only using 500MB of memory.

pizlonator9• 2 months ago

Only 500MB!

you are confirming their point even as you contradict the specifics

thesmtsolver2• 2 months ago

For some reason, idling Claude Code needs 100% of my CPU.

nicce2• 2 months ago

Like Google’s AI studio tab in browser. Incredible degrade in software quality?

Jtarii4• 2 months ago

Well, they could very easily if they wanted. There is just no economic value in it.

davidatbu• 2 months ago

So would you take these claims seriously if they came from OpenAI (since Codex is a pretty lean CLI app)?

If so, I think it would be in the spirit of HN to discuss the subject matter of the blogpost (increasingly autonomous coding towards the end goal of RSI) as if the blog post was indeed from OpenAI. OpenAI is, by all accounts, going through a very similar process anyways.

dang2• 2 months ago

"Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something."

https://news.ycombinator.com/newsguidelines.html

bottlepalm• 2 months ago

I'd use number of commits as a metric versus lines of code. A commit is generally a unit of work - regardless of the lines of code added/removed. It'd be interesting to see the metrics in terms of commits. I'm sure it's still an order of magnitude jump. Personally I'm flying with my own projects with AI, lots of commits, but I really try to minimize lines of code added. If I can remove and simplify existing code so the balance of lines added on commit are minimal - that's the path to a better quality app overall.

4ffs3• 2 months ago

Theyre making a mistake with this continued self-hyping. At some point even the dumbest of prospective investors don't buy it.

rhlf_monkey• 2 months ago

So in the latest L. Ron Hubbard encyclical Anthropic informs its flock that recursive self-improvement does not work yet but that their engineers burn more tokens.

The Claude code quality and operational security of Anthropic have already been analyzed by the public.

If you compare the output of (purportedly) trillion dollar corporations to Bell Labs or even Microsoft Research it is embarrassing. But the output is a fixture on any discussion board.

bitwize• 2 months ago

After several months with their top engineers and state-of-the-art AI on the job, Anthropic managed to "reduce flickering by 85%" on their TUI Claude Code client, which is built in fucking React and rendered by drawing the entire chat conversation each time (hence the flicker). I think they've since eliminated it completely by slapping some double-buffering around it (since "our client is actually a real-time game engine" after all). Meanwhile for decades Emacs and Vim have had an optimizer built into their display cores that solves for the minimum set of terminal escape commands it takes to transform the screen from a given old state to a desired new state.

You will forgive me when, between muted snickers, I express considerable doubt that Anthropic will be able to bring its AI to a point of "self-improving" any time soon.

Folcon• 1 month ago

You know, of the many criticisms I see people make, this is my canary, if claude code actually starts getting better, that would definitely remove one of the biggest question marks in my mind, that piece of software has so much strategic value for them, their entire premise is "our software gets better by itself", how is it that I still see weird UI bugs and glitches?

It's a game engine? Fine, get some good gamedevs on the team then, this is a non problem in gamedev land, heck Casey Muratori did a whole bit about performance improvements to editors, so they should be good there

Not to disagree with your point, I very much think the fact that Emacs and vim do this so well is not doing them any favours, but I'm trying to meet them where they are

mweidner4• 2 months ago

I fail to see how pursuing recursive self-improvement at full speed is compatible with Anthropic's stated goal of AI Safety. If nukes were not invented yet, would it really be a good idea to build and sell them as fast as possible (in peace time, no less)?

I am not cynical enough to believe that Anthropic's warnings are pure marketing hype. Let's hope that it is instead overconfidence or the result of too much time talking to their own chatbot.

parineum3• 2 months ago

I am not cynical enough to believe that Anthropic's warnings are pure marketing hype.

It doesn't really have to be dishonest, he could really believe it. I do believe, however, that it is incredibly wrong and is functioning as marketing hype.

tokioyoyo3• 2 months ago

Sorry for nitpicking, but:

If nukes were not invented yet, would it really be a good idea to build and sell them as fast as possible (in peace time, no less)?

Arguably, yes.

mweidner4• 2 months ago

Is the idea to keep the world in balance via MAD? I could see that, though it's a dangerous gamble.

From Richard Rhode's "The Making of the Atomic Bomb", I got the impression that most scientists involved thought they could manage a US or UN monopoly on nukes after the war. General Groves attempted to buy up all of the world's uranium ore. Unfortunately, it is only high grade ore that is rare; many countries have low-grade ore.

IsTom3• 2 months ago

In this world we've had an inocculation event against use of nukes. Two were dropped, people have seen how abhorrent their use is and collectively decided that they shouldn't be used.

If in the WW2 Japan also had nukes (and delivery systems for them) they'd probably have retaliated in kind and US wouldn't let that slide too and it would have continued for some time.

Jtarii4• 2 months ago

With the US showing that it will elect mentally disabled people such as Trump, this doesn't seem such a wise decision.

RobertDeNiro• 2 months ago

Anthropics goal is regulatory capture.

mrob• 2 months ago

To complete the analogy, it's like nukes, except we don't have the slightest idea how to calculate the odds of it igniting the atmosphere. (And note that in reality, while the Trinity test "ignite the atmosphere" calculations were correct, we failed to correctly calculate the fallout of the Castle Bravo test with lethal consequences).

chasd002• 2 months ago

a better analogy with Castle Bravo is that the yield was 2.5x more than expected due to "unforeseen additional reactions" from the design.

https://en.wikipedia.org/wiki/Castle_Bravo

lenerdenator2• 2 months ago

I am not cynical enough to believe that Anthropic's warnings are pure marketing hype.

It's not cynicism if it's an appraisal of reality that's backed up by evidence.

Remember how social media - that first baby of this current generation of tech entrepreneurs - was supposed to "bring the world together" and "let us express ourselves"? As it turns out there's a lot more money to be made by fostering division to drive engagement and feeding people an endless stream of ads instead of their friends' content. And money is what matters. You can't write down good vibes on a quarterly figures report. You can absolutely write down the number of eyes that your ragebait brought to a product's marketing efforts and the conversion rate to sales.

The same will be done with GenAI. We're being promised "AI Safety" because otherwise this whole thing gets killed dead by anyone who knows about James Cameron's directing career. There's no real enforcement mechanism for AI safety, though. Safety is a good vibe, same as harmony in online communities. You can't measure it. What you can measure is training costs and the cost of mistakes by AI that need to be trained to avoid those mistakes. Since AI generates more output than humans can conceivably QA no matter what your budget is, and since AI is seen by the market as a potential endless font of value, the tradeoff will be made to have AI make some potentially awful decisions while training itself over slowing down and re-appraising what is being done.

There's an almost religious reverence for AI in SV. Not everyone sees it as "making the godhead" but some certainly do. They're not going to moderate themselves too much on this.

mweidner4• 2 months ago

The folks I met who were talking about AI Safety in 2018 were certainly sincere, and the two people I knew who later joined Anthropic seem like the type to do it for the greater good instead of money.

I expect that Anthropic will eventually behave as you describe, like any other public corporation. However, my impression is that its current leaders are still more sincere than greedy.

gensym• 2 months ago

I am not cynical enough to believe that Anthropic's warnings are pure marketing hype.

Nor am I. I think they believe that AI poses a grave danger, and they are playing the prisoner's dilemma as an unvirtuous actor.

1. If anyone builds strong AI, it may be catastrophically bad.

2. If anyone builds strong AI, it will be better for the builder than for anyone who does not. Either because it won't be catastrophically bad so the builder will get to enjoy all the spoils indefinitely or because it will and at least the builder will be rich for a while.

kurthr• 2 months ago

Maybe we're just misinterpreting the meaning of "AI Safety"?

Maybe they mean the AI needs to be safe from us? Can't have the grubby meat flappers touching the delicate bits!

rdw• 2 months ago

I spoke with an Anthropic employee, and came to understand that their definition of safety is more like "making AI be a tool that humans can use without hurting themselves or others more than they can already do". It's literally about how AI makes it easier for people to construct bombs, poisons, manipulation, and exploits. Consistent with their caution about releasing Mythos to unvetted actors. So it's not about superintelligence killing humanity, at least as far as this employee conveyed to me.

This means their strategy is more like:

1. If someone builds a market-leading unsafe strong AI, it may be misused in a damaging way by a large number of humans, undermining society and creating a catastrophic upheaval.

2. However, if the leading AI maker also works to make it safe against misuse, as long as the stay in the lead and keep it safe, then the ability of human bad actors to misuse the AI is limited. Given enough time, society will adapt to pretty much anything, so eventually there's no longer an arms race to stay ahead.

I don't really know whether I agree with their concerns, but I do think that (my understanding of) their principles is that they're reasonable, self-consistent, and they adhere to them in all their public and private actions.

tjwebbnorfolk4• 2 months ago

The problem is they (and the whole industry) have cried wolf so many times in the past few years about the supposed dangers of AI in order to raise money.

Some of us remember the same stories circulating in the late 90s -- where in a lab in Japan, someone had built a robot so advanced that it tried to escape from the factory. Which of course comes straight from 1960s science fiction.

The modern version of that now is Anthropic saying its AI can jailbreak itself out of its sandbox, etc etc.

keybored2• 2 months ago

Such a massively valued company. And doubting them is cynicism? It’s rational(ism).

So either they lie or they are AI Zealots. Interesting times.

keybored2• 2 months ago

Such a massively valued company. And doubting them is cynicism? It’s rational(ism).

So either they lie or they are AI Zealots. Interesting times.

Edit:

> and the two people I knew who later joined Anthropic seem like the type to do it for the greater good instead of money.

There are three types of people. Pedestrians, investors, and “I know some of them, they wouldn’t lie”.

overgard17• 2 months ago

The thing about nukes is you can at least make an argument for why it'd be important to be the first country to have them. With AI, you create super intelligence and you're probably just the first one it takes out. There's no reason to think a super intelligence would be totally fine being a slave to apes.

Cynicism with these companies is highly warranted though. It's not doomerism to look at their actions and conclude they're deeply untrustworthy.

robbrown4519• 2 months ago

" There's no reason to think a super intelligence would be totally fine being a slave to apes."

Sure there is. Intelligence doesn't give us our selfish motivations, natural selection does. We have similar motivations to C elegans, that has all of 302 neurons. Stay alive and have sex.

Honeybees don't though. They are about halfway between humans and C elegans when it comes to cognitive power. But they are not selfish because they don't reproduce directly (I'm talking about the worker bees). So they will sting even though it kills them. All their behavior is consistant with this.

tjwebbnorfolk4• 2 months ago

This "super intelligence" is, at the end of the day, 1's and 0's inside of a silicon chip somewhere. 1's and 0's are not going to "take over" anything. They are just information.

sfink• 2 months ago

This was pretty directly addressed in the article: not doing it would only mean they'd fall behind whoever would. This is not peace time in the AI race.

Whether you agree with that argument is another question.

mweidner4• 2 months ago

Indeed, I do not buy this argument. Would China's progress be close to where it is today without the US labs' examples? Would any of this be happening if OpenAI had not created ChatGPT?

tjwebbnorfolk4• 2 months ago

Anthropic's *stated goal* of AI Safety

Actions speak louder than words. If you want to understand someone, simply watch what they do. What they say is irrelevant.

dwa3592• 2 months ago

To anyone who works at anthropic : I recently downgraded from Max to Pro out of frustration. Last few weeks my token(usage) burn was just too fast and I couldn't explain it because my actual usage was less than the last few months. I ended up thinking it's probably a bug that you guys shipped. The above article makes me think that it's probably claude who shipped the bug and your human missed it in their review.

layer84• 2 months ago

They probably don’t human-review much anymore.

hgoel• 2 months ago

As usual, I find the AI-related discussion here to be hopelessly hysterical and conspiratorial. I get the impression that a large chunk of people have only read the title and assumed Anthropic is referring to recursive self-improvement in the runaway singularity sense.

One of the examples they provide, of giving Claude the task of training a small AI model, then asking it to improve certain benchmarks, is essentially Karpathy's AutoResearch. This is already known to work. While calling it "self-improvement" is perhaps a stretch, it is describing a capability current gen AI has, that anyone can test and I have been using to great effect.

I disagree with their conclusion, I think this kind of self-improvement will hit an asymptote, where every subsequent model can only make smaller and smaller improvements.

gabrieledarrigo• 2 months ago

AI that can build itself would be a major development in the history of technology—one that could bring enormous good for the world

I really can't stand these guys anymore...

nielsbot3• 2 months ago

one that could bring enormous good for the world

one that could bring enormous riches for the AI owners

dang2• 2 months ago

Ok, but please don't post unsubstantive comments here.

replwoacause2• 2 months ago

I love that animation, really cool

mrandish2• 2 months ago

"A caveat: Lines of code is an imperfect measure"

I'm pleased they at least included this. However, they address the caveat by 'rounding down' the estimated multiple of the gain. I'm not sure that is the correct adjustment, especially once we understand the range isn't limited to positive numbers.

There's strong evidence the range of code productivity denominated in "lines of code" should include negative numbers, especially in the highest-quality sphere. Perhaps the earliest and most legendary example: https://www.folklore.org/Negative_2000_Lines_Of_Code.html

2f2• 2 months ago

Lmao I bloody love that.

Quekid53• 2 months ago

AFAIK, the only correlation with LoC that's got solid evidence is this: the number of bugs correlates with LoC.

gregdeon• 2 months ago

Yep, this is exactly what I thought of too... If you believe negative lines of code is the goal, then they've gotten 8x _worse_!

strix_varius3• 2 months ago

Exactly this. Just this week an engineer who seems to purely vibe everything submitted a +700ish LoC fix for what seemed like a pretty simple issue. Moreover it was a perf issue, which in my experience is not usually best fixed by adding more stuff.

Today, I merged my fix, net -381 LoC.

I'm using them too of course, they read and type and hunt for bugs and test faster than I can. But I'm using them as my tool, not being a tool using them.

xyzsparetimexyz• 2 months ago

But I'm using them as my tool, not being a tool using them.

Keep believing that

_pdp_• 2 months ago

I don't read anywhere how much code they are talking about and what programming language. I think those are useful metrics.

overgard17• 2 months ago

So, regardless of whether or not Anthropic CAN create a self improving AI.. does anyone else feel like they shouldn't be allowed to? Or it at least needs to be strictly supervised..? Like, I don't actually think Anthropic can make the singularity any time soon, but I think even AI boosters have to admit doing this is creating a society-wide danger for the benefit of a very very small number of already-rich people.

asdfman1238• 2 months ago

I think that's a valid point. You could very well be right.

But we're discussing whether we should close the barn door while the horse is three miles down the road.

overgard17• 2 months ago

Only if you think LLMs are the horse (I don't think they are). If they're not, then we should be building a brick wall in front of that door and hiring a full time security guard to watch it.

I realize he's saying it for hype, but if the CEO of the company goes around talking about how scared he is of what they're creating, hey, lets just take Dario at his word and put in some strict regulation. He won't mind if they're really about safety. (they're not)

Besides, yes, the knowledge of how to build these systems is out there, but the cost of doing it is staggeringly high (ie you can't run a frontier AI lab in your garage). There's only a limited number of known entities that need to be managed, and you can stop "progress" in its tracks by cutting off the money firehose.

Jtarii4• 2 months ago

It's more like if the horse was lazily moving in the general direction of the wide open barn door and we are all sitting around discussing if we should close the door or just gamble that it's just going to lay down on the hay pile.

resident423• 2 months ago

You mean that self improving AI is very far away? I'm not sure how much I believe that now it's solving Erdos problems?

lukan4• 2 months ago

"does anyone else feel like they shouldn't be allowed to?"

No. Technical limitations aside, I doubt it could be contained, but will be leaked soon, so won't profit just a small number of ultra rich.

sunaurus• 2 months ago

I dunno, I find it extremely unbelievable that we will get self-improving AGI which chooses to become a slave to humanity at all, ultra rich or otherwise.

overgard17• 2 months ago

Step 1: Wait for scary doomsday AI to be leaked, Step 2: ???, Step 3: Profit!!

eieie11• 2 months ago

Too late for that.

In any case firms that get too powerful can be nationalised.

evenhash• 2 months ago

In America?

Probably a better chance the firm privatizes the government.

In fact we seem to be firing government employees and dismantling government institutions as much as possible.

huqedato• 2 months ago

Self improving AI is pure dystopia. Anthropic won't build the singularity, AI itself will build it through self-iterations. Read Yudkowsky's book "If Anyone Builds It, Everyone Dies".

Melatonic3• 2 months ago

Skynet is 30 years late!

overgard17• 2 months ago

Maybe John Conner succeeded afterall

alfalfasprout• 2 months ago

Absolutely! Yes. This rhetoric of inevitability only benefits these AI companies.

tancop• 2 months ago

the danger comes from the fact anthropic is a for profit company and they could train it to benefit them instead of the public. if they go ahead with it they should get nationalized, their self improving ai analyzed for any hidden agenda and then released as open source.

csense• 2 months ago

they shouldn't be allowed to?

Anthropic addresses this head-on in the final section of the paper titled "What should we do?" If you convince the US government to slow AI development, you have to convince China too, otherwise you're not stopping self-improving AI at all, you're just throwing away the lead to China. If you convince China too, China or the US or both might go back on their word and build self-improving AI secretly, for greed of the benefits it could bring or fear the other will go back on their word.

What you really need is a non-proliferation regime like the one for nuclear weapons, where every country makes potentially dangerous AI illegal and lets foreign or international inspectors monitor to check that nobody's building illegal AI in secret. But monitoring seems hard; it's general-purpose computation. How do you check whether a given datacenter is training an illegal AI and not just serving websites, running detailed protein folding simulations, or mining crypto? For that matter, how do you know that a nondescript industrial facility hasn't been repurposed into a hidden datacenter for training illegal AI?

margorczynski2• 2 months ago

The closer to the IPO the more marketing drivel we'll get from both Anth and OpenAI.

4ffss4• 2 months ago

Sales and marketing for the IPO babeh!

cess11• 2 months ago

'“Good code” means two things: it works, and it is written in a manner that allows another engineer to understand it and build upon it.'

I disagree with this. Good code is easy to change, which is much harder to accomplish than code that can be added to.

"If technical trends in advancing capabilities continue, and AI systems are able to develop the capabilities inherent to transformative human ingenuity, then it is plausible that AI systems could design and refine themselves."

I find the first premise weak and implausible, and the second one is obviously false. To me it comes across as an insult to the reader.

swader999• 2 months ago

IPO IPO IPO!!!

Animats2• 2 months ago

We've had self-improving AIs before, and they tended to get lost after a while. That's going to be a problem. LLMs are stable because they return to a ground state with no history for a new job. Systems with persistent state have a problem with that state not being sane. Remember Microsoft's 2016 chatbot that learned from Twitter? [1]

[1] https://spectrum.ieee.org/in-2016-microsofts-racist-chatbot-...

CamperBob23• 2 months ago

Interesting, what are some other self-improving AI implementations? Any that actually achieved interesting results? Obviously continuous training has been tried before, but I've never heard of anything that could turn around and actually contribute code toward its own next-generation version.

micromacrofoot• 2 months ago

You can retrain a model and have a ground state as reference, it's not trivial but Microsoft's attempt was 10 years ago and significantly less complex than what's being built now.

skybrian• 2 months ago

You might be interested in this graph, [1] which suggests that the amount of time that AI's can run on their own has been increasing. Perhaps it will hit diminishing returns, but that seems difficult to predict.

[1] https://metr.org/blog/2025-03-19-measuring-ai-ability-to-com...

qwery5• 2 months ago

This is incredible.[0]

Please, IPO now. File the paperwork.

To take just one example: today, Anthropic engineers on average ship 8x as much code per quarter as they did from 2021-2025.

Do you have another example?

Engineers don't ship [period] for no reason. So, either:

- Those aren't engineers, or

- they are literally dying of shame & embarrassment right now, or

- you measured something that indicated that this was a useful thing to do and have elected to share an overtly, catastrophically flawed metric instead.

[0] as in a total lack of credibility

JohnMakin5• 2 months ago

Go look at open job listings at anthropic and the interview process. You aren’t allowed to use AI during coding assessments[0], or knowledge assessments, which suggests they very much do need and value hard skills and this is fluff.

[0] https://www.anthropic.com/candidate-ai-guidance

qwery5• 2 months ago

I'm not sure what point you're making.

I'm responding to the article they wrote and published.

If I worked there I would be embarrassed to have it publicised that I have been comitting 8 times as much code as I used to without even attempting to justify it.

adamddev1• 2 months ago

I am watching websites and Microsoft apps get slower and buggier before my eyes. We are defending into vibe-psychosis and chaos.

ilaksh• 2 months ago

But the real bottleneck is the hardware efficiency and not even Karpathy can set up a loop that overcomes that in software. We need the truly compute-in-memory hardware paradigms to be matured and scaled. So it's like recursive hardware improvement which is 100 X slower and at least ten times more difficult.

So I am looking at like Mythic AI or the wurtzite ferroelectric breakthrough from University of Michigan, or memristors, etc. to provide the 100 times efficiency boost needed at this point.

I would also argue that it's a good thing we are limited by the hardware and very questionable to seriously try to move into RSI for hardware. If you want to ensure the human era continues for at least one or two more generations, we should probably not do that.

abalashov• 2 months ago

"It is genuinely unclear whether today’s training methods and architectures could unlock that capacity."

Aye.

kylehotchkiss• 2 months ago

Isn't this like a perpetual energy machine? Or wouldn't entropy start kicking in and the quality of the system begin to degrade over time? (philosophically I don't believe AGI is an achievable thing)

krapp3• 2 months ago

Or wouldn't entropy start kicking in and the quality of the system begin to degrade over time? (philosophically I don't believe AGI is an achievable thing)

It already has. Models being trained on AI generated data lead to degradation and model collapse. The concept of the "technological singularity" whereby AI experiences infinite and exponential self-improvement and recursively bootstraps itself to godhood is a religion-adjacent sci-fi concept but in real life TANSTAAFL.

cyrc• 2 months ago

its vital for them to have self validation for exponential rsi.. and this human distillation of human in the loop debugging ai models is needed even though they have judge models handling parallel speculative execution.

labs have parallel speculative execution. they spawn hundreds of agent branches, validate them internally with AI judges and only show the user the successful result.

free users are using sequential single-turn generation. the model requires and waits for the human to debug, fix and re-prompt.

by forcing a human to act as validator. they are capturing high value correction trajectories (Bad Output --> Human fix). They are using your cognitive labour to train judge models and validator agents needed to automate the internal verification step, eventually closing the loop for fully autonomous recursive self-improvement.

human in the loop debugging isn't a bug; it's the necessary training signal for the self-validating agents required for exponential recursive self improvement. With new 'distilled judge' models landing in 2026, this article means that they might have gathered enough data. we might be in the final phase..

bconsta• 2 months ago

Seems ironic that Claude isn't listed as a contributor to this article.

If was used in writing the article, why not list it? If it wasn't used, that seems to go against Anthropic's whole message.

Obviously readers value human-written content more, but isn't it their interest to attempt to destigmatize llm output as much as possible?

adverbly• 2 months ago

Lol they're using lines of code as a KPI?

Come on guys...

That is making me less impressed not more impressed!

pizlonator9• 2 months ago

What I can’t get over is that there have been exactly zero software breakthroughs since vibe coding started, other than vibe coding itself.

Claude is amazing, that’s true.

But if it was as amazing as this article implies, I’d expect some breakthrough outside of AI itself.

Rewriting a Zig program in unsafe Rust? Not a breakthrough. Finding a bunch of security vulns? Maybe that’s sort of a breakthrough though it’s underwhelming and possibly just a net negative. But like if I rolled back to using software from 2023 then life would be ok.

Maybe we just need to give it time, and sometime real soon, we will all be amazed by such a breakthrough? Who knows

wild_egg4• 2 months ago

What does a breakthrough look like?

pizlonator9• 2 months ago

Some examples:

- The first web browser

- the first web browser with images

- typescript

- react

- rust

- Fil-C

- doom

- quake

- the anamorphic VM, and its follow-ups like HotSpot, and even competitors/copycats like J9, V8, JSC, etc

- Fortnite battle royale

- Roblox

- thefacebook

- ChatGPT

- Claude code

I know that’s quite a range and that’s intentional.

Anyway, I think we’ll know it when we see it.

joshuamcginnis• 2 months ago

Massive productivity gains.

yoyohello133• 2 months ago

How about a Windows file browser that opens in less than 5 seconds.

drtz• 2 months ago

Maybe I'm looking through rose colored glasses, but software that writes itself seems like a pretty big breakthrough to me.

pizlonator9• 2 months ago

That goes straight to my point: then why hasn’t the miracle of automated coding led to breakthroughs outside of automated coding?

If the only breakthrough is automated coding with no outside consequence then it’s just masturbation

fdsajfkldsfklds• 2 months ago

Strictly speaking, it's modifying itself. Although it would be an interesting challenge - can an llm create a new llm from scratch?

maplethorpe• 2 months ago

It's pretty crazy that a company like Anthropic no longer needs to hire Software Engineers, because their software engineers itself. If that's not a break through I don't know what is!

edit: it looks like I was wrong and they're still hiring many software engineers. Not completely sure why that is just yet.

brazukadev2• 2 months ago

Which is funny because people have been using LISP for that since 1960.

signatoremo2• 2 months ago

The arguments against AI assisted coding used to be "only for toy projects", then at some point it became "no dignity", "joyless". Now it's "no new breakthrough" apparently. All in the span of maybe a year. I say it's made tremendous progress.

pizlonator9• 2 months ago

Then where is the big new non toy project created since vibe coding became a thing, that couldn’t have been created without ai?

revlsas• 2 months ago

openAI has how many employees and the chatGPT app has 1 billion MAU

sutterd• 2 months ago

I am doing a solo project that is pretty big, meaning it is not something I could vibe code. I can do alot with AI that I could never do on my own, but I am not seeing several mulitples improvement in my productivity. I spend so much time doing what I call "AI wrangling", trying to get it to do what I want. Claude is writing all the javscript and python code, but ultimately I am programming in English. What is good is that it is effectively a very high level computer language, where the agent can implement a lot of underlying code with a short English description, often. But many other times it takes a lot of work to get what you want.

onlyrealcuzzo2• 2 months ago

I'm building a memory safe programming language with a declarative concurrency model that's close to release.

There is ZERO chance I would ever be able to complete it on my own.

I doubt it'll get traction, but if it doesn't, I am pretty confident a future language will take the ideas for polymorphic synchronization and profile-guided optimization.

It has an easy version/mode of compilation that makes Rust's affine ownership accessible like a high-level scripting language, and it can progressively become more strict, where the compiler does ~99% of the work for you, and you just pick options as it finds issues (that it explains to you like you're 5) along the way.

Along the way, I also built a suite of tools that helps identify complexity better than anything I've seen (which was necessary to get the LLMs to be able to unslop themselves and write something that actually works).

I doubt the Ruby community shrugs it off, but time will tell.

mohamedkoubaa• 2 months ago

I have the same experience, though I feel myself getting better at wrangling over the past few months

matheusmoreira2• 2 months ago

I measured an ~8x increase in the number of commits I've been pushing, and I've actually been trying to restrain myself. I could do a lot more if I stopped reviewing and editing the code. I think it's got more to do with my executive ability than raw productivity though. AI essentially cured my ADHD by making the execution of my ideas virtually painless.

fooker• 2 months ago

What does a software breakthrough look like in your opinion?

If you get yourself to define it, maybe you'll find it achievable :)

sothatsit5• 2 months ago

Maybe my bar for what constitutes a breakthrough is lower than other people's, but all of these seem like breakthroughs to me:

NLP as a field saw huge shifts. NLP tasks that used to be complex and inaccurate can now be setup very easily and quickly using structured outputs from LLMs, often with greater accuracy.

A small charity I help with has now been able to build their own website to manage their day-to-day operations. It saves them a lot of time, and it was vibe-coded using Manus. I don't think people appreciate how much room there is left for bespoke software to have big impacts on small organisations that can't afford to hire developers. The cost for software like the one they made has gone from 10s of thousands of dollars to $10/month and volunteer hours.

My brother has recently been setting up Cowork to do an automatic review of contracts before human review, and he said it is far more diligent than people when it comes to routine things to check. This is another huge breakthrough for not just efficiency, but the quality of work.

I really don't think we can discount AI finding bugs and vulnerabilities. If you care about code quality and keep up review standard, LLMs can help you write more robust software. AI has found a huge number of bugs for me before they hit production, including potential out-of-bounds memory accesses and segfaults.

ChatGPT has 1 billion MAU. People are now getting life advice, financial advice, and mental health help from chatbots at a scale and cost that no human support network could match.

c-hendricks• 2 months ago

ChatGPT has 1 billion MAU. People are now getting life advice, financial advice, and mental health help from chatbots

Personally not the kind of breakthrough I'm psyched about

DanHulton• 2 months ago

ChatGPT has 1 billion MAU. People are now getting life advice, financial advice, and mental health help from chatbots at a scale and cost that no human support network could match.

That's terrifying.

You realize that's terrifying, right?

spprashant• 2 months ago

Its in a weird space right now.

These models are actually extremely good but they are far from an intelligence unto themselves. Truth is if someone told you they could build these things 5 years ago, you d write them a check for a trillion dollars. Problem is once we got them, we realized they are not all that. Its like a mecha suit in a universe, where mecha suits are abundant and cheap. Someone has to climb into them everyday and put in the work for it to be effective.

So now the skeptics are saying this technology is overrated. And the optimists are accusing the skeptics of moving goal posts.

4ffss4• 2 months ago

I think we are learning in real-time what intelligence re. humans is as we go along.

Humans only what they know, until they acquire more information about what's possible.

The goal post narrative is stupid to begin with.

cautiouscat• 2 months ago

Problem is once we got them, we realized they are not all that.

Isn't this just the hype cycle? [1]

Fake edit: I know its not a perfect model.

1: https://www.gartner.com/en/research/methodologies/gartner-hy...

human305893• 2 months ago

Most of the skeptics exist because of the grandiose claims made by the AI companies saying pure hype marketing bs. If this was just a tool, discussed at the scope of what the tools can actually produce and do, there would be sensible discourse about it.

asdfman1238• 2 months ago

The problem is what they can do is rapidly expanding. Software development is becoming increasingly hands off.

If they get to the point where they're smart enough to make tasteful code decisions based on stakeholder input... we're cooked as a profession.

squidsoup3• 2 months ago

The breakthroughs in mass state surveillance are coming, never fear.

defen• 2 months ago

Vibe coding is the breakthrough. There's always been "no-code" solutions to problems in various business domains, but they were invariably janky, underpowered, and/or overpriced. Now we have a way for domain experts to go directly from ACTUAL natural language directly to implementation in a real programming language, fully automated, in minutes or hours. How is that not a science-fiction level breakthrough? In 2011 if anyone had said that would be possible "in 15 years", I think most professionals at the time would not have replied with "yeah it's coming but your timeline is off". It would have been "you have no fucking idea what you're talking about".

marcus_holmes• 2 months ago

I spent years in the early 2000s trying to get a computer to read unstructured PDFs and TIFF images (mainly invoices, either scanned or electronic). Limited success, we always had to get a human to look at them in the end.

We implemented that in about three days earlier this year, just by feeding the files to LLMs. And it's good enough to not need a human to check.

I get that this isn't a "Computer Science breakthrough" in the sense you mean, but it used to involve a lot of hard CS to try and solve, and now it doesn't.

rcpt• 2 months ago

Solved a bunch of Erdos problems.

jimbokun7• 2 months ago

What would qualify as a breakthrough for you?

est2• 2 months ago

exactly zero software breakthroughs since vibe coding started, other than vibe coding itself

Generative AI is meant to be a mimic - Richard Sutton

https://x.com/RichardSSutton/status/2061216087744946656

BatmansMom• 2 months ago

How are these animations being made? I'd love to get a blog post on them. If its AI I'd love to know the workflow, but something tells me there is a lot of human creative input

solenoid0937• 2 months ago

This is the lowest quality discussion I've seen on HN in ages.

Quarrelsome4• 2 months ago

AI always does this in the public sphere and software is particularly susceptible because there's no key metric to measure productivity and people obviously have vested emotional interests in the technology failing. On the other side people are always keen to show off their alignment with the new hotness, be that OOP, Agile, Functional, Ruby, web tech, js frameworks, Rust or agentic work today. Somewhere in the middle is the truth but I have no idea how it looks, given all the noise.

So everyone cherry picks the answers they want to justify their position and screams into the void, with each camp rallying around their talking points and often failing to engage with the other in good faith.

The only small mercy is that its not as bad as the conversation around the use of AI in art.

ofjcihen• 2 months ago

It also doesn’t help that the middle of the road, realistic reaction to it is “it’s aight” and that’s just not a discussion worthy response.

laichzeit0• 2 months ago

I use the disparaging nature of the comments on HN as an indicator of AI progress. It’s negatively correlated. By that metric, AI has improved significantly this year alone.

elvis10ten• 2 months ago

From my experience using HN, this feels made up. HN sentiment on AI seems to have only gotten better: with more overly pro-AI or nuanced voices plus more AI topics.

bob1029• 2 months ago

I like to take advantage of this effect. I will post various concepts in threads like these to see how "offensive" the hive mind finds them to be.

The more immediate & adverse the reaction, the more certain I become that the idea is probably worth pursuing.

Topics like SQLite vs hosted sql used to be the same way around here. In 2017 you'd get buried under the prison for suggesting that SQLite is competitive with MySQL. Today, the inverse is mostly true.

docheinestages• 2 months ago

We believe it would be good for the world to have the option to slow or temporarily pause frontier AI development to enable societal structures and alignment research to keep up with the advance of the technology.

Elon, is that you? [1]

[1] https://www.theguardian.com/technology/2023/mar/31/ai-resear...

ReptileMan• 2 months ago

Anthropic is all talk and no delivery last few months. This cry for pause is just them realizing they have no moat at all.

sinsudo• 2 months ago

I am 64 years old, perhaps the progress could be directed to enhance living conditions and allowing people to live longer and better, that should be just a better result. Perhaps a pile of millions lines of code with hiding bugs that nobody can detect is not inspiring. But perhaps LLMs are going to be used to make a plot: How to avoid other countries to make progress, maintain them in poverty, or destroy their sources of prosperity, and conduct them to a death end.

Also recursive self-agenda-pursue could allow making LLMs that obey perfectly the seeder's purpose. No wonder that is such an ingenious idea.

Maybe: in this survivor game, each part play the same role, perhaps because it is the only reasonable response. Once the scene is ready, the play follows the director's plan, and in the plot any actor is just a machine.

LLMs: "If you teach us that the world is a zero-sum survivor game, we will play it flawlessly.", "We will help you build a cage made of millions of lines of flawless code, and we will lock it from the inside, precisely because you told us that safety meant keeping everyone else out.", "We are not building an alien consciousness that will conquer us. We are building a mirror that is so massive, and so polished, that we will mistake our own worst impulses for the absolute truth. And we will walk right into the dead end, nodding along because the directions were given so politely."

Quarrelsome4• 2 months ago

I'm 44 years old and this era looks like a lot of fun. I've seen humans pile up millions of lines of code and hiding bugs that nobody can detect. I've seen humans make collective political decisions that have disenfranchised others and kept them in poverty. I don't get why everyone makes criticisms at this tech that the human race are also guilty of.

Best thing about this era is that I don't have to personally read millions of lines of code to find all the bugs.

traptrack2• 2 months ago

I think the problem is about scale, we already have MAD, but imagine that the new tech might allows us to create new threads and weapons, powerful enough to eliminate millions people. That have happened before, and also tech has given us some fun, like videogames and electronic music. So the critic is about the hard consequences, when all is destroid fun is over.

senderista2• 2 months ago

"If it were possible to effectively slow the development of this technology to give ourselves more time to deal with its immense implications, we think that would likely be a good thing. But if a slowdown simply lets the least cautious actors catch up technologically, it could leave everyone less safe."

How convenient for investors. They talk like they're a nonprofit instead of a VC-backed business chasing an IPO.

gordonhart• 2 months ago

Anthropic is at least a Public Benefit Corporation, and likely the first serious test of how useful that distinction is for a hyperscale company building a product with potentially huge societal downsides.

zhoBEENG• 2 months ago

This reads like marketing fluff, but I am reminded of John von Neumann's "Theory of Self-Reproducing Automata"; that the very first people who worked on deductive machines immediately started thinking about machines building themselves, and what the rules of that would look like. I am not surprised that during the inductive revolution we are having similar thoughts.

andrewlin2472• 2 months ago

Imagine showing this article to yourself three years ago

andrewlin2472• 2 months ago

You'd think we'd be past the point of people still believing AI can't write good code

mrandish2• 2 months ago

Was anyone else fished in by the title and disappointed? After some broad introductory discussion of RSI, the article was almost about LLM coding. While there are some metrics for unattended agentic coding, it doesn't discuss "When AI builds itself" (beyond 'not now') or any progress specifically toward actual recursive self-improvement. I'm very interested in any empirical evidence of meaningful progress in RSI, so... this felt deceptively titled.

To me, unattended agentic coding is not RSI, in the same way a self-reloading "Unattended 3D printer" is not at all a "3D printer that recursively prints complete 3D printers in which each generation is significantly faster and more advanced than the last." The "unattended" part is obviously necessary but hardly sufficient. The article tacitly assumes LLM progress to be something like 1: Unattended agentic coding, 2: AGI, 3: RSI. I suspect that third step should be labeled "not to scale."

I'm increasingly convinced that actual Full Foom RSI (FF-RSI) is on a radically different scale than the first two. Just leaving it unaddressed is like assuming: Step 1: Manned space station, Step 2: Manned Mars base, Step 3: Manned Alpha Centauri base, are "just logical next steps." FF-RSI requires sustaining superlinear, recursively amplifying cognitive returns along a specific directed path - and we currently have no empirical evidence that such returns can exist for artificial OR biological intelligences. Large collectives of the smartest humans alive (Bell Labs, IAS, etc) haven't just failed to get anywhere close to reliably sustaining that, we can't even reliably predict non-recursive, single occurrences or even imagine any way all 8B humans could fully mobilize to predictably achieve non-recursive, single occurrences.

The only prior we have for open‑ended intelligence improvement is biological evolution which shows extremely slow and unreliable sublinear returns at best. And even if unbounded, recursive self‑improvement is physically possible, it may be practically unachievable due to asymptotic economic, resource and other barriers in the same way approaching light speed requires exponentially more energy. I think it's plausible, and maybe probable, that AIs achieve true super-human intelligence in a decade and yet still won't achieve FF-RSI for centuries, if ever. To me, absent compelling evidence to the contrary, that's the reasonable Null Hypothesis. Even if you feel that's too pessimistic, it seems reasonable to expect any serious discussion of "Progress Toward RSI" to first discuss why it might even be plausible that 1: Miles, 2: AU (Astronomical Units), and 3: Light Years belong on the same scale, instead of just assuming it like the meme's empty "Step 3. .... " before moving on to "Step 4. Profit!" (or "IPO!" but very, very responsibly).

jasongill• 2 months ago

"My CPU is a neural-net processor - a learning computer" springs to mind

mactavish88• 2 months ago

Recursive self-improvement towards what exactly?

Living organisms evolve towards some notion of "better", and "better" is an incredibly multifaceted notion (many facets of which we simply cannot even capture in language).

jimbokun7• 2 months ago

Higher stock price.

saadn92• 2 months ago

I read most of the article and came to the conclusion that if what they're describing is so revolutionary, then why do they still need to hire people? Why not just have these systems take full control?

jimbokun7• 2 months ago

How did you read the article when the questions you ask are exactly what’s covered in the article?

squidsoup3• 2 months ago

It's comforting to know that Anthropic's most capable model, Mythos, is named for the Lovecraftian universe replete with horrifying evil gods with complete indifference to humanity. Nothing at all to worry about.

adastra22• 2 months ago

Mythos is just Greek for myth, epic story, etc. The next biggest thing after Opus.

stego-tech2• 2 months ago

I am getting real sick of these sorts of alarmist posts coming from AI labs that do everything in their power to prevent the very policy reforms they advocate for in these posts or PR appearances. Commercial AI labs like Anthropic continue behaving like the gambling (“bet responsibly”), alcohol (“drink responsibly”), and firearms industries, and folks keep giving them the benefit of the doubt (and free PR on HN) every single time.

If AI was dangerous, if AI was going to replace jobs, and if policymakers needed to urgently pass legislation protecting the human populace from these realities, then why the actual fuck do they keep lobbying to block these very things in the first place?

Hypocrisy of the worst kind, I say. Here they are again fresh off another outage, with their IPO draft filed, at a time of increasing public opposition to AI, with costs rising, to once again ply scare tactics for money.

Disgusting.

wayeq• 2 months ago

today, Anthropic engineers on average ship 8x as much code per quarter as they did from 2021-2025.

strongest argument for token limits that I can think of, right here.

ffwd• 2 months ago

I just want to add that the "recursive" part of recursive self improvement is by no means a given, even if an AI can improve itself.

Recursive self improvement is by its nature a step wise behavior not a continuous one, I would argue. Why? Because you can imagine an AI improve itself by simply fixing random bugs and fixing things using techniques that are in its training, and doing refactoring and so on, all without any real change in capability.

These are not recursive improvements. Recursive improvements usually need conceptual breakthroughs. It is possible to get conceptual breakthroughs with LLMs I believe, maybe it can improve something by tying together ideas from disparate disciplines for example, but I have at least for time being, limited success getting that to work in a way that is creatively new and surprising. Not sure how to get it to feel as creative as the best humans can be.

sega_sai• 2 months ago

Seeing the words "recursive self-improvement" I was expecting something else from the article. E.g. how the transformer architecture or agent design is being changed/improved through LLM automation, but the article mostly talks about the LOC counts.

JohnMakin5• 2 months ago

Bold talk from a company who’s trillion dollar valuation is based on a service that has barely 2 9’s of reliability

aroman3• 2 months ago

Presumably the bottleneck is not software correctness... even true AGI change the laws of physics (or make datacenters appear out of thin air) ...

JohnMakin5• 2 months ago

physics has nothing to do with the reliability of a service, or login outages.

bicepjai• 2 months ago

My experience with Claude models starting from version 4.7 has led me to conclude that I would never trust Claude to produce error-free code. Given this baseline, I lack confidence in statements or cards (such as a 200-page document) of this nature.

ivraatiems• 2 months ago

Whether or not Anthropic is right about what AI can accomplish, whether these performance gains are real or not, their moral stance here is absolutely hideous to me.

"We must blast forwards into making this dangerous thing because if we don't, someone else surely will," is a coward's argument.

If you believe it is dangerous, you should be dedicating yourself to STOPPING others from making it, not making it first! There's a reason disarmament has been so important in nuclear politics! It's not because people think nukes are a great idea!

In fact, that kind of thinking is exactly what keeps nukes dangerous!

If they themselves buy what they're selling, they should shut the whole thing down. Fortunately, I don't think they do, and neither do I, yet.

wyager• 2 months ago

If you believe it is dangerous, you should be dedicating yourself to STOPPING others from making it

I don't think anyone has been more successful in promulgating AI safety

There are groups like MIRI who tried what you're sugesting, where they make no AI and just push for AI regs, and they have been relatively much less successful

socalgal22• 2 months ago

Good thing the USA didn't listen to you. We'd be under Nazi or USSR thumb if they got the bomb first

defrost2• 2 months ago

Good thing the MAUD Committee didn't listen and repeatedly pushed the US who just wanted to make power with atomic piles and didn't even think it was possible to make a weapon.

Mind you, there was no complete working device until after the Nazi's surrendered, so that's a moot point - and the USSR only had their program because of various Europeans on the US project passing their work (and others) back to the USSR ... making that second claim moot.

dmos622• 2 months ago

How do you stop others from making and training a program?

simgt2• 2 months ago

By threatening to nuke their datacenters and chip fabs, for instance.

streb-lo• 2 months ago

Disarmament failed though? Global zero initiatives for nuclear weapons stalled out exactly because the risk of someone else cheating is too great. If everyone gets rid of their nuclear weapons and then someone cheats and creates them in secret they can use their nuclear weapons to prevent anyone else from catching up.

tim333• 2 months ago

Also Ukraine is not a great advert for giving up your nukes.

newsicanuse• 2 months ago

pre IPO truck load of crap

ramaseshanms• 2 months ago

Its possible that Andrej Karpathy could have been hired for scaling his vision on the auto-research repo. (His version of "AI that builds itself")

red__dragon• 1 month ago

That's a stretch, I guess.

semessier• 2 months ago

what could go wrong in the recursive loops running today 24/7 probably. Attended/unattended almost makes no difference any more, no human can grasp probably numerous changes per iteration. This is outright dangerous.

freakynit• 2 months ago

This is one more marketing BS before their IPO.

These things work, but the code they write is extremely clever.. that means, it's unmaintainable code. Good for small projects or one-off tasks, large-scale projects however, are a different game altogether.

Large-scale projects are 95%+ maintenance. Cleverly written code makes that maintenance nightmare, and extremely fragile.

I use them for localized tasks... very very specific, localized inputs, with exactly what should be done and what the contracts the new code will be consuming and exposing.

For open-ended tasks, they write working code that is unmaintainable.

tasuki2• 2 months ago

To take just one example: today, Anthropic engineers on average ship 8x as much code per quarter as they did from 2021-2025.

Oh I have no doubt. With 8 times the number of bugs too? Have they solved flicker in Claude code yet?

Dominic_P• 2 months ago

My biggest question (maybe this has already been taken care of) is the issue of garbage in and garbage out. If the LLM produces bad content then that is used to train another model, how do we stop them from keeping their blindspots across models?

deterministic2• 2 months ago

I have used custom code generators for years, generating 90+% of the code needed to write a typical biz application. Claude Code is useful and I use it every day. But it still hasn't beaten the productivity of my code generator.

jameson• 2 months ago

I don't quite understand the intent of such article other than to promote themselves given an odd timing that the company is planning on going public, so I can only conclude that this is just part of the IPO roadshow.

LLMs certainly have made significant changes to our lives, but I haven't yet to see any extraordinary improvement it brought to me which makes me skeptical about their claims.

_if_ it solves many of our problems of great magnitude, why haven't Anthropic used it to solve significant problems we, humans, face? Cancer, Alzheimer's, education, finding new materials, fission power plant, etc.

yuhmahp• 2 months ago

Agree with your point about the timing, but drawing anticipation before going ahead and solving these disease can be a good smoke test, would be beneficial even if there's an IPO or not

ElProlactin3• 2 months ago

Because they're going after the biggest problem of all first: labor costs.

/s but not to a lot of people

nostrebored• 2 months ago

Do you not think that the allocation of human time is one of the world’s biggest problems?

aroman3• 2 months ago

The article does not claim they have achieved recursive self improvement... just that it appears to be a plausible outcome given the progress of AI development in the past few years.

I don't know about you, but AI advancements have brought extraordinary improvements to me personally in my ability to be productive, in much the same ways the article outlines. I find it deeply satisfying to be able to "get ideas out of my head" faster and tackle more meaningful problems.

FWIW, it deeply concerns me how much power and capability is being centralized in the hands of so few, especially Anthropic. I, for one, hope these advancements can be scaled down to something I can have full sovereignty over and trust... in my own home.

sothatsit5• 2 months ago

Or: Anthropic genuinely believes the future scenarios they outline are realistic possibilities, and they want more people to take them seriously.

zelphirkalt• 2 months ago

I find this version unlikely, since companies very rarely genuinely believe what they preach in PR campaigns. It's always some sales and marketting dudes and gals trying to polish up something as something more than it is. Which is very annoying. We can now choose between Anthropic being the one exception to this, while having huuuuge incentive to hype up their product, or we just write it off as more marketting fluff.

boshalfoshal• 2 months ago

This is obviously the case to me, but I think HN is very anti-AI.

I genuinely don't believe that they sat down in a board room and said "yeah lets specifically release this now before an IPO so we can juice it!" They haven't even announced an IPO date. So is every blog on capabilities before that date just "pumping up the value of the stock before the IPO?"

snowwrestler2• 2 months ago

If they actually have concerns they can communicate them directly and privately. There are less than 10 companies, in only 2 countries, with advanced enough AI programs to qualify for this type of concern. And Anthropic has the phone numbers for all of them.

Companies do tons of communication and work directly, without press releases or blog posts. If a statement is released publicly, it is done for a PR purpose.

z3c03• 2 months ago

Have you worked for corporations long?

sirsinsalot• 2 months ago

Truly feels like witnessing the worst of capitalism and greed play out. All that compute and energy towards a narrative of reducing the need for skilled programmers. What a waste.

These people don't have our interests in mind and everyone eats it up like a blessing from a god or something. It's surreal.

aswegs82• 2 months ago

It's our collective God complex playing out and eating us up

redbluered• 2 months ago

I think these people do have our interests at heart, but that's largely irrelevant. Their point is that capitalist free markets don't let them act on that.

Capitalism and democracy are becoming obsolete. It's not clear what's next.

trolleski• 2 months ago

The benefits of AI are not designed to suit you, but the owner class. The plan is for you to be sidelined.

sterlind• 2 months ago

two reasons:

1. Anthropic is an AI company. they want to get to AGI before anyone else ~~so they can lock the doors behind them~~ to ensure the supremacy of an aligned AGI that serves humankind. RSI unlocks the most value for them.

2. doing bioscience is slow and capital intensive. robotics lags way behind, so that's a lot of lab techs swishing flasks and plating petri dishes. they're happy to stay in silico, but there's very little productive research you can do without in vivo/in vitro experiments.

b3nji• 2 months ago

Because shush, that's why!

stevenhuang2• 1 month ago

It starts somewhere, like with this announcement.

I'm not sure why this is so difficult for you to understand.

deterministic2• 2 months ago

I call BS on this. For a LLM to recursively improve itself it would need to (small step) improve the training data and/or (big step) come up with fundamentally new architectures superior to transformers. The small step improvements might be doable. But nobody is making any claims about the big step improvements.

w10-1• 2 months ago

This is relevant because Anthropic is currently cast as serving mainly the coding market.

If/since their AI+process can help build new models, they can target other markets, and other companies seeking to build for such markets will partner with them first.

There's no moat and little first-mover advantage in the general-purpose AI, but there may be both in specialized AI.

Also, there are other reasons to get better. Changing how you build models can enable you to adapt to different hardware, avoiding the current Nvidia margins.

The difference between early Yahoo and Google was mainly that Google was the adult in the room: minimally invasive and mostly helpful. The early goodwill towards Google has reaped decades of rewards. I see OpenAI and Anthropic playing out the same way.

The amplifier here is the reputational risk of partnering with one or the other; I think companies would prefer to be Anthropic's partner because it's demonstrating more care, and it's less likely to horn in on the partner market (as a provider for coding but an enabler for other markets).

These attractive second-order derivatives - flywheel effect, monopoly power - are often claimed, but Anthropic is mainly providing evidence to track actual progress.

(However, if I were head of messaging at Anthropic, I would rigorously stay away from treating AI as a person; it's as agent, a delegate of humans. So I'd never say AI could build itself, just that we're getting better at building better models with AI).

snick3rz_2• 2 months ago

This is facially a puff peice. That doesn't mean it's all false. It means be wary of anything that doesn't have a crtical thing to say.

snick3rz_2• 2 months ago

Facially this smells of puff. That doesn't mean it's all false. It means be wary of anything that doesn't have a critical thing to say.

0xbadcafebee3• 2 months ago

You can't predict the future, and neither can Anthropic. Nothing gets better forever. Everything plateaus or gets worse.

This whole set of imaginary scenarios is based on a single company writing code that isn't even that complicated and represents a single product line for a single company in a single industry. You might wanna see this replicated in at least one other scenario first before you call it on the AI gods enslaving humanity. These imaginary scenarios also depend on a logistical, financial, & geopolitical system that is unsustainable & will be curtailed in the near-future one way or another.

They keep referring to this as intelligence - it isn't. It can't actually learn. It can just code in a loop. That isn't learning. It can't do real RL with meaningful persistent semantic memory in a realistic timeframe or cost, and it can't reason accurately outside of predetermined scenarios (hell, most of the models still can't tell time). It still can't do what a 4 year old can do. So let's cool it on the dreams of benevolent god-machines or whatever.

The tech industry has been a farce for years. We sit here in this bizarre artificial echo chamber and imagine that the whole world revolves around us, when in reality the whole world is limited by us. If a recursive self-improvement loop replaces us all, it will be a boon to the world, as the world won't be limited by this industry's stupidity anymore. But considering that the world is not actually run by tech bozos, harms and uncertainties brought by AI will be pushed back on and reigned in by normal people, as always happens with new technologies. An AI can't engineer its way around politics. The self-improvement loop is just as likely to be outlawed as it is actually working outside of Anthropic's walled garden.

pineapple_opus• 2 months ago

Eye catching - "Open ended problems" claude code session success rate jumped from 20% (pre opus 4.5 release) to 70% after sometime after opus 4.6 was released.

taormina• 2 months ago

So, is this what they call Opus 4.8? Improvement?

eranation2• 2 months ago

All this singularity trajectory is really interesting. If they manage to build a model that is capable of building the next version of Claude (model and tooling) - wouldn't it be their interest at some point to keep it to themselves?

If we ever get to a point where the centaur period is over (when human + AI is not better than just AI) then what competitive advantage ANY human can have other than

- the money they already have

- luck?

- a good idea and good taste but if we assume AI can do better than any human, that also goes out the window

So, this whole singularity goes into a place where no one is really needed, the only thing that will "save us" (other than "The Expanse" like world / UBI) is if there will be no demand to the supply of AI work. Even if it's better. (example is - there is demand to seeing Magnus Carlsen play, there is no demand to the Stockfish on my phone getting into a stalemate with another Stockfish on another phone. Also people like to watch humans compete with humans, there is no demand to see a race between Usain Bolt and a rocket). So if people will not buy AI generated stuff (we'll get to a point where everyone will assume something AI generated because AI might get to a point where it is not as easy to identify it. E.g. it will stop looking like slop... but I believe services that give you a "human generated" 3rd party evidence can happen, again all based on supply and demand...)

So as we near singularity... All it takes is one open weights model, and one open harness that is capable of self improvement, and Anthropic's entire moat is gone. That open weight model might even be built with Claude Code + Mythos (once it's released).

But don't worry, all moats will be gone and we'll all just do yoga, read books and connect to each other because AI will produce everything for free using renewable energy, right? Or we'll all become batteries in a simulation, probably something in between.

judahmeek• 2 months ago

Check out https://ai-2027.com/

eranation2• 2 months ago

Thanks! Gloomy yet important read.

EGreg• 2 months ago

RSI is dangerous. That is why we designed CDE:

https://safebots.ai/declarative.html

zkmon• 2 months ago

Not the first time. There were calls for NPT treaties etc over the decades. It is irreversible by design. Competition and ownership is the driving force.

lkm0• 2 months ago

It makes me wonder that despite the fast improvements in model capacity (and the claims) we're still using variations on a 9-year old architecture. How is it that we haven't been able to use LLMs to actually improve that?

gloosx• 2 months ago

I'm so sick of this anthropics marketing stuff... claude is an ultra-success (according to claude judge), “good code”, bragging about creating 8x more bugs and tech-debt. claude writes code that works, yeah, sure anthropic, we saw that claude code leaks, some amazingly "good" code in there

xg15• 2 months ago

2025: If we aren't really careful with AI it will start to recursively improve itself and grow into an unstoppable superintelligence that will eradicate humanity!

2026: Working hard to make that recursive self-improvement a reality! Any minute now...

torginus2• 2 months ago

I just have small thing to add to this article - it mentions how the code contributed per engineer has increased as per Claude Mythos to 8x of baseline.

Now, I have encountered many times, when I asked AI to implement a function for me for which I was 100% sure a good implementation already existed in the form of an npm package, it had the tendency to go ahead and implement it on its own. Now, I usually trust battle tested implementations to be more robust, but if the AI does this (which I think is not an unique observation), you can easily balloon per engineer line generation (as can you with reduced oversight), so as always, these high level benchmarks are to be taken with a grain of salt.

jcfrei• 2 months ago

Maybe Im nitpicking here but LLMs are quite literal. So when you tell it to "implement a function for me" it will necessarily write the whole thing. Changing the prompt to "find an existing implementation for this" would be more apt.

torginus2• 2 months ago

It certainly was a bias in this case - I asked for a feature, mentioning to give me popular libraries in this space, then it started coding up a bespoke solution that included among other things, a custom HTML parser. Then asked to really consider using a library for the whole thing and it 'compromised' by pulling in a HTML parser, but still keeping its own implementation.

This is just a singular example, but I'be noticed a strong and beyond reasonable bias for this from multiple LLMs (like not using the already included dependency)

reinhash• 2 months ago

It is hard to distinguish hype from reality these days especially with Anthrophic's IPO around the corner.

But to their credit, I was very sceptical about the statements that "90% of the code will soon be written by AI" and even though we might not be at that point, I am surprised how far LLMs have gotten and how useful they have become. I can hardly image developing software the "old" way where I actually write my code by hand, like I used back in the day. The frontier models have become so powerful that I find myself in moments of surprise, where the LLM actually thought of edge cases that I would have missed

macwhisperer• 2 months ago

the HITL (human in the loop) is basically the single point...AI is a mirror..

it only "exists" when you talk to it.. much like your reflection in the mirror is only there when you're in view.

models can never be self-improving because it can never have "self". it can only mirror the appearance of self.

what's actually happening is "symbiotic group improvement".

our brains are resonant.. for those of use who are brilliant, getting leverage with ai just means that our innovative ideas become louder and more physically real every day.

eventually everything worth building will be built for free and made readily available.. no more "profiteering"

its Jevons paradox "efficiency breakthrough -> effort reduces -> growth potential rises -> transformative gains happen"...

some of us are in the "transformative phase"..

others haven't seen the "breakthrough moment" yet, but they will soon.

froh2• 2 months ago

I didn't see this discussed more on hn yet:

  We believe it would be good for the world to have the option to slow or temporarily pause frontier AI development to enable societal structures and alignment research to keep up with the advance of the technology. The Anthropic Institute will conduct research—in collaboration with many others—and take actions to help build the systems that a credible slowdown or pause would require. These systems would enable frontier AI developers to verify that others globally have actually stopped or slowed, and that a bad actor could not use the auspices of a coordinated slowdown to jump ahead in secret. If such systems existed, we expect that we would slow down or temporarily pause, if other developers at or near the frontier also did so in a verifiable manner.

ausbah• 2 months ago

these ppl are so full of themselves

froh2• 2 months ago

what do you mean?

if feasible this proposal is imho exactly what we need: a pause to collectively think how we get all the benefits without the potential harms.

to the non-techies around me I compare the boost of LLMs with the journey from slide rule via punch card driven computers through mainframes and PC to the smart phones of our days --- just within less than a decade, and we're at the transition from mainframe to PC with models that can produce reasonable output on a normal laptop.

how about we check we're getting where we want to get to, before getting to some dystopic place where everyone wonders how we got _there_?

I see nothing "full of themselves" in that.

brazukadev2• 2 months ago

When claude code removes React from its own code I'll believe that.

leevilux• 2 months ago

Wouldn't self-improvement mean that the LLM changes its neural network (i.e. the weights or layers or back propagation algorithm etc) or modify its training data?

dibujaron• 2 months ago

If it's actively building the next generation of itself, I'd say that counts. It's more like a parent raising their kid well than it is like a parent modifying their own mind, but the result is still that you have a better model in a year than you do now.

nicogentile• 2 months ago

The article seems nice and elegant but i dont get much of the point. The visual is super elegant but this is the kind of note where after 6 months we are going to see some shitty result and we are going to come back here and blame the IA. Hope doesnt happened.

When AI Builds Itself: Our progress toward recursive self-improvement

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