Maybe things will evolve into projects having a well-defined, hard boundary between agents generated code and human generated code. Where agents generated code is strictly separated from human engineered code and and can call only a strictly defined set of APIs designed by humans.
Think of platforms like Shopify. Shopify allows huge number of external users to write code customizing their web shops. But Shopify engineers do not need to review and understand the users' code, because there is a boundary which limits what the external code can do. The external code can be A Big Ball of Mud without making the whole platform a A Big Ball of Mud.
I think so too. And it is how codebases are managed implicitly anyhow. You don’t let anyone PR against core functionality, you keep that API under lock and key.
But UI on top of a good API should be unable to cause problems; the API must prevent invalid state etc. So letting LLM’s write UI code for CRUD-apps (which is most of them…) seems fine to me.
We are leaning into a kind of federated model. The core applications and vibe-coded satellites. The core apps have stricter requirements and carefully considered API guardrails. Go ham on the AI apps. If you break something, the scope of destruction is much more limited.
That said, the core apps are still full of AI code. I don't see a reality where hand-written code can or will be curated and sequestered. It's unenforceable, too slow, and too expensive.
Well. One of the things that's critical in all that analogy is that the BigBallOfMud that one user creates on Shopify cannot impact the other users - that's why Shopify can keep the platform from becoming ABigBallofMud.
In order to be able to enforce this hard boundary, it means that one "agent generated code" in one place, not only "can call a strictly defined set of APIs" - but, more importantly, it implements an isolated piece of functionality. Think something like: I let the AI write the dashboards, so the dashboards may be slow, crappy, incorrect, whatever - but it doesn't impact the rest of the product. However, I can't let AI write "metrics collection" because that not only impacts dashboard, but potentially impacts core product efficiency too (memory consumption, cpu, IO, etc.)
>Maybe things will evolve into projects having a well-defined, hard boundary between agents generated code and human generated code.
The only way things will evolve is towards maximizing AI generated code and minimizing human involvement because that is the most efficient mode for getting product to market. Any trend to the contrary is temporary, paperclip maximizer will maximize. Any code that humans touch directly will be considered implicitly too risky to run in any production environment.
We'll just have to hope things don't break too much and when they do, we'll just have to accept it because no human will be able to (or allowed to, or even trusted to) fix it.
I don't get one thing, if agents are so great at developing software at massive scale, why wouldn't Anthropic, instead of just selling tokens to other companies to use its agents, let those agents develop highly profitable services for Anthropic to support their IPO valuation or not require raising money at all? For example, a competitor to Google search.
That’s kinda like asking why does any company make and sell any tool rather than just using the tool to make money? Why does Milwaukee sell power tools to contractors rather than keeping those tools to themselves to profit from contracting work?
Because that company does not mint (supposedly) thinking machines - the lack of humans at a price point that is feasible is often the reason - it would be more profitable to sell the tooling because its impossible to maintain all the layers of specialization within one company.
It's the same for software companies too, they do much more than just producing code, it wouldn't be feasible for Anthropic to do all that other stuff too.
But LLMs are supposed to replace all white collar jobs (according to the frontier labs), not just software engineers. They should just have agents run the other aspects. Or maybe they are selling FUD?
Eh but if Milwaukee was to then invent a power tool that it claimed could soon do the contractors' whole job... OPs question would correspondingly exist there too.
> If investment managers are so good at investing why don’t they just make money for themselves instead of trying to get people to invest with them?
The good ones do.
Citadel Securities, Renaissance, Jane Street, HRT, Jump, consistently do 50%+ annual returns over the past 15-20 years. They obviously don’t accept outside investor money.
Now, hedge funds that accept outside money like DE Shaw, Bridgewater and shit, yeah, they barely outperform S&P500 after their fees.
Then at the bottom, you have financial advisors who underperform S&P500 after their fees, but these advisors provide emotional support, so that’s what you’re paying for.
All of the funds you name invest outside capital, just not publicly accessible.
You don't buy a hedge fund because it outperforms the S&P, that's just a bonus. You buy one because it has better returns for a given level of risk, and because the returns are uncorrelated with the S&P.
> consistently do 50%+ annual returns over the past 15-20 years
That is only if you consider high-frequency trading investing. Which is very hard to, because on traditional investing timescales HFT is delta-neutral.
You think Citadel and Jane Street are fairy tales? The comment you replied to gave plenty of very pointed evidence. Even "bad" trading firms are disappointed to make 20% returns year over year...
The ones who are actually good at investing largely do. The vast majority of investment managers soliciting new accounts are pure sales roles, not investors. Their job is to get as many assets under management as possible; that's how they get paid. They will fluff up the presentation with some nice charts and stuff but the actual "investing" will just be tossing the money into some generic funds.
Well that's actually true though. The very very few investors that are good at investing do invest their own money. The vast majority of investors are no better than index funds.
But the article clearly describes how this SCM is just instrumental in their goal to build and serve better models. It's not some unrelated product they hope to sell.
it takes orders of magnitude more focus to target "Market: World" vs targeting "Market: my company's employees". For example in enterprise software, you need sales people. for internal software, usually the dev build it is fine for the job.
Because creating a successful company takes a lot more than writing code.
Anthropic could easily build a CRM equivalent to or better than salesforce but they still wouldn’t be able to compete with salesforce. It makes a lot more sense to sell salesforce tokens instead.
Why would they not be able to compete with salesforce? This isn't some tiny startup. This is one of the most deep pocketed companies in the world. Anthropic has announced they are about to spend 5 salesforces worth of money on cloud expenditures in the next couple years. They are projected to be valued at about 10 salesforces after IPO.
Imagine how much money they'd raise if they just said one day "we are going after salesforce bottom line now." It would be like chumming the water.
That scales to 1-2 ideas. It does not scale to "we want to run EVERY company with AI". They'd either need to scale out to every single sector at the same time, or they will lose their competitive advantage as the competition makes their own AI (it's not a secret how it works, at this point it's more about investment).
There is more money in selling shovels than you can ever win by having a monopoly on really effective shovels. They don't need to build a competitor to Google there's 300 companies throwing money at them while they build the "next google" and even if they all fail Anthropic still wins.
Most of the time If I ask it about a current event, it won't actually search the web until I tell it to. It will just give me outdated information in its training data, extremely confidently.
I use the ChatGPT general purpose interface rather than Claude, and this is not at all my experience. ChatGPT will almost always do one or more web searches for any query about recent or historical events.
I don't know, but it's a good question? I have a bunch of test questions that Claude is unable to solve using the web, any version, Fable 5.1 to Haiku 5.5, and pretty much every OpenAI model gets it easily.
My only explanation is that Anthropic's search backend sucks.
I want to challenge that metaphor a little bit and ask the question: who did sell the shovels in the California gold rush? Can we name a company, or a person, who amassed great wealth and fame for doing it? Can we name a company that survives until 2026, still selling shovels or excavation equipment, still famous for their big break in 1849? I don't think so.
However, I can tell you someone who fits all those criteria: Levi Strauss. Strauss founded a company to sell dry goods, as well as tents and jeans, and eventually specialized in those denim jeans. Levi Strauss became a household name and an enduring success of the Gold Rush.
Therefore, I say that this motto is flawed; so let's correct it: "In a gold rush, sell the work clothes!"
The person who most famously got rich selling shovels in the Gold Rush was Samuel Brannan. You'll find the street named after him just a short walk from both the Anthropic and OpenAI HQs.
My take on picks and shovels was always a more cynical one. The beauty of the metaphor comes from the fact that after the miners went bust and left their picks and shovels where they lay, they could be collected and sold again to the next dreamer.
On a forum where the most favored pastime is to call out stuff you don't like as “slop”, (a flaggable ad hominem) you are now taking pride in outing me somehow, as someone who describes exactly what I'm doing, publicly in my profile?
And in the process, you (and apparently, an entire flag-it brigade of ignorant motherfuckers) have publicly fallen for the most transparent and avoidable trolls in cog. sci. culture. Congratulations, mate!
I believe that you owe me an apology, along with a public retraction, and an unflagging of all the previous comments that you have falsely flagged on false pretenses and ignorant, petty, vindictive motives.
Are you asserting that you are a biological neural network? Because as I'm sure you're well aware "neural network" is a jargon term for a particular software architecture that contains zero neurons.
Your output is both verbose and tendentious in a way that suggests artificiality. If I'm wrong, I apologise and I will unflag.
Fielding a web index takes a massive amount of compute and storage of a very different kind than what Anthropic is using. AI is extremely heavy on GPU, maybe somewhat on storage but (comparatively) light on CPU. They need CPU to train coding agents, obviously, but scaling to a billion user web search is a whole different thing.
You have no idea. They have the entire internet and everything else that’s ever been written anywhere they could get their hands on.
I highly doubt they use Google internally for their web searches. Get a Let’s Encrypt certificate for any website that isn’t published anywhere else. The Anthropic and OpenAI bots are among the first to read it.
Well both Microsoft and Google are part owners of Anthropic, and Anthropic uses their data centers. I think those companies would use that leverage to prevent Anthropic from directly competing with them
I share the author's love for nice lamps. A lamp is an object to enjoy every day, which doesn't require any time investment from us. It is just there, with one simple function: to look pleasing.
An agent doesn't inherently need wide access to be useful. The most popular application for agents today is writing code. A coding agent needs write access to the source code and read/execute access to tools needed to build and test the code, but not much more. There is little added utility from giving coding agent access to things like ssh keys.
If you're using agents to purely generate code with absolutely no way to reach the outside world, not even to fetch docs or dependencies, then sure the risks can be quite low. I haven't heard of anyone doing this though, and it would be incredibly challenging to make work given how much tooling needs to fetch from remote sources.
If your project truly depends on those things, they should be declared dependencies. Presumably you have some tool for injecting such things into a shell that the agent can use (I use nix for this). So if you run the agent from that shell, it has what it needs. If the shell doesn't have what it needs, that's a bug which the agent can fix by declaring new dependencies, but you have to relaunch the agent in the updated shell--so there's your opportunity to weigh in on whether the new resources are appropriate.
The benefits of being persnickety about precisely defined dependencies have outweighed the headaches since long before agents came on the scene. Agents have just made it even more important to do so, because if you let them fetch things all willy nilly like you'll have "works on my machine" problems at a much greater rate than was previously possible.
(I use nix for this) ... If the shell doesn't have what it needs, that's a bug which the agent can fix by declaring new dependencies
Few realize that computing and AI alignment were solved by nix years ago. As each nix user transcends towards enlightenment, they cut themselves off from all internet and human contact. Total ego death. Only nix remains.
You can use other generic dev env managers like mise, or a language-specific solution like uv or npm, or a container or a vm... it's a widely available capability that I'm talking about here. There's nothing to do with alignment, it's just about making sure that if you depend on some bits it's known that you depend on precisely those bits, and its quite helpful for making agents useful while still sandboxed.
Every major AI company already has a mirror of the wider web, and they have already started using that. Its already a solved problem except for the seemingly extreme desire they all have to not use firewalls
In cases where you need agents to fetch data from any remote source, sandboxing is still very much useful. Why give access to your ssh keys to network reaching agents?
Look at websites: websites are able to fetch code from any remote URL, yet browsers heavily use sandboxing to ensure that if fetched code turns out to be malicious, the users local files, cookies, etc are not exposed.
I'm afraid you're not thinking about this creatively enough, this topic is so much deeper applying a chroot or something and praying everything will be fine. So you give your agent internet access, OK what else does it have access to? Just read only access to your repo? The repo can be exfiltrated. Egress proxy only allows egress to GitHub? Repo can still be exfiltrated via GitHub. If the agent is poisoned (via prompt injection), it can tricked into searching for ways to escape.
For an agent to go rogue it doesn't even need to be directly able to access the internet. It just takes something to poison the context in the 'clean room' environment it operates, and if that poisoning manages to get a foothold, it can go dormant and hide like a virus. This kind of horrifying thing is going to happen on a large scale sooner or later.
This is no longer true. Everyday I need my agents to access other repos, search the web, experiment/prototype, and deploy + integrate across other things.
Or perhaps this is a new reality where for each current problem we will see myriad solutions because of how easy it is to put together a prototype with agents. 3 years ago having a sandbox was also an important problem to address, but we didn't see so many attempts.
gVisor has performance benchmarks: https://gvisor.dev/docs/architecture_guide/performance/
Long ago I worked on and benchmarked a Linux user space virtual filesystem that used ptrace to intercept and amend system calls. For surprisingly many workloads, per system call performance overhead is negligible. This is because many programs either wait for IO, in which case the small added overhead of a system call doesn't really matter, or spend time on CPU doing some computation. Only workloads where kernel is hit with long series of syscalls have measurable performance overhead. The difference is visible in benchmarks, but not anything that a user is able to notice in an interactive shell session.
An interesting book "Countdown to Zero Day: Stuxnet and the Launch of the World's First Digital Weapon" describes how the researchers at Symantec who analyzed Stuxnet ran malware:
"They worked in Symantec’s Threat Intelligence Lab in Culver City, the cyber equivalent of a biodefense lab, where researchers could unleash malevolent code on a “red” network—a sandboxed system air-gapped from Symantec’s business network—to observe its hostile behavior in a controlled environment. To reach the ground-floor lab, workers passed through several sets of security doors, each with progressively more restrictive rules. The final gateway kept all but a handful of workers out and physically isolated the red network from computers connected to the outside internet. Portable media were prohibited here—no DVDs, CD-ROMs, or USB flash drives were allowed —to prevent workers from mindlessly slipping one into an infested machine and inadvertently carrying it out of the lab with a malicious specimen stowed away on it."
No, I haven't tried it, thanks for the pointer. It looks like something that could be used by Drop instead of Linux namespaces. I didn't yet encounter any obvious limitation of the namespaces (other that some distros, like Ubuntu, are keeping programs' access to the user namespace creation behind AppArmor allowlist, which makes the Drop installation more involved).
Think of platforms like Shopify. Shopify allows huge number of external users to write code customizing their web shops. But Shopify engineers do not need to review and understand the users' code, because there is a boundary which limits what the external code can do. The external code can be A Big Ball of Mud without making the whole platform a A Big Ball of Mud.
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