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I would say the underlying principle was ensuring a tight, highly relevant context (e.g. choose the "right" task size and load only the relevant files or even code snippets, not the whole codebase; more manual work upfront, but almost guaranteed one-shot results.)
With newer models the sharper edges have largely disappeared, so you can hold them pretty much any which way and still get very good results. I'm not sure how much of this is from the improvements in the model itself vs the additional context it gets from the agentic scaffolding.
I still maintain that we need to adapt ourselves to this new paradigm to fully leverage AI-assisted coding, and the future of coding will be pretty strange compared to what we're used to. As an example, see Gas Town: https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d...
It's just the same agent swarm orchestration that most agent frameworks are using, but with quirky marketing. All of that is just based on the SDLC [PM/Architect -> engineer planning group -> engineer -> review -> qa/evaluation] loop most people here should be familiar with. So actually pretty banal, which is probably part of the reason Steve decided to be zany.
I agree with your framing that measuring should NOT be separated from political issues, but each can be made clear separately (framing it as "training the tools of the oppressor" seems to conflate measuring tool usefulness with politics).
The vast majority of coders in employment barely write anything more complex than basic CRUD apps. These jobs were always going to be automated or abstracted away sooner or later.
Every profession changes. Saying that these new tools are useless or won't impact you/xyz devs is just ignoring a repeated historical pattern
And it's actually kind of amazing, because a lot of people who earn six figures programming Salesforce came to it from a non-traditional software engineering background.
Similarly, Lisp's homoiconicity makes sense to me as a wonderfully aesthetic idea. I remember generating strings-of-text that were code, but still just text, and wishing that I could trivially step into the structure there like it was a map/dict... without realizing that that's what an AST is and what the language compiler / runtime is already always doing.
[1] Like the recent "Gas Town" and "Beads" that people keep mentioning in the comments that require extensive scripts/human intervention to purge from the system: https://news.ycombinator.com/item?id=46510121
My experience has been negative progress in this field. On iOS, UIKit in Interface Builder is an order of magnitude faster to write and to debug, with less weird edge cases, than SwiftUI was last summer. I say last summer because I've been less and less interested in iOS the more I learn about liquid glass, even ignoring the whole "aaaaaaa" factor of "has AI made front end irrelevant anyway?" and "can someone please suggest something the AI really can't do so I can get a job in that?"
Too bad they were mostly proprietary and won't even run in modern hardware.
It's the same with artists who are now pissed that regular people can manifest their artistic ideas without needing to go through an artist or spend years studying the craft. The artists are calling the AI companies oppressors because they are breaking the artist's stranglehold on the market.
It's incredibly ironic how socializing what was a privatized ability has otherwise "socialist" people completely losing their shit. Just the mask of pure virtue slipping...
Software development was already one of the most democratised professions on earth. With any old dirt cheap used computer, an internet connection, and enough drive and curiosity you could self-train yourself into a role that could quickly become a high paying job. While they certainly helped, you never needed any formal education or expensive qualifications to excel in this field. How is this better?
Maybe not as good, but they can certainly do far far more than what was available a few years ago.
That's primarily why I finally had to suck it up and sign up for Claude. Claude clearly can cough up proprietary codebase examples that I otherwise have no access to.
As far as I can tell the reason OpenAI and Anthropic are ahead in code is that they've invested extremely heavily in figuring out the right reinforcement learning training mix needed to get great coding results.
Some of the Chinese open models are already showing signs of catching up.
> simonw: It's better because now you can automate something tedious in your life with a computer without having to first climb a six month learning curve.
Completely ignores, or enthusiastically accepts and endorses, the consolidation of production, power, and wealth into a stark few (friends), and claims superiority and increased productivity without evidence?
This may be the most simonw comment I have ever seen.
I'm not worried about that at all any more. There are dozens of organizations who have achieved that milestone now, and OpenAI aren't even definitively in the lead.
A lot of those top-class models are open weight (mainly thanks to the Chinese labs) and available for people to run on their own hardware.
I wrote a bunch more about this in my 2024 wrap-up: https://simonwillison.net/2024/Dec/31/llms-in-2024/#the-gpt-...
She used to log into 3 different websites. Now she just opens localhost:3000 and has all of them on the same page. No emails shared with anyone. All data stored locally.
I could have done this earlier but the time commitment with Claude Code now was writing a spec in 5-minutes and pressing approve a few times vs half a day.
I count this as an absolute win. No privacy breaches, no data sharing.
Tt's because these companies profit from all the existing art without compensating the artists. Even worse, they are now putting the very people out of a job who (unwittingly) helped to create these tools in the first place. Not to mention how hurtful it must be for artists seeing their personal style imitated by a machine without their consent.
I totally see how it can empower regular people, but it also empowers the megacorps and bad actors. The jury is still out on whether AI is providing a net positive to society. Until then, let's not ignore the injustice and harm that went into creating these tools and the potential and real dangers that come with it.
Ascribing the goals of "democratize code/art" onto these companies and their products is called delusion.
I am sure the 3 letter agency directors on these company boards are thrilled you think they left their lifelong careers solely to finally realize their dream to allow you to code and "manifest your artistic ideas".
So maybe celebrate open/private/local models for empowering people rather than selfishly complain about it?
It's more economical for the average person to spend $20/month on a subscription than it is for them to drop multiple thousands $ and untold hours of time experimenting. Local AI is a fun hobby though.
It's incredibly ironic how blatant theft has left otherwise capitalistic people so enthusiastic.
I'm kind of fascinated by how AI has become such a culture war topic with hyperbole like "tools of the oppressor"
It's equally fascinating how little these comments understand about how LLMs work. Using an LLM for inference (what you do when you use Claude Code) does not train the LLM. It does not learn from your code and integrate it into the model while you use it for inference. I know that breaks the "training the tools of the oppressor" narrative which is probably why it's always ignored. If not ignored, the next step is to decry that the LLM companies are lying and are stealing everyone's code despite saying they don't.
The prompts and responses are used as training data. Even if your provider allows you to opt out they are still tracking your usage telemetry and using that to gauge performance. If you don’t own the storage and compute then you are training the tools which will be used to oppress you.
Incredibly naive comment.
They show a clear pop-up where you choose your setting about whether or not to allow data to be used for training. If you don't choose to share it, it's not used.
I mean I guess if someone blindly clicks through everything and clicks "Accept" without clicking the very obvious slider to turn it off, they could be caught off guard.
Assuming everyone who uses Claude is training their LLMs is just wrong, though.
Telemetry data isn't going to extract your codebase.
I am curious where your confidence that this is true, is coming from?
Besides lots of GPU's, training data seems the most valuable asset AI companies have. Sounds like strong incentive to me to secretly use it anyway. Who would really know, if the pipelines are set up in a way, if only very few people are aware of this?
And if it comes out "oh gosh, one of our employees made a misstake".
And they already admitted to train with pirated content. So maybe they learned their lesson .. maybe not, as they are still making money and want to continue to lead the field.
1. There are good, ethical people working at these companies. If you were going to train on customer data that you had promised not to train on there would be plenty of potential whistleblowers.
2. The risk involved in training on customer data that you are contractually obliged not to train on is higher than the value you can get from that training data.
3. Every AI lab knows that the second it comes out that they trained on paying customer data saying they wouldn't, those paying customers will leave for their competitors (and sue them int the bargain.)
4. Customer data isn't actually that valuable for training! Great models come from carefully curated training data, not from just pasting in anything you can get your hands on.
Fundamentally I don't think AI labs are stupid, and training on paid customer data that they've agreed not to train on is a stupid thing to do.
2. The risk of using "illegal" training data is irrelevant, because no GenAI vendors have been meaningfully punished for violating copyright yet, and in the current political climate they don't expect to be anytime soon. Even so,
3. Presuming they get caught redhanded using personal data without permission- which, given the nature of LLMs would be extremely challenging for any individual customer to prove definitively- they may lose customers, and customers may try to sue, but you can expect those lawsuits to take years to work their way through the courts; long after these companies IPO, employees get their bag, and it all becomes someone else's problem.
4. The idea of using carefully curated datasets is popular rhetoric, but absolutely does not reflect how the biggest GenAI vendors do business. See (1).
AI labs are extremely shortsighted, sloppy, and demonstrably do not care a single iota about the long term when there's money to be made in the short term. Employees have gigantic financial incentives to ignore internal malfeasance or simple ineptitude. The end result is, if anything, far worse than stupidity.
Anthropic had to pay $1.5bn after being caught downloading pirated ebooks.
First: Valuations are based on expected future profits.
For a lot of companies, 1% of valuation is ~20% of annual profit (P/E ratio 5); for fast growing companies, or companies where the market is anticipating growth, it can be a lot higher. Weird outlier example here, but consider that if Tesla was fined 1% of its valuation (1% of 1.5 trillion = 15 billion), that would be most of the last four quarter's profit on https://www.macrotrends.net/stocks/charts/TSLA/tesla/gross-p...
Second: Part of the Anthropic case was that many of the books they trained on were ones they'd purchased and destructively scanned, not just pirated. The courts found this use was fine, and Anthropic had already done this before being ordered to: https://storage.courtlistener.com/recap/gov.uscourts.cand.43...
My confidence comes from working in big startups and big companies with legal teams. There's no way the entire company is going to gather all of the engineers and everyone around, have them code up a secret system to consume customer data into a secret part of the training set, and then have everyone involved keep quiet about it forever.
The whistleblowing and leaking would happen immediately. We've already seen LLM teams leak and and have people try to whistleblow over things that aren't even real, like the Google engineer who thought they had invented AGI a few years ago (lol). OpenAI had a public meltdown when the employees disagreed with Sam Altman's management style.
So my question to you is: What makes you think they would do this? How do you think they'd coordinate the teams to keep it all a secret and only hire people who would take this secret to their grave?
No, that is why I wrote
"Who would really know, if the pipelines are set up in a way, that only very few people are aware of this?" (Typo fixed)
There is no need for everyone to know. I don't know their processes, but I can think of ways to only include very few people who need to know.
The rest is just working on everything else. Some work with data, where they don't need to know where it came from, some with UI, some with scaling up, some .. they all don't need to know, that the source of DB XYZ comes from a dark source.
We have a legal binding contract with Anthropic. Checked and vetted by our laywers, who are annoying because they actually READ the contracts and won't let us use services with suspicious clauses in them - unless we can make amendments.
If they're found to be in breach of said contract (which is what every paid user of Claude signs), Anthropic is going to be the target of SO FUCKING MANY lawsuits even the infinite money hack of AI won't save them.
We have stopped using major services because of their TOS wording, Midjourney being one.
Could be, but it's a huge risk the moment any lawsuit happens and the "discovery" process starts. Or whistleblowers.
They may well take that risk, they're clearly risk-takers. But it is a risk.
[1]https://www.cbc.ca/news/business/anthropic-ai-copyright-sett...
The training was OK, but the piracy wasn't, they were held accountable for that.
so there's no risk
AI threads really bring out the extreme hyperbole and doomerism.
I find it hard to believe there are people who know these companies stole the entire creative output of humanity and egregiously continually scrape the internet are, for some reason, ignoring the data you voluntarily give them.
> I know that breaks the "training the tools of the oppressor" narrative
"Narrative"? This is just reality. In their own words:
> The awards to Anthropic, Google, OpenAI, and xAI – each with a $200M ceiling – will enable the Department to leverage the technology and talent of U.S. frontier AI companies to develop agentic AI workflows across a variety of mission areas. Establishing these partnerships will broaden DoD use of and experience in frontier AI capabilities and increase the ability of these companies to understand and address critical national security needs with the most advanced AI capabilities U.S. industry has to offer. The adoption of AI is transforming the Department’s ability to support our warfighters and maintain strategic advantage over our adversaries [0]
Is 'warfighting adversaries' some convoluted code for allowing Aurornis to 'see a 1337x in productivity'?
Or perhaps you are a wealthy westerner of a racial and sexual majority and as such have felt little by way of oppression by this tech?
In such a case I would encourage you to develop empathy, or at least sympathy.
> Using an LLM for inference .. does not train the LLM.
In their own words:
> One of the most useful and promising features of AI models is that they can improve over time. We continuously improve our models through research breakthroughs as well as exposure to real-world problems and data. When you share your content with us, it helps our models become more accurate and better at solving your specific problems and it also helps improve their general capabilities and safety. We do not use your content to market our services or create advertising profiles of you—we use it to make our models more helpful. ChatGPT, for instance, improves by further training on the conversations people have with it, unless you opt out.
[0] https://www.ai.mil/latest/news-press/pr-view/article/4242822...
[1] https://help.openai.com/en/articles/5722486-how-your-data-is...
Much as I despair at the current developments in the USA, and I say this as a sexual minority and a European, this is not "tools of the oppressor" in their own words.
Trump is extremely blunt about who he wants to oppress. So is Musk.
"Support our warfighters and maintain strategic advantage over our adversaries" is not blunt, it is the minimum baseline for any nation with assets anyone else might want to annex, which is basically anywhere except Nauru, North Sentinel Island, and Bir Tawil.
I think its gross to distill military violence as defending 'assets [others] might want to annex'.
What US assets were being annexed when US AI was used to target Gazans?
https://apnews.com/article/israel-palestinians-ai-technology...
> Trump is extremely blunt about who he wants to oppress. So is Musk.
> our adversaries" is not blunt
These two thoughts seem at conflict.
What 'assets' were being protected from annexation here by this oppressive use of the tool? The chips?
Yes, but that's how the world works:
Another country wants a bit of your country for some reason, they can take it by force unless you can make at the very least a credible threat against them, sometimes a lot more than that.
Note that this does not exclude that there has to be an aggressor somewhere. I'm not excluding the existence of aggressors, nor the capacity for the USA to be an aggressor. All I'm saying is your quotation is so vague as to also encompass those who are not.
> What US assets were being annexed when US AI was used to target Gazans?
First, I'm saying the statement is so broad as to encompass other things besides being a warmonger. Consider the opposite statement: "don't support our warfighters and don't maintain strategic advantage over our adversaries" would be absolutely insane, therefore "support our warfighters and maintain strategic advantage over our adversaries" says nothing.
Second, in this case the country doing the targeting is… Israel. To the extent that the USA cares at all, it's to get votes from the large number of Jewish people living in the USA. Similar deal with how it treats Cuba since the fall of the USSR: it's about votes (from Cuban exiles in that case, but still, votes).
Much as I agree that the conduct of Israel with regard to Gaza was disproportionate, exceeded the necessity, and likely was so bad as to even damage Israel's long-term strategic security, if you were to correctly imagine the people of Israel deciding "don't support our warfighters and don't maintain strategic advantage over our adversaries", they would quickly get victimised much harder than those they were victimising. That's the point there: the quote you cite as evidence, is so broad that everyone has approximately that, because not having it means facing ones' own destruction.
There's a mis-attributed quote, "People sleep peaceably in their beds at night because rough men stand ready to do violence on their behalf", that's where this is at.
> These two thoughts seem at conflict.
Musk is openly and directly saying "Canada is not a real country.", says "cis" is hate speech, response to pandemic was tweeting "My pronouns are Prosecute/Fauci.", and self-justification for his trillion dollar bonus for hitting future targets is wanting to be in control of what he describes as a "robot army"; Trump openly and explicitly wants the USA to annex Canada, Greenland, Panama canal, is throwing around the national guard, openly calls critics traitors and calls for death penalty. They're a subtle as exploding volcanoes, nobody needs to take the worst case interpretations of what they're saying to notice this.
Saying "support our warfighters" is something done by basically every nation everywhere all the time, because those places that don't do this quickly get taken over by nearby nations who sense weakness. Which is kinda how the USA got Texas, because again, I'm not saying the USA is harmless, I'm saying the quote doesn't show that.
> What 'assets' were being protected from annexation here by this oppressive use of the tool? The chips?
This would have been a much better example to lead with than the military stuff.
I'm absolutely all on board with the general consensus that the US police are bastards in this specific way, have been since that kid got shot for having a toy gun in an open-carry state. (I am originally from a country where even the police are not routinely armed, I do not value the 2nd amendment, but if you're going to say "we allow open carry of firearms" you absolutely do not get to use "we saw someone carrying a firearm" as an excuse to shoot them).
However: using LLMs to code doesn't seem to be likely to make a difference either way for this. If I was writing a gun-detection AI, perhaps I'm out of date, but I'd use a simpler model that runs locally on-device and doesn't do anything else besides the sales pitch.