louiereederson

Surveillance for all

The people in this image remind me of early this person does not exist, in the best way

The image of the messy desktop with the ASCII art is so impressive - the text renders, the date is consistent, it actually generated ASCII art in "ChatGPT", etc. I was skeptical that it was cherry-picked but was able to generate something very similar and then edit particular parts on the desktop (i.e. fixing content in the browser window and making the ASCII dog "more dog like"). It's honestly astounding, to me at least.

That Reddit account is only 3 days old and this is their only post so probably not credible. This would have strategic merit as noted already, but seems difficult to justify for Anthropic as a private company given they are horribly computer constrained and have more pressing needs for cash. It could be possible if/when they IPO though.

I think it's difficult to say agentic and human developer labor are fungible in the real world at this point. Agents may succeed in discrete tasks, like those in a benchmark assessment, but those requiring a larger context window (i.e. working in brownfield systems, which is arguably the bulk of development work) favor developers for now. Not to mention that at this point a lot of necessary context is not encoded in an enterprise system, but lives in people's heads.

I'd also flip your framing on its head. One of the advantages of human labor over agents is accountability. Someone needs to own the work at the end of the day, and the incentive alignment is stronger for humans given that there is a real cost to being fired.

I meant reference Toby Ord's work here. I think his framing of the performance/cost frontier hasn't gotten enough attention https://www.tobyord.com/writing/hourly-costs-for-ai-agents

LLMs exist on a logaritmhic performance/cost frontier. It's not really clear whether Opus 4.5+ represent a level shift on this frontier or just inhabits place on that curve which delivers higher performance, but at rapidly diminishing returns to inference cost.

To me, it is hard to reject this hypothesis today. The fact that Anthropic is rapidly trying to increase price may betray the fact that their recent lead is at the cost of dramatically higher operating costs. Their gross margins in this past quarter will be an important data point on this.

I think the tendency for graphs of model assessment to display the log of cost/tokens on the x axis (i.e. Artificial Analysis' site) has obscured this dynamic.

I mean there is a runtime layer that needs to be developed, and some of it may live in CC/Codex and some might live in the various enterprise systems. Someworkflow automations and some amount of the semantic layer may for instance exist in your CRM/ERP/data platform. Yes the front-end would be owned by the chat interface, but part of the solution may exist in the various enterprise systems. This would be closer to a distributed system than a monolith. The demos and marketing language point to this as the direction of travel (i.e. the reference to Atlassian Rovo, etc.).

Maybe but the product category is not necessarily a monolith in the same way that Claude Code is. These general purpose tools will have to action across a heterogeneous set of enterprise systems/tools. A runtime environment must be developed to do that but where that of the agent ends and that of the enterprise systems begins is a totally open question.

I don't doubt it, I just mean the decision to release/not release generally may also be informed by the commercial/economic viability of the model for general usage patterns versus extremely high value patterns like vulnerability assessment

I don't think you can say this with confidence, outside-in. It's not just about safety. The additional unknown is cost - I don't just mean API cost, but fully loaded cost for a given task. Is the model cost effective for tasks such that it has product market fit?

We don't yet know if Mythos was a level shift in the capability/cost frontier, or a continued extension of the same logarithmic capability/cost curve.

Successful over what time frame? It's way too early to declare victory.

TBPN seems like the media equivalent of Soylent. Oh wait...

Funny how everyone gravitated towards analysis of the star distribution of REPOS when the headline claim is on ADDITIONS. If you look at my comment below (invite you to verify the stats), the distribution of additions by star count is far more weighted to 2+ star repos in GitHub overall. The observation is meaningful, up to the observer to draw a conclusion. Is Claude just speeding up output or is it generating piles of spaghetti code with no use? Considering the get rich quick economy that has sprung up around app development, I'm inclined to at least consider the latter.

They announced a $30b+ commitment with Azure back in November, so not really a surprise that Azure is now listed as one of their cloud providers. https://www.anthropic.com/news/microsoft-nvidia-anthropic-an...

OP. I'm not a confident SQL user so encourage someone to double check this. From what I can tell have been 2.21x10^12 additions on GitHub in total, 6.36x10^11 of which are in repos with 2+ stars. That's about 29%. People earlier were comparing the star distribution of repos which is not really what this is about - it is about OUTPUT, as measured by additions.

Interestingly, there are 21.37b commits in GitHub, implying 104 additions per commit. Per the dashboard, Claude is linked to 20.81m commits and 50.44b additions - or 2,424 additions/commit. So additions for Claude-linked repos is higher, and it's actually higher for repos with 0-1 stars (2,568 additions/commit for Claude, 91 for all GitHub). None of this is a smoking gun but aligns with the intuition that Claude is producing enormous amounts of code. TBD whether it is 'adding value'.

Would be appreciative of anyone who verifies/invalidates this. https://play.clickhouse.com/ https://ghe.clickhouse.tech/#clickhouse-demo-access

That is fair, in fact I just came across their recent blog post on this. They're pointing to usage growth as the issue https://github.blog/news-insights/company-news/addressing-gi...

Just to clarify as OP, the point here is not that Claude is not contributing to serious work, just that the dashboard suggests a lot of usage in public GitHub repos seems to be tied to low attention, high LOC repos. This is at least something to keep in mind when considering the composition of coding agent usage, and when assessing the sustainability of current trends.

In hindsight the headline was a bit more sensational than I meant it to be!

I hope you don't mind, I thought this was a really valuable dashboard.

The instability is related to their Azure migration isn't it? Cynically you could say it hasn't been helped by the rolling RIFs at Microsoft

Toggling the stars shows 50b lines of code created across all projects, only 5b on projects with 2+ stars since Claude Code launch. Kind of eye opening where these Claude Code tokens are going.

Came across this from this ShowHN post yesterday https://news.ycombinator.com/item?id=47501348

This is great, thank you! I've been looking for something like this for a while now.

Interesting that whoever is developing BroadwayScore.com appears to be one of the biggest users of Claude Code, if I'm reading this correctly (25m lines created, 20m lines deleted when 'since launch' is toggled). Might give you an idea of how this is being used. https://github.com/thomaspryor/Broadwayscore

That would not be stochastic, just parroting

I think for your comment to follow the guidelines, you need to explain why the original comment did not follow them.

Customer values are relevant to the discussion given that they impact choice and therefore competition.

And they're reportedly back in talks with the DOW per the FT (below).

They are not the exception, and are just as bloodlessly, shamelessly publicity hungry as any other tech co, if not more so. No surprise based on their conduct up until this fake event.

https://news.ycombinator.com/item?id=47256452

Apple is a two sided market between developers and users. OpenAI has not succeeded in building this so far.

This article is bad. It is mixing up capex and opex. OpenAI is projecting more spending on compute through their income statement now than they were 6 months ago.

Seems like code production is up but mainly in feature branches. Main branch changes are down. MTTR deteriorating. This is for all but the highest performing (top 5%ile) teams.

This has to be driven by AI adoption. I'm trying to keep an open mind, but I can see how this is productive. Maybe the optimistic take is the top 5% are showing the way and the remainder will follow? That seems a bit too optimistic though, because the bottom 95% are probably burdened by technical/organizational debt that limits their ability to adapt quickly enough.

I think this was the best write up on the impact of AI on software engineering I've read yet. By extension it might be the best 'take' on AI I've read period.

Alas it is not written by AI and boosted on X (which is owned by an LLM model vendor), and therefore will not get 80m views or whatever.

Wow thank you, I didn't know about this feature