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They also call out how it's more used for augmentation rather than full automation which will address some concerns the public has.
Tools empower those with knowledge further than those without knowledge. The fact that people were concerned layman were simply going to be able to take on experienced programmers at their day jobs was farcical.
Incredible how low usage is among lawyers. Does anyone have any intuition on why?
Part of it is selection bias, Claude is much less general-audiences than ChatGPT. But any lawyers using LLMs in 2025 deserve to be disbarred: "A Major Law Firm's ChatGPT Fail" https://davidlat.substack.com/p/morgan-and-morgan-order-to-s... "Lawyer cites six cases made up by ChatGPT" https://arstechnica.com/tech-policy/2023/05/lawyer-cited-6-f... "AI 'hallucinations' by ChatGPT end up costing B.C. lawyer" https://www.…
Awesome that there are releasing this paper and the associated data. I hope they'll do this regularly, so that changes can be tracked. One thing I hope they'll correct going forward is inclusion of API usage. Anecdotally, I only use Anthropic models via Cursor. So none of that usage shows up in here. I'd expect that specialized tools/interfaces like Cursor will grow and thus more usage will shift to API. It would be…
Even if they don’t train on the data they could break it down by user agent / API client ID and infer something about cursor traffic.
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Coffee for $5? That's a steal in this economy!
The coffee is made with the assistance of AI, which means some nonzero portion will be something other than coffee, but at least it means every sip is an adventure.
It's not the best choice, it's spacer's choice!
This more or less confirms what I imagine most of us thought, AI is mostly used by engineers, or for engineering tasks. Makes sense, I wonder how much traffic comes from automated tasks (co-pilot, etc). Every time I read a report like this I do wonder if we'll ever see an ROI on LLMs. HUNDREDS of billions of dollars of spend, and 3 years in its still primarily the same crowd using it, and has yet to create a "killer"…
Seems like Anthropic has too much money on their hands and are looking for ways to spend it. It’s surprising to see lean AI startups accumulate fat so quickly. Usually this sort of wheel spinning is reserved for large corporations. And it’s not just them. To me this trend screams “valuations are too high”, and maybe hints at “progress might start to stagnate soon”.
This more or less confirms what I imagine most of us thought, AI is mostly used by engineers, or for engineering tasks. Makes sense, I wonder how much traffic comes from automated tasks (co-pilot, etc). Every time I read a report like this I do wonder if we'll ever see an ROI on LLMs. HUNDREDS of billions of dollars of spend, and 3 years in its still primarily the same crowd using it, and has yet to create a "killer"…
We’re trying to use it for industrial apps. Been over a year of R&D. Some good but often mixed results. Adherence to prompts is a big issue for us. It’s most useful not as a chatbot but to give explained descriptions of what the user is seeing, so they don’t need to dig down into 20 graphs and past history. That necessitates being able to refer to things with URIs which works 95% of the time but the 5% is killer sinc…
Earlier quoted context omitted.
Tools empower those with knowledge further than those without knowledge. The fact that people were concerned layman were simply going to be able to take on experienced programmers at their day jobs was farcical.
I'm not a dev but I thought the issue from a senior dev perspective was AI on AI, not layman on AI?
I suspect that a) will get better over time. I also suspect that b) can be addressed by a pre-programmed prompt-flow that uses a LLM to gather requirements from a PM and ask probing questions to get a well-defined scope and agree on how edge cases should be handled. It doesn't seem far-fetched that a AI also would be able to call out small requirement changes that might allow for much simpler/faster solutions.
To what degree can you really trust these data? They obviously have a financial interest in playing with the numbers.
Unless they are trying to mislead competitors (who don't look at their own numbers...), they have no reason at all to game those numbers there.