> Look at my drafts that were started within the last three months and then check that I didn’t publish them on simonwillison.net using a search against content on that site and then suggest the ones that are most close to being ready
This is a very detailed, particular prompt. The type of prompt a programmer would think of as they were trying to break down a task into something that can be implemented. It is so programmer-brained that I come away not convinced that a typical user would be able to write it.
This isn’t an AI skepticism post - the fact that it handles the prompt well is very impressive. But I’m skeptical that the target user is thinking clearly enough to prompt this well.
It takes a certain amount of expertise to use LLMs effectively. And I know that some people claim otherwise but they simply aren't worth listening to.
Just because Claude Cowork is for "other" kinds of work, not just software engineering, doesn't in any way change that. It's not like other kinds of knowledge work aren't being done by intelligent professionals who invest time into learning how to use complicated software and systems
That is to say, I don't know who the "target user" of this is, but it is a $100/month subscription, so it's presumably someone who is a pretty serious AI user.
One part I like about LLMs is that they can smooth over the rough edges in programming. Lots of people can build pretty complicated spreadsheets, can break down a problem into clear discrete tasks, or can at least look at a set of steps and validate that solves the issue they have & more easily updated it. Those people don’t necessarily know json isn’t a person, how to install python or how to iterate over these things. I cant give directions in Spanish but its not because I don’t know how to get to the library its just I can’t translate precisely.
Also you may only need someone to write the meta prompt that then spits out this kind of thing given some problem “I want to find the easiest blog posts to finish in my drafts but some are already published” then a more detailed prompt out of it, read it and set things going.
I enjoyed hearing Claude Code creator Boris Cherny talk about "latent demand"[0], which is when users start using your product for something it was not intended for. When that happens, it's a great signal that you should go build that into a full product.
Cowork seems like a great application of that principle.
Leveraging Claude Code in a Linux shell to do all sorts of stuff has been an amazing superpower for me, and I think for many others. Cowork is a promising next step to democratize this superpower for others.
If Microsoft, in creating their next gen agentic OS, wants to replace Windows with the Linux kernal, Claude Code, and bash shell (turning Windows into a distribution of sorts,) more power to them. However, I doubt this is the direction they'll go.
This is a nice technical account that we're used to seeing from Simon.
I get a kick out of the fact that Microsoft has been preciously clinging to the "Copilot" branding and here comes Claude coming saying "Cowork? Good enough for us!".
-
Taking a step back, I really would love to see a broader perspective -- an account of someone who is not tech savvy at all. Someone who works a basic desk job that requires basic competency of microsoft word. I'm so deep into the bubble of AI-adjacent people that I haven't taken stock of how this would or could empower those who are under-skilled.
We've taken it as truth that those who benefit most from AI are high-skilled augmenters, but do others see some lift from it? I'd love if anthropic tried to strap some barely-performing administrative assistants into these harnesses and see if there's a net benefit. For all I know, it's not inconceivable that there be a `rm -rf` catastrophe every other hour.
This predates Cowork, but I have started to see "non-technical" journalists start taking Claude Code seriously recently. For instance, Joe Weisenthal has been writing about this, eg.: https://nitter.net/thestalwart/status/2010512842705735948.
>Someone who works a basic desk job that requires basic competency of microsoft word.
I dont actually think there many of those people out there. And those that are, are on their way out. There are basically none of those people entering the work force. There are tons of people with that sort of computer literacy but they aren't working on computers.
Eh, I can think of some examples for sure, I think there are still a lot of people like this.
* Bookkeeper & planning approval within city government
* Doctor/dentist/optometry receptionist & scheduler (both at independent offices and at major hospitals)
* Front desk staff at almost every company with a physical front desk
* University administrative staff (there can be a lot more of these people than you'd think)
* DMV workers
* Probably lots of teachers
Those jobs all will use other software as well, but a lot of their job is making and filling forms on a computer, where they are likely needing to use MS Word fairly often to write things up.
I think Claude Cowork should come with a requirement or a very heavily structured wizard process to ensure the machine has something like a Time Machine backup or other backups that are done regularly, before it is used by folks.
The failure modes are just too rough for most people to think about until it's too late.
I worry this is gonna cause even more sensitive/privilaged data extrafiltration than currently is happening. And most “normies” won't even notice.
I know the counterargument is people are already putting in company data via ChatGPT. However, that is a conscious decision. This may happen without people even recognizing that they are “spilling the beans”.
I think you're right, but the issue goes deeper. If the productivity gains are real, the incentive to bypass security becomes overwhelming. We are going to see a massive conflict where compliance tries to clamp down, but eventually loses to 'getting work done.'
Even if critics are right that these models are inherently insecure, the market will likely settle for 'optically patched.' If the efficiency gains are there, companies will just accept the residual risk.
I just used Claude Code to do something that would have taken my wife 3+ days
She has to go through about 100 resumes for a position at her college. Each resume is essentially a form the candidate filled out and lists their detailed academic scores from high school > PhD, their work experience, research and publications.
Based on the declared data, candidates are scored by the system
Now this is India and there's a decent amount of fraud, so an individual has to manually check the claimed experience/scores/publications against reality
A candidate might claim to have relevant experience, but the college might be unaccredited, or the claimed salary might be way too low for a relevant academic position. Or they might claim to have published in XYZ journal, but the journal itself might be a fraudulent pay-to-publish thing
Going through 100+ resumes, each 4 pages long is a nightmare of a task. And boring too.
--
So I asked Claude Code to figure out the problem. I gave it a PDF with the scoring guidelines, a sample resume, and asked it to figure out the problem
Without me telling it, it figured out a plan that involved checking a college's accredition and rating (the govt maintains a rating for all colleges), the claimed salary vs actual median salary for that position (too low is a red flag), and whether the claimed publication is in either the SCOPUS index or a govt approved publications index
(I emphasize govt approved because this is in a govt backed institution)
Then I gave it access to a folder with all the 100 resumes.
In less than 30 minutes, it evaluated all candidates and added the evaluation to a CSV file. I asked it to make it more readable, so it made a HTML page with data from all the candidates and red/green/yellow flags about their work-experience, publications, and employment
It made a prioritized list of the most promising candidates based on this data
My wife double checked because she still "doesn't trust AI", but all her verification almost 100% matched Claude's conclusions
This was a 3 day, grinding task done in 30 minutes. And all I did was type into a terminal for 20 minutes
Given the data exfil vulnerability a few stories down HN's front page I would be extremely hesitant to ask Claude to process a document someone else produced and sent to me
Was the double-checking done in that 30 minutes? The fact that it wasn't 100% right means that the human in the loop was still important, so I'm just trying to understand the actual time saved.
He's a proponent, but that doesn't mean his analysis isn't useful. It's clear and mostly accurate and when he gets something wrong he makes it right. Does he do all that with rose tinted glasses, probably, but my experience reading him is that he's sharp, thoughtful, and entirely reasonable.
Dismissing the opportunity to learn because the person offering you knowledge is enthusiastic about his area of expertise is probably shortsighted.
This is more akin to a race car driver give a review of, for example, a new type of electric car. It doesn’t matter that the driver is not a domain expert in electric motors and regenerative braking; what matters is he knows how to operate these machines in their use case at the limits.
Hearing a programming legend weigh in on the latest programming tool seems entirely completely reasonable.
Very generous example there. Except it’s more like an accomplished car YouTuber reviewing beta autopilot. They’ll tell you it’s “amazing” on a clear highway, ignore the scary edge cases, and somehow every conclusion aligns with what gets more views and forum clout.
I don't think they were being dismissive. They just said they were skeptical, which is generally a good thing. It's certainly better than the goofy hero worship I constantly see on HN.
This is some low hanging fruit that keeps getting driven by in order to speed up development. There is so so much potential here. If this can replace the RPS consulting industry I won't be unhappy. Let individuals do it themselves so they have time to work themselves into some other position or move up/take on more responsibility.
For me, I recently wanted to assemble a “supercut” of my videos of attempts at learning to bunny-hop a bike. The tool was able to craft a python script that used ffmpeg to edit out the no-motion portions of the videos and stitch them together.
This would have taken ages to do by hand in iMovie, and probably just as long to look up the needed parameters in ffmpeg, but Claude code got it right in the first try, and worked with me to fine-tune the motion detection threshold.
One rough edge for me: the cowork interface seems to have turned off “extensions” - my first ask was to read some emails and compare with some local documents and draft a document. It kept trying to use claude chrome to navigate to gmail.
I’m not sure what the plan for integrating extensions is here but they definitely will be wanted.
This is a very detailed, particular prompt. The type of prompt a programmer would think of as they were trying to break down a task into something that can be implemented. It is so programmer-brained that I come away not convinced that a typical user would be able to write it.
This isn’t an AI skepticism post - the fact that it handles the prompt well is very impressive. But I’m skeptical that the target user is thinking clearly enough to prompt this well.
Just because Claude Cowork is for "other" kinds of work, not just software engineering, doesn't in any way change that. It's not like other kinds of knowledge work aren't being done by intelligent professionals who invest time into learning how to use complicated software and systems
That is to say, I don't know who the "target user" of this is, but it is a $100/month subscription, so it's presumably someone who is a pretty serious AI user.
Also you may only need someone to write the meta prompt that then spits out this kind of thing given some problem “I want to find the easiest blog posts to finish in my drafts but some are already published” then a more detailed prompt out of it, read it and set things going.
Cowork seems like a great application of that principle.
[0] https://www.youtube.com/watch?v=AmdLVWMdjOk
If Microsoft, in creating their next gen agentic OS, wants to replace Windows with the Linux kernal, Claude Code, and bash shell (turning Windows into a distribution of sorts,) more power to them. However, I doubt this is the direction they'll go.
I get a kick out of the fact that Microsoft has been preciously clinging to the "Copilot" branding and here comes Claude coming saying "Cowork? Good enough for us!".
-
Taking a step back, I really would love to see a broader perspective -- an account of someone who is not tech savvy at all. Someone who works a basic desk job that requires basic competency of microsoft word. I'm so deep into the bubble of AI-adjacent people that I haven't taken stock of how this would or could empower those who are under-skilled.
We've taken it as truth that those who benefit most from AI are high-skilled augmenters, but do others see some lift from it? I'd love if anthropic tried to strap some barely-performing administrative assistants into these harnesses and see if there's a net benefit. For all I know, it's not inconceivable that there be a `rm -rf` catastrophe every other hour.
I dont actually think there many of those people out there. And those that are, are on their way out. There are basically none of those people entering the work force. There are tons of people with that sort of computer literacy but they aren't working on computers.
* Bookkeeper & planning approval within city government
* Doctor/dentist/optometry receptionist & scheduler (both at independent offices and at major hospitals)
* Front desk staff at almost every company with a physical front desk
* University administrative staff (there can be a lot more of these people than you'd think)
* DMV workers
* Probably lots of teachers
Those jobs all will use other software as well, but a lot of their job is making and filling forms on a computer, where they are likely needing to use MS Word fairly often to write things up.
The failure modes are just too rough for most people to think about until it's too late.
I know the counterargument is people are already putting in company data via ChatGPT. However, that is a conscious decision. This may happen without people even recognizing that they are “spilling the beans”.
> Claude Cowork exfiltrates files https://news.ycombinator.com/item?id=46622328
Even if critics are right that these models are inherently insecure, the market will likely settle for 'optically patched.' If the efficiency gains are there, companies will just accept the residual risk.
She has to go through about 100 resumes for a position at her college. Each resume is essentially a form the candidate filled out and lists their detailed academic scores from high school > PhD, their work experience, research and publications.
Based on the declared data, candidates are scored by the system
Now this is India and there's a decent amount of fraud, so an individual has to manually check the claimed experience/scores/publications against reality
A candidate might claim to have relevant experience, but the college might be unaccredited, or the claimed salary might be way too low for a relevant academic position. Or they might claim to have published in XYZ journal, but the journal itself might be a fraudulent pay-to-publish thing
Going through 100+ resumes, each 4 pages long is a nightmare of a task. And boring too.
--
So I asked Claude Code to figure out the problem. I gave it a PDF with the scoring guidelines, a sample resume, and asked it to figure out the problem
Without me telling it, it figured out a plan that involved checking a college's accredition and rating (the govt maintains a rating for all colleges), the claimed salary vs actual median salary for that position (too low is a red flag), and whether the claimed publication is in either the SCOPUS index or a govt approved publications index
(I emphasize govt approved because this is in a govt backed institution)
Then I gave it access to a folder with all the 100 resumes.
In less than 30 minutes, it evaluated all candidates and added the evaluation to a CSV file. I asked it to make it more readable, so it made a HTML page with data from all the candidates and red/green/yellow flags about their work-experience, publications, and employment
It made a prioritized list of the most promising candidates based on this data
My wife double checked because she still "doesn't trust AI", but all her verification almost 100% matched Claude's conclusions
This was a 3 day, grinding task done in 30 minutes. And all I did was type into a terminal for 20 minutes
Well, and learning how to do that in 20 minutes
Dismissing the opportunity to learn because the person offering you knowledge is enthusiastic about his area of expertise is probably shortsighted.
I’m not intending to be dismissive, just noticing a pattern and advocating a bit of skepticism.
Hearing a programming legend weigh in on the latest programming tool seems entirely completely reasonable.
This would have taken ages to do by hand in iMovie, and probably just as long to look up the needed parameters in ffmpeg, but Claude code got it right in the first try, and worked with me to fine-tune the motion detection threshold.
I’m not sure what the plan for integrating extensions is here but they definitely will be wanted.