Since LLMs were introduced, I've been of the belief that this technology actually makes writing a *more* important skill to develop than less. So far that belief has held. No matter how advanced the model gets, you'll get better results if you can clarify your thoughts well in written language.

There may be a future AI-based system that can retain so much context it can kind of just "get what you mean" when you say off-the-cuff things, but I believe that a user that can think, speak, and write clearly will still have a skill advantage over one that does not.

This is why I think (at least given the current state of AI code generators) that senior engineers will benefit more from AI than less experienced engineers. I don't know exactly what the chart of experience (on the x-axis) and amount of productivity gain from AI (on the y-axis) will look like, but I'm pretty sure it will be roughly (given suitable error bars around the input) a monotonically increasing function.

I agree 100% - it's a very programmer-coded prompt. It was pretty much the first thing I thought to try.

I expect we'll see an enormous quantity of "cool prompts to try in Cowork" content show up over the next few months, which makes sense - regular non-programmers will benefit enormously from cookbooks and prompting guides and other tools to help them figure out what they can ask this thing.

> But I’m skeptical that the target user is thinking clearly enough to prompt this well.

Over time, target users will learn to think and communicate this way. As this is what tools will demand of them.

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.

But that's how literally all software adoption curves work...

The 1980's version of simonw was explaining to people how to use Excel, too.

(though 40 years later, things are still pretty bad on the Excel front, hah)

Select star from blog posts where... :)

Applying for a job is an action that can change the entire course of your life. A job is something somebody spends ~30% of their time at, and every individual job contributes to a career trajectory and determines the opportunities one will have available throughout their life. Not only from the candidate's perspective, making the correct hires is something that will determine the course of a company's future; I would argue that there is literally nothing more important in running a business than hiring the right people. You would think, given these considerations, maybe the person who is paid money to review these applications should actually review them with the thoroughness that is warranted by such a task. Did the university approve of the work being outsourced to a chatbot instead of the person they were paying the salary to do the work?

To say nothing of the flagrantly immoral and likely illegal data privacy violations, of course.

I'm very skeptical of using AI in this way. I've given Claude access to calendars and travel plans and asked it to do similar analytical tasks cross referencing documents that would take days for me to do manually. Since it was about my own plans and life that I knew well, it was possible for me to spot subtle errors that seemed correct at the surface level but actually weren't the conclusions I would make. I've attempted these types of tasks 10-20 times with similar experiences each time. In the end, it's made me very skeptical, like your wife. I don't trust any AI output without a thorough review. Hallucinations are still a frequent problem.

This is good work. When a task is of critical importance, I give two different LLMs the same task. And then ask them to review each other's output and validate all claims. I do this with Codex and Claude Code. It is very rare for them to find some valid fault in the other LLM's solution. And they are generally good about admitting mistakes and then creating a single unified solution that addresses identified issues. This result is better and ready for human review.

> My wife double checked because she still "doesn't trust AI", but all her verification almost 100% matched Claude's conclusions

She's right not to trust it for something like this. The "almost 100%" is the problem (also consider that you're sending personal data to anthropic without permission) especially for something like this where it might mean discarding someone's resume, which is something that could have a significant impact on a person's life.

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

Doesn’t submitting the resumes to Anthropic violate India’s data protection laws?

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.

> And all I did was type into a terminal for 20 minutes

Well, and learning how to do that in 20 minutes

The latest models work just as good with PowerShell as they do with bash, well at least that’s true for codex.

I've gotten much more excited about our future AI overlords since it has led to all kinds of people at work asking me how to use tmux!

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.

Claude (generally, even non Cowork mode) is vulnerable to exfil via their APIs, and Anthropic's response was that you should click the stop button if exfiltration occurs.

This is a good example of the Normalization of Deviance in AI by the way.

See my Claude Pirate research from last October for details:

https://embracethered.com/blog/posts/2025/claude-abusing-net...

This hit the front page yesterday so you may have seen it, but figured I'd post for posterity sake

> Claude Cowork exfiltrates files https://news.ycombinator.com/item?id=46622328

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.

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.

Have you seen my writing on prompt injection (a term that I coined)?

That's pretty negative! https://simonwillison.net/series/prompt-injection/

There's a whole section in the linked piece about how Cowork doesn't do enough here, including:

> I do not think it is fair to tell regular non-programmer users to watch out for “suspicious actions that may indicate prompt injection”

I would argue the EXACT opposite. His analysis is very constructive.

The people you should be skeptical of are the random Xitter handles who post about a robotic phlebotomists and say "THE FUTUE IS ALREADY HERE".

You're right to be skeptical. He makes a living as a hype merchant.

id imagine someone like Simon to pick his AI products carefully enough that he doesn't waste his time on duds.

From the release page, this seems like a pretty big deal in terms of office jobs at some point in the future: "Spreadsheets with formulas: Generate Excel files with working VLOOKUP, conditional formatting, and multiple tabs"

There are so many office workers who just shuffle data between systems. Not sure about the error rate though but it is not like the error rate is going to be worse a decade from now.

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.

I've been using Google's Antigravity (which has a similar UI) to do data analysis and making reports. Skills are really useful for that.

I don't use a Mac so can't run Cowork, but the normal Claude CLI is pretty good at general automation tasks (as is Codex-CLI and Gemini CLI.)

Most recent example: I wanted to try out GLM-image when it dropped the other day, but didn't feel like spending an hour dealing with multifile, multidirectory HuggingFace downloads and all the usual Python dependency headaches. So I made an empty directory, ran Claude Code, and told it "Please download all files from https://huggingface.co/zai-org/GLM-Image/tree/main into this directory and test the model." An hour later, I tabbed back to the console window and there was the sample image file.

Looking at the transcript, sure enough, it ran into all the usual headaches and hassles... but the difference is I didn't have to deal with them.

Note that I didn't tell it "Use uv to test the model" -- I just YOLOed it with my system Python installation. If I later find that it broke something else, oh, well... that sounds like a job for Claude, too.

Another thing that's nice about these CLI tools is that they hide the differences between terminals pretty effectively. I ran this particular task in a Windows DOS box, but could just as easily have used PowerShell, a Mac, or a Linux terminal. The idea of not having to care what OS I'm running is an alluring one, given the steady enshittification of Windows.