3 months ago, Anthropic and Simon claimed that Skills were the next big thing and going to completely change the game. So far, from my exploration, I don't see any good examples out there, nor is a there a big growing/active community of users.

Today, we are talking about Cowork. My prediction is that 3 months from now, there will be yet another new Anthropic positioning, followed up with a detailed blog from Simon, followed by HN discussing possibilities. Rinse and Repeat.

This is something I have experienced first hand participating in the Vim/Emacs/Ricing communities. The newbie spends hours installing and tuning workflows with the mental justification of long-term savings, only to throw it all away in a few weeks when they see a new, shinier thing. I have been there and done that. For many, many years.

The mature user configures and installs 1 or 2 shiny new things, possibly spending several hours even. Then he goes back to work. 6 months later, he reviews his workflow and decides what has worked well, what hasn't and looks for the new shiny things in the market. Because, you need to use your tools in anger, in the ups and downs, to truly evaluate them in various real scenarios. Scenarios that won't show up until serious use.

My point is that Anthropic is incentivized in continuously moving goalposts. Simon is incentivized in writing new blogs every other day. But none of that is healthy for you and me.

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.

Cowork seems like a great application of that principle.

[0] https://www.youtube.com/watch?v=AmdLVWMdjOk

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!".

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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 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”.

We'll see.

It is probably a good lesson on how far confidence can get you in life. People are often highly biased by the presentation of the thing.

starting with a bare ubuntu desktop system with plenty of RAM and CPU, setup three ubuntu VMs for secure development and networking skills learning (wireshark, protocol analysis, etc etc):

one ubuntu “virtual” desktop to simulate a working desktop that an end-user or developer would use. its networking should initially be completely isolated.

one ubuntu server to simulate a bastion machine. route all “virtual desktop” traffic through this “bastion”. it will serve as a tap.

one ubuntu server to serve as edge node. this one can share internet access with the host. route all bastion traffic through the edge node.

use this three vm setup to perform ordinary tasks in the “virtual desktop “ and observe the resulting traffic in the “bastion”. verify that no other traffic is generated on or from the host outside of the expected path virtual desktop -> bastion -> edge.

i claim this is a minimal “network clean” development setup for anyone wanting to do security-conscious development.

extra credit: setup another isolated vm sever to act as the package manager ; ie mirror anything to be installed on the “virtual desktop” onto this package server and configure this server as the install point for apt on the “virtual desktop”.

i doubt an AI can set this up right now. (i’ve tried)

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.

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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

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.

The failure modes are just too rough for most people to think about until it's too late.

Over time this has become more sophisticated. I've created custom commands to incorporate training tips from YouTube videos (via YT-DLP and WhisperX) and PDFs of exercise plans or books that I've purchased. I've used or created MCP servers to give it access to data from my smart watch and smart scale. It has a few database-like YAML files for scoring things like exercise weight ranges and historical fitness metrics. At some point we'll probably start publishing the workouts online somewhere where I can view and complete them electronically, although I'm not feeling a big rush on that. I can work on this at my own pace and it's never been anything but fun.

I think there's a whole category of personal apps that are essentially AI + a folder with files in it. They are designed and maintained by you, can be exactly what you want (or at least can prompt), and don't need to be published or shared with anyone else. But to create them you needed to be comfortable at the command line. I actually had a chat with Claude about this, asking if there was a similar workflow for non-CLI types. Claude Cowork seems like it. I'll be curious to see what kinds of things non-technical users get up to with it, at least once it's more widely available.

I’m not sure what the plan for integrating extensions is here but they definitely will be wanted.

But seriously, other tasks I've encountered recently that I wish I could delegate to an AI:

- Posting my junk to Craigslist, determining a fair price, negotiating a buyer (pickup only!)

- Scheduling showings to find an apartment, wherein the listing agents are spread over multiple platforms, proprietary websites, or phone contacts

- Job applications -- not forging a resume, but compiling candidate positions with reasoning, and the tedious part were you have to re-enter your whole resume into their proprietary application pipeline app

What strikes me as basic similarities across these types of things, is that they are essentially data-entry jobs which interact with third-party interfaces, with CRM-like follow up requirements, and require "good judgement" (reading reviews, identifying scams, etc).

More broadly, my observation is that the type of tools that developers use are naturally suited to be scripted. Because developers do that all the time. We work with command line prompts, lots of tools that can be scripted via the command line, and scripting languages that work in that environment.

Tools like Claude Code and Codex are extremely simple for that reason. It's a simple feedback loop that in pseudo code reads like "while criteria not met, figure out what tools to run, run those, add output to context and re-assess if criteria were met". You don't need to hard code anything about the tools. A handful of tools (read file, run command, etc.) is all that is needed. You can get some very sophisticated feedback loops going that effectively counter the traditional limitations of LLMs (hallucinating stuff, poor instruction following, assertively claiming something is done when it isn't, etc.). A simple test suite and the condition that the tests must pass (while disallowing obvious hacks like disabling all the tests) can be enough to make agents grind away at a problem until it is solved.

In a business context, this is not true yet. Most business users use a variety of tools that aren't very scriptable and require fiddling with complex UIs. Worse, a lot of those tools are proprietary and hacking them requires access you typically don't get or is very limited. Given that, a life hack is to translate business workflows into developer tool workflows and then use agentic coding tools. Claude can't use MS Word for you. But it can probably work on MS word files via open source libraries and tools. So, step zero is to "mount a directory" and then use command line tools to manipulate what's inside. You bypass the tool boundary by swapping out business tools with developer tools. Anything behind a SAAS web UI is a bit out of scope unfortunately. You get bogged down in a complex maze of authentication and permission issues, fiddly APIs with poor documentation. That's why most of the connectors for e.g. Chat GPT are a bad joke in how limited they are.

Simple example. Codex/Claude Code, etc. are probably fairly useless doing anything complicated with say Square Space, a wordpress website, etc. But if you use a static site builder, you can make these tools do fairly complicated things. I've been working for the last two weeks on our Hugo website to do some major modernization, restructuring, content generation, translations, etc. All via prompting codex. I'm working on SEO, lighthouse performance, adding complex new components to the website, reusing content from old pages to create new ones, checking consistency between translations, ensuring consistent use of certain language, etc. All by prompting codex. "Add a logo for company X", "make sure page foo has a translation consistent with my translation guide", etc.

I got a lot more productive with this setup after I added a simple npm run verify test suite with a simple AGENTS.md instruction that the verify script has to pass after any change. If you watch what codex does there's a pattern of trial and error until the verification script passes. Usually it doesn't get it right in one go. But it gets there without my intervention. It's not a very sophisticated test suite but it tests a few of the basics (e.g. tailwind styling survives the build and is in the live site, important shit doesn't 404, hugo doesn't error, etc.). I have about 10 simple smoke tests like that.

I think we'll see a big shift in the business world towards more AI friendly tooling because smart business users will be flocking towards tools that work with AI tools in a hurry as they discover that they can shave weeks/days of grinding those tools manually by switching. This is a process that's likely to take very long because people don't like to change their tool habits. But the notion of what is the right tool for the right job is shifting. If it's not AI friendly, it's the wrong tool probably.

Long term, I expect UIs and dealing with permissions in a sane way will be easier to deal with for AI tools. But meanwhile, we don't actually have to wait for all that. You can hack your way to success if you are a bit smart with your tool choices.