Bright Data ranks #1 on Foil's leaderboard [1], but is still detected. ScrapFly is #4 and ZenRows #7. And I guess Capsolver isn't really a scraping thing but is more just for the captcha component.
I think it'd be good if there were more products that did a better job of making an actually undetectable agent, but doesn't seem like any exist yet.
It seems like some of the main reasons people care so far are:
- Preventing automated credential stuffing
- Preventing bots from creating a bunch of fake accounts (eg free trial abuse, which can also lead to high twilio SMS bills!)
- Reducing payment fraud
- Blocking LLM scraping
- Blocking automated scalpers (!) eg for tickers or sneakers
I'm curious to see which use cases end up dominating as the reason companies care about this. And I'm hopeful that my agents will still have good ways for me to browse and do things on the web on my behalf - eg detect agents and route them to an agent path, rather than blocking them.
(I'm interested in tools for detecting AI agents and seeing how this shifts as bot traffic goes way up.)
I think of computer use as like last mile delivery. APIs and bash and such are the efficient logistics networks. Both have different benefits. Obviously, use the efficient methods when you can.
The history of both knowledge work and software engineering seems to be increasing in both volume and complexity, feels reasonable to me to bet on both of those trendlines increasing?
> 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.
What would make it not be a monolith? To me it seems like there'll be a big advantage (e.g. in distribution, user understanding) for most people to be using the same product / similar interface. And then the agent and the developer of that interface figure out all the integrations under that, invisible to the user.
> For all the benefits that agents offer, they can be asymmetrically harmful. This is not a solved issue.
Strongly agreed.
I saw a few people running these things with looser permissions than I do. e.g. one non-technical friend using claude cli, no sandbox, so I set them up with a sandbox etc.
And the people who were using Cowork already were mostly blind approving all requests without reading what it was asking.
The more powerful, the more dangerous, and vice versa.
> There are businesses that want bespoke AI tools and don't have the discipline to deploy them in-house. I don't know if it is ever possible for OAI & friends to develop a "hyper" agent that can produce good outcomes here automatically. There are often people problems that make connecting the data sources tricky. Having a human consultant come in and make a case for why they need access to everything is probably more persuasive and likely to succeed.
Sort of agreed, though I wonder if ai-deployed software eats most use cases, and human consultants for integration/deployment are more for the more niche or hard to reach ones.
> Non-technical users expect a CEO's secretary from TV/movies: you do a vague request, the secretary does everything for you. LLMs cannot give you that by their own nature.
What are you using today? In my experience LLMs are already pretty good at this.
> Please for the love of god actually go outside and talk to people outside of the tech bubble.
In the past week I've taught a few non-technical friends, who are well outside the tech bubble, don't live in the SF Bay Area, etc, how to use Cowork. I did this for fun and for curiosity. One takeaway is that people at startups working on these products would benefit from spending more time sitting with and onboarding users - they're very powerful and helpful once people get up and running, but people struggle to get up and running.
> People don't want "personalized interfaces that change every second based on the whims of an unknowable black box". They have plenty of that already.
I obviously agree with this, I think where our view differs is I expect that models will be able to get good at making custom interfaces, and then help the user personalize it to their tasks. I agree that users don't want something that changes all the time. But they do want something that fits them and fits their task. Artifacts on Claude and Canvas on ChatGPT are early versions of this.
Yes, and the same thing will happen in non-coding knowledge work too. Making knowledge work cheaper will cause complexity to increase, more knowledge work.
My current expectation is that the Cowork/Codex set of "professional agents" for non-technical users will be one of the most important and fastest growing product categories of all time, so far.
i.e. agents for knowledge workers who are not software engineers
A few thoughts and questions:
1. I expect that this set of products will be extremely disruptive to many software businesses. It's like when a new VP joins a company, they often rip and replace some of the software vendors with their personal favorites. Well, most software was designed for human users. Now, peoples' agents will use software for them. Agents have different needs for software than humans do. Some they'll need more of, much they'll no longer need at all. What will this result in? It feels like a much swifter and more significant version of Google taking excerpts/summaries from webpages and putting it at the top of search results and taking away visits and ad revenue from sites.
2. I've tried dozens of products in this space. For most, onboarding is confusing, then the user gets dropped into a blank space, usage limits are uncompetitive compared to the subsidized tokens offered by OpenAI/Anthropic, etc. It's a tough space to compete in, but also clearly going to be a massive market. I'm expecting big investment from Microsoft, Google etc in this segment.
3. How will startups in this space compete against labs who can train models to fit their products?
4. Eventually will the UI/interface be generated/personalized for the user, by the model? Presumably. Harnesses get eaten by model-generated harnesses?
Products I've tried: ai browsers like dia, comet, claude for chrome, atlas, and dex; claw products like openclaw, kimi claw, klaus, viktor, duet, atris; automation things like tasklet and lindy; code agents like devin, claude code, cursor, codex; desktop automation tools like vercept, nox, liminary, logical, and raycast; and email products like shortwave, cora and jace. And of course, Claude Cowork, Codex cli and app, and Claude Code cli and app.
Edit: Notes on trying the new Codex update
1. The permissions workflow is very slick
2. Background browser testing is nice and the shadow cursor is an interesting UI element. It did do some things in the foreground for me / take control of focus, a few times, though.
3. It would be nice if the apps had quick ways to demo their new features. My workflow was to ask an LLM to read the update page and ask it what new things I could test, and then to take those things and ask Codex to demo them to me, but it doesn't quite understand it's own new features well enough to invoke them (without quite a bit of steering)
4. I cannot get it to show me the in app browser
5. Generating image mockups of websites and then building them is nice
I think this is smart and very interesting. I see it like an aggregator marketplace. A powerful position to be in.
Cloudflare, GitHub (if they shipped more), Anthropic and OpenAI are also in decent positions to do this.
I wrote notes on this previously [1]. If you believe agents are going to be big consumers, it's helpful to make things that today allow users of agents to easily discover and purchase services via apis.
https://x.com/chrisbarber