I tried it out on a workflow I've been manually piecing together and it gave me a bunch of "Error encountered, contact support" messages when doing things like clicking on a form input field, or even a button.

The more complex "Instruction" block worked correctly instead (literally things like "click the "Sign In" button), but then I ran out of the 5 minutes of free run time when trying to go through the full flow. I expect this kind of thing will be fixed soon, as it grows.

In terms of ultimate utility, what I really want is something which can export scripts that run entirely locally, but falling back to the more dynamic AI enhanced version when an error is encountered. I would want AutoTab to generate the workflow which I could then run on my own hardware in bulk.

Anyway, great work! This is definitely the best implementation I've seen of that glimpsed future of capable AI web browsing agents.

curious what you mean by generating the workflow that you run on your own hardware? Is this different than running Autotab locally?

My other request is probably not in line with your business model. I get the sense that Autotab is always communicating with some server on your end, probably for the various bits of AI functionality. What I was asking for is the ability to export the actions/workflow as, say, a python script (like a Selenium script, or even better, a script which drives your browser) which performs the actions in the Autotab workflow.

I need AI understanding when creating the workflow, or healing in case of an error, but I don't always need it when just executing a prepared script. In those (non AI needed) cases, I don't really want to use up my runtime minutes just because I'm executing a previously generated workflow.

Haven’t done a lot with Scribe-like documentation cases. Given the pace at which this technology is developing we’re focused on making Autotab really good at the most economically valuable tasks.

Which layer is the automation happening? Inside using Dev tools? Multiple?

What is the self-healing mechanic? I'm guessing invoking an LLM to find what happened and fix it?

I guess what I'm wondering is. Is this some sort of hybrid between computer use and Dev tools usage?

For instance, if Autotab is trying to click the "submit" button on a sparse page that looks like previous versions of that page, that click might take a few hundred milliseconds. But if the page is very noisy, and Autotab has to scroll, and the button says "next" on it because the flow has an additional step added to it, Autotab will probably escalate to a bigger model to help it find the right answer with enough certainty to proceed.

There is a certain cutoff in that hierarchy of compute that we decided to call "self-healing" because latency is high enough that we wanted to let users know it might take a bit longer for Autotab to proceed to the next step.

For a case with lots of requests how does Autotab handle ip-blocking? Does each run use a different portal instance?

Who is your vendor for residential proxies? That’s quite a sketchy industry.

Autotab has a structured type system underlying the workflows, so any data processed in the course of an automation can be referenced in later steps. It's a bit like a fuzzy programming language for automation, and the model generates schemas to ensure data flows reliably through the series of steps.

For example, users often start by collecting information in one system (using an extract step as you mentioned), then cross reference it in another and then submit some data by having Autotab type it into a third system. In Autotab, you can just type @ to reference a variable, each step has access to data from previous steps.

At the end, you can get a dump of all of Autotab's data from a run as a JSON file, or turn specific arrays of data into CSV files using a table step.

Can I point it at my own LLM or am I locked into using OpenAI?

Right now we do not let you BYO llm, but it's something we would love to provide an option for where possible!

A lot of AI tools promise the world and don't deliver. We explicitly don't want anyone to pay us until they're sure Autotab can do their task, even though the model costs during editing are actually much higher than during runtime.

After you've done that, the API is great for cases where you want to incorporate Autotab into a larger data flow or product.

For instance, say Company A has taught Autotab to migrate their customers' data - so their customers just see a sync button in the Company A product, which kicks off a Autotab run via API. Same for restaurant booking, if you'd want that to happen programatically.

Docs are here with sample code: https://docs.autotab.com/api-reference

Here is more info on auth and security: https://docs.autotab.com/manual/security

For 2FA, different users take different approaches. Everything from teaching Autotab to pull auth codes from their email, to setting intervention requests at the top of their skills, to enterprise integrations that we support with SSO and dedicated machine accounts.

If the modal pops up frequently you can also record an click to dismiss it and make that click optional so Autotab knows to move on if the modal does not pop up sometimes.

How does this not violate TOS? Do you have legal protection set up from megacorps trying to bully you with legal threats?

Automation despite TOS via Adversarial Interop should be a Digital Human Right. Godspeed.

As more and more AI Agent enabled tooling comes out, this will become a bigger issue (the fact that people are automating these services against the TOS) so it's good if everyone who can get legal help has and shares the tactics to fight back against any civil TOS-based legal threats so we are all protected.