Here is a walkthrough of how it works: https://youtu.be/63co74JHy1k, and you can try it for free at https://autotab.com by downloading the app.
Why a dedicated editor?
The number one blocker we've found in building more flexible, agentic automations is performance quality BY FAR (https://www.langchain.com/stateofaiagents#barriers-and-chall...). For all the talk of cost, latency, and safety, the fact is most people are still just struggling to get agents to work. The keys to solving reliability are better models, yes, but also intent specification. Even humans don't zero-shot these tasks from a prompt. They need to be shown how to perform them, and then refined with question-asking + feedback over time. It is also quite difficult to formulate complete requirements on the spot from memory.
The editor makes it easy to build the specification up as you step through your workflow, while generating successful task trajectories for the model. This is the only way we've been able to get the reliability we need for production use cases.
But why build a browser?
Autotab started as a Chrome extension (with a Show HN post! https://news.ycombinator.com/item?id=37943931). As we iterated with users, we realized that we needed to focus on creating the control surface for intent specification, and that being stuck in a chrome sidepanel wasn't going to work. We also knew that we needed a level of control for the model that we couldn't get without owning the browser. In Autotab, the browser becomes a canvas on which the user and the model are taking turns showing and explaining the task.
Key features:
1. Self-healing automations that don't break when sites change
2. Dedicated authoring tool that builds memory for the model while defining steps for the automation
3. Control flows and deep configurability to keep automations on track, even when navigating complex reasoning tasks
4. Works with any website (no site-specific APIs needed)
5. Runs securely in the cloud or locally
6. Simple REST API + client libraries for Python, Node
We'd love to get any early feedback from the HN community, ideas for where you'd like the product to go, or experiences in this space. We will be in the comments for the next few hours to respond!
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.