How to: How it works
Skyvern was inspired by the Task-Driven autonomous agent design popularized by [BabyAGI](https://github.com/yoheinakajima/babyagi) and [AutoGPT](https://github.com/Significant-Gravitas/AutoGPT) -- with one major bonus: we give Skyvern the ability to interact with websites using browser automation libraries like [Playwright](https://playwright.dev/).

Skyvern uses a swarm of agents to comprehend a website, and plan and execute its actions:
This approach has a few advantages:

1. Skyvern can operate on websites it's never seen before, as it's able to map visual elements to actions necessary to complete a workflow, without any customized code
1. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate
1. Skyvern is able to take a single workflow and apply it to a large number of websites, as it's able to reason through the interactions necessary to complete the workflow
1. Skyvern leverages LLMs to reason through interactions to ensure we can cover complex situations. Examples include:
    1. If you wanted to get an auto insurance quote from Geico, the answer to a common question "Were you eligible to drive at 18?" could be inferred from the driver receiving their license at age 16
    1. If you were doing competitor analysis, it's understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!)

A detailed technical report can be found [here](https://www.skyvern.com/blog/skyvern-2-0-state-of-the-art-web-navigation-with-85-8-on-webvoyager-eval/).