It takes automation descriptions in English and turns them into in-browser playbooks that can either be launched via shortcut or triggered by an external event (such as an email arriving).
I think it's pretty cool and it's ready for anyone to try it out (no waitlist!). We currently have about 30 productivity apps integrated. Please give it a shot and let us know what you think.
Here is a Twitter thread if you're not in the mood for Youtube https://twitter.com/bardeenai/status/1648355825537421314
Here is Bardeen installation link https://chrome.google.com/webstore/detail/bardeen-automate-m...
``` function (recipient) {\n when: __0 = GoogleCalendar.when_next_event_is_in(time: B.Duration(120000));\n __1 = GoogleCalendar.get_next_event();\n __2 = OpenAI.get_summary_of(text: __1.description);\n __3 = BardeenCommons.get_string_concatenating_strings(strings: ["Your next event is:", __1.summary, "at", __1.startTime, "Here is a summary of the event:", __2]);\n Slack.send_message(message: __3, recipient: recipient);\n}' ```
Initial accuracy was about 10%, which was pretty meh TBH. With a lot of tweaking and tuning we were able to get it to 70%. This means that it takes about 2-3 attempts to get it to generate what's expected.
The great thing is that we only use AI to generate the DSL description of the automation and let the user tweak and tune it. Once it's there we just execute it with our engine.
On a more serious note, we have built a DSL and an engine for executing automations inside the browser. Where possible we connect natively to the apps we're integrating with (like Calendar or Notion), where it's not possible (like LinkedIn) we use browser capabilities to interact or get data. We use a GPT model to transform the description of automation to our DSL, we then verify it, typecheck it, fill in the gaps where possible and present it to the user. If the user likes it they can save it and start using it. Happy to share more details if it's interesting.