Show HN: Build and run automations in the browser with natural language
youtube.comIt's Artem, Co-Founder of Bardeen here. We launched Magic Box today and I wanted to share it with you.
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...
This is awesome, curious what is your DSL look like and what is the accuracy of LLM translating into your DSL?
It's similar to javascript, but not exactly identical. Here is an example that sends a summary of calendar event two minutes before it starts (uses gmail, openai and slack):
``` 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.
nice, pretty impressive to go from 10% to 70%. Do you also do autogpt style looping with reasking and verification until proper DSL is creating?
Not yet because honestly we were able to get to where we needed in terms of accuracy without it. Creating a feedback loop and turning into an agent-style interaction can be helpful for more complex automations, but honestly, you can get a lot of mileage out of what we have. Having said that, agents look really fascinating and some demos I saw are mind blowing, so we will definitely look into it very closely.
Wow, the future is here! Curious to see how it works under the hood :)
Come work at Bardeen! email me artem@ if you're interested
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.
Super amazing UX. Build automations in seconds :)