Introducing Adept Experiments – use AI workflows to delegate repetitive tasks (opens in new tab)

For anyone looking to try this in an E2E testing context, we just released a library for Playwright called ZeroStep (https://zerostep.com/) that lets you script AI based actions, assertions, and extractions.

This is a working example that tests the core "book a meeting" workflow in Calendly:

    import { test, expect } from '@playwright/test'
    import { ai } from '@zerostep/playwright'

    test.describe('Calendly', () => {
      test('book the next available timeslot', async ({ page }) => {
        await page.goto('https://calendly.com/zerostep-test/test-calendly')

        await ai('Verify that a calendar is displayed', { page, test })
        await ai('Dismiss the privacy modal', { page, test })
        await ai('Click on the first available day of the month', { page, test })
        await ai('Click on the first available time in the sidebar', { page, test })
        await ai('Click the Next button', { page, test })
        await ai('Fill out the form with realistic values', { page, test })
        await ai('Submit the form', { page, test })

        const element = await page.getByText('You are scheduled')
        expect(element).toBeDefined()
      })
    })

this seems useful based on the fact that software pieces do not work with each other. so the human has to manually move data from one to the other. in most of the cases if users always have to do A->B, does it make more sense to build automation in code instead of using ai? the automation can be built by engineers who are also assisted by ai.

Been excited for this type of neural network since they announced it months and months ago. Imagine this type of agent in conjunction with a framework like autogen