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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()
})
})
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Your example above - 7 function calls in one test. let's say usually closer to 5, we have hundreds of tests. Every single PR runs E2E tests. We open a handful of PRs a day. Let's call it 5. We're already looking at thousands of invocations a day. Based on your pricing, that would be incredibly expensive.
This is with 3 eng.