Building a car online should feel as smooth as driving one.
With @docketqa, we tested the @MercedesBenz customizer by building a GLE 450 SUV end-to-end — all from a single natural language prompt.
Because even luxury flows deserve reliable QA.
We asked @docketqa to generate a video on @pika_labs. Instead of the flow completing, we hit a paywall.
That’s the reality of end-to-end testing: catching the unexpected before your users do.
Runway (@runwayml) turns ideas into visuals — but only if every click, render, and export works flawlessly.
With @docketqa, we told @runwayml to generate a unique image and tested the entire flow end-to-end, using just natural language.
Creative tools deserve creative QA.
@playground_ai makes creating stunning visuals effortless. With @docketqa , we told it to design a sticker and tested the entire flow end-to-end, using just natural language.
No scripts. No setup. Just real user behavior, automated.
Testing Gen AI isn’t just about buttons. We need to test subjective outputs.
With @docketqa , we acted as a synthetic user on @leonardoai , giving only high-level instructions to test its model image generation flow end-to-end.
How do you test a Gen AI platform… with personality?
With @docketqa , we created a @character_ai persona for their CEO - then had a full conversation with him, end-to-end, using just natural language.
Because the best way to test AI is with AI.
The best way to test Gen AI platforms… is with AI.
With @docketqa, we tested @withdelphi's core flows using just natural language - validating not just clicks and inputs, but AI-generated outputs too.
No brittle scripts. No manual setup. Just real user behavior, automated.
Startups like @cluely ship fast, but moving fast shouldn’t mean breaking trust.
We tested @cluely's unauthenticated share link with @docketqa end-to-end, using just natural language.
No scripts. Just real user behavior, automated.
#ai#qa#e2etest#yc#cluely#docket
Background agents in @cursor_ai can quietly power entire workflows. If they fail, you lose automation, context, and speed.
With @docketqa , we tested @cursor_ai's background agent flow end-to-end, using just natural language.
#ai#qa#e2etest#yc#cursor
What if your @LinkedIn posts stopped getting engagement?
Sometimes it’s not the content — it’s the flow.
With @docketqa , we tested it end-to-end:
→ Solve the CAPTCHA at login
→ Follow a company
→ Like their most recent post
#ai#qa#e2etest#yc
@github stars aren't just vanity — they drive discovery, reputation, and adoption.
If these break, developers notice.
With @docketqa, we tested the full @github flow — starring a repo and adding it to a list — using just natural language.
#ai#qa#e2etest#yc#github
@SlackHQ emoji reactions power more critical workflows than you'd think. Approvals, handoffs, standups — all riding on a single click.
We used @docketqa to test the full flow: open a channel, update the description, post an image, react with an emoji — all in plain English.
Broken links break trust - especially when they’re supposed to be your sources.
Here’s @docketqa testing one of @perplexity_ai 's core flows by verifying each of their sources.
No scripts. No maintenance. Just real user behavior, automated.
#ai#qa#e2etest#yc#perplexity