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Verex – Write E2E tests in plain English, powered by Playwright and AI

Hacker News

Verex – Write E2E tests in plain English, powered by Playwright and AI

I built Verex, a tool that lets you write E2E tests in plain English (e.g. "Login and check dashboard loads"). It uses Playwright under the hood with an AI layer to interpret and run tests, reducing the need to maintain brittle test scripts. No more flaky tests that break every time the UI changes. CI-ready (GitHub Actions, BitBucket Pipelines, Gitlab), with visual bug reports and screenshots. Would love feedback: https://youtu.be/KUHjFeHlSlg

Visit product View on Hacker NewsMar 26, 2025

Actual performance

1points

1comments

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual, plain · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: pipe, io · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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