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Discover AI tools based on your real workflow

Hacker News

Discover AI tools based on your real workflow

Hi HN! I built WorkMirror as a side-project because I was tired of generic “Top 10 AI Tools” lists that ignore how I actually work. WorkMirror is a browser extension that watches your real workflow for a few hours and recommends AI tools based on what you actually do. Ex: “You spent 2h 10m coding in Replit and switching files 74 times. Windsurf could cut context switching and save ~35 min/day.” It’s privacy-first: no accounts & it's free. The real challenge has been modeling workflow patterns reliably from noisy browser data. I’m using event timing + URL classification + interaction frequency to infer “work states” (coding, research, writing, idle) and feed those into a simple scoring model that ranks AI tools by expected time savings. Still iterating on the feature weighting and recommendation logic. I'd love any feedback!

Visit product View on Hacker NewsOct 22, 2025

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2points

Did not reach leaderboard

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best fitHighest predicted score across all platforms for this description.

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

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

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

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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

26%26% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

16%16% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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