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I built LeetEngineer – Interview prep for non-IT engineers

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I built LeetEngineer – Interview prep for non-IT engineers

Hi HN, I built LeetEngineer because while software engineers have platforms like LeetCode or HackerRank to prepare for interviews, non-IT engineers (mechanical, civil, aerospace, manufacturing, etc.) have almost nothing. From my own experience applying for 500+ jobs, I realized interviews for engineers often focus on scenario-based questions that test how you apply engineering skills to real-world problems. I wanted a tool that helps with exactly that. With LeetEngineer, you just paste a job description and the platform generates tailored, scenario-based practice questions so you can walk into your interview prepared and confident. This is the first MVP and I’d love feedback from this community. https://leetengineerai.com What do you think about the idea, and what features would you find most useful? Thanks!

Visit productView on Hacker NewsSep 25, 2025
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
46%46% predicted probability of success on AppSumo, 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
45%45% 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
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: code · Missing: mac, agents, macos
36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% 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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