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Fizzbuzz.md – Turn a Markdown file into a coding challenge

Hacker News

Fizzbuzz.md – Turn a Markdown file into a coding challenge

I work at a small startup trying to hire engineers and got tired of looking through resumes. As Joel Spolsky points out, they're not great indications of technical ability. Instead, I decided to throw together a take-home challenge that applicants could access via an API. "If they can't solve the challenge, I don't need to see their resume," I told myself. FizzBuzz.md is a better version of the solution I built for work. It lets applicants send questions and submissions to configurable email addresses via API so the email addresses aren't exposed directly. (Less spam, FTW) Hope you find it useful. I plan to use it going forward.

Visit productView on Hacker NewsApr 26, 2025
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, coding · Missing: mac, agents, macos
79%79% 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
71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
28%28% predicted probability of success on TrustMRR, 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.

Incorrect prediction on native model

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