Logfolio – A Tool to Track Developer Work Logs and Prepare for Reviews

Hacker News

Hi HN, After realizing how much I struggled with keeping a consistent record of my daily work, I decided to build Logfolio – a tool to help developers effectively track their work and leverage it for career growth. Logfolio helps developers: - Record daily work logs of accomplishments and key work items. - Summarize their progress using AI, making it easier to review achievements during performance reviews. - Craft tailored cover letters and prepare for interviews based on work logs. The idea was inspired by Gergely Orosz's "The Software Engineer's Guidebook" and his insights on the importance of keeping work logs. I just launched it on Product Hunt and would love feedback from the community: - Does this solve a pain point for you? - Are there features you'd want to see added? You can check it out here: https://logfolio.com Thanks in advance for your feedback and thoughts!

Visit product View on Hacker NewsOct 18, 2024

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

84%84% 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.

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

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

30%30% 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

28%28% 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 · Strong signals: reviews · Missing: plus, platform, intuitive

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

18%18% 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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