An open-source platform like Dribble for developers and designers

Hacker News

Hi everyone, I'm super excited to announce Portfoliwoah, an open-source platform designed to facilitate the sharing and discovery of personal work by designers and developers across various companies. The goal is simple: make it easier for designers and developers in industry to find, appreciate, and be inspired by others. The idea came about when I was making my portfolio to showcase the work I had been doing. I wanted to showcase my passion for design through my portfolio but was having a difficult time figuring out how I wanted it to look. I'm a big fan of the design philosophy of Vercel, so I figured that checking out the portfolios of their design team would be perfect to help get my creative juices flowing. Fortunately, a quick Google search led me to a page on Vercel's website dedicated to the design team. However, when I tried to find a similar page for companies like Notion, Linear, and Airbnb the results were less than favorable. I figure having a unified platform for anyone to post their portfolios, projects, and more from across the industry would be beneficial to a lot of people. Not only can people take inspiration for their projects, but they can also see what it takes to work at different companies. Here's a link to a YouTube demo: https://youtu.be/JLJTnYzyRrg At the end of the day, Portfoliwoah is a simple idea that tries to solve a simple problem. I would love to hear what y'all think, and if you have an idea or suggestion, open an issue or PR! https://www.portfoliwoah.io/ https://github.com/Oustro/portfoliwoah Thanks for reading! P.S. The ranking algo for Portfolio was actually inspired by the HN one. I obviously had to make some changes for our use case.

Visit product View on Hacker NewsJan 9, 2024

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

90%90% 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: google, open · Missing: mac, agents, macos

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

Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist

67%67% 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 · Strong signals: ios, personal, google · Missing: mobile apps, entrepreneurs, apps

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

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

33%33% 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

11%11% 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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