Design Navigator

Hacker News

Design Navigator

Hello HN! Just shipped my first digital product, Design Navigator: https://navigator.designdisciplin.com/ I've been designing, studying design, and teaching design for many years. One of the biggest challenges I faced was how my profession is divided into different "worlds". Designers employed at companies, freelancers, academics, creators... All seem to live in different worlds. I developed Design Navigator to help designers choose their world and excel in it. It starts with a simple questionnaire and recommends to you one of four worlds, along with a set of resources to dive deep: employment, freelancing, founder, and creator. Of course, the best way to use it is to check out all four of the "worlds", get into some of the resources, and then make up your mind. Built using Next.js, TailwindCSS, Vercel, etc. – nothing fancy from a tech standpoint. But I'm particularly proud of the front end design, wanted to show off some of my skills, and it was received well. Over the years I've learned a lot from HN, and incorporated many YC resources into Design Navigator, especially for the Founder path. While it's mainly intended for designers (and particularly UI, UX, web designers, etc.), I'm sure many of us in tech can find some inspiration in it. I hope you enjoy it!

Visit product View on Hacker NewsFeb 3, 2023

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Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

89%89% 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.

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

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

47%47% 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

12%12% 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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