My Book: Build a SaaS App in Go

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Hi, I've reached the pre-order phase for my book on building a back-end JSON API in Go for a SaaS or web application. I've build two SaaS using Go in the last 4 years, LeadFuze and Roadmap. This book contains what I've learned building those. It's way harder than what I thought to write a book. After receiving lots of requests to have early access I decided to enable pre-order and publish chapter as they are ready. I thought it might interests some of you here maybe if you were looking at using Go to build your next product. This is the book URL: https://buildsaasappingo.com/ As always all feedback are highly appreciated. Thanks

Visit product View on Hacker NewsApr 24, 2018

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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

61%61% 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

56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

35%35% 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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

25%25% 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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