General Forums on Product Hunt

Lauching for 5th time - Still loving it, but we need to talk...

Matous Kralik · 2026-02-17T02:04:14.619-08:00

So, @Boost.space is launching today. Every time we decide to go through this whole "Product Hunt thingy," it feels like a full-circle moment.But we keep doing it. Whenever we have a major release—like this v5—we end up back here. It honestly feels like Product Hunt is simply the place to be.I have to be honest: I love how Product Hunt reacted to the "falling trends" and "hijacked launches" by actually changing the mechanics. Our previous launches were insane. We’ve had races with 1,250 upvotes against "weird tools" that someone vibecoded overnight.What I love about Product Hunt now is that it reveals how strong your community actually is. We have nearly 5,000 members across Facebook and Slack—a massive group of active users and dedicated moderators. Under the new system, every single one of those votes counts more than ever.But beyond the users, you have to activate your partners; they are a massive part of the Product Hunt mix. It really makes you stop and ask: "Are we leaning on our community pillars enough?"In a world obsessed with "growth hacking," "AI shortcuts," and "weird outreach," it feels like we’re forgetting the bedrock of every business: Relationships. With everyone. Partners, users, and followers on LinkedIn and X.Of course, you can buy "packages" from the influencers who slide into your DMs the very first minute of your launch, promising a #1 spot because of their follower count. But is that what you actually want? Is that the spirit of Product Hunt?No. It’s simpler than that:Good productActive communityStable partnershipsDon’t be a d*ckYes, that last one matters most. 😁Post your launch or product here, lets talk about it, lets be humans and support each other. No weird "AI this" and "AI that". At least for a little bit 🤞

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To makers who have launched in the past, what would you do differently next time?

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Looking to understand the differences between AWS's machine learning offerings? I've written a comprehensive comparison between AWS SageMaker and Amazon ML. This article explores: SageMaker's end-to-end ML capabilities vs. Amazon ML's historical approach Detailed analysis of SageMaker's features including Studio, Autopilot, and Ground Truth Implementation best practices and cost optimization strategies Practical recommendations for teams starting with machine learning on AWS Whether you're a data scientist, developer, or decision-maker, this comparison will help you understand AWS's machine learning evolution and make informed decisions about using SageMaker for your ML projects. Here is the article link - https://medium.com/@smith.emily2... Join the discussion and share your experiences with these platforms!