I've just recently joined Product Hunt, and looking forward to connecting with the community here. I've been a software engineer for the last 30 years, and have often been the only Black engineer on the team (or the entire company). As the years have gone on, there has certainly been an uptick in Black people getting into tech - far more than when I first started out in the late 90's.

I grew up in South Central Los Angeles, around gangs and drugs; being a software engineer or an entrepreneur wasn't something that I had many examples of. So gravitating towards computers at an early age, becoming an engineer, and working on software was beyond "living the dream" for me.

Following on from what @gabe posted on the forum (I decide what's featured on the leaderboard - AMA w/ Gabe from Product Hunt) you can be more "clear" why you didn't make it to the featured leaderboard.

From the points presented in the discussion, several conclusions and perhaps even advice emerged, which can increase your chances of getting to the featured section.

Personally, I would summarize it as follows.

Hey Product Hunt community!

We all know the classic ways to brainstorm startup ideas scratching your own itch, spotting market gaps, or improving on an existing product. But sometimes, the best ideas come from unexpected places.

Hello guys,

for the context, in Murmell, we run CLI sessions like Claude code and Codex, and damn this mf is consuming too much RAM around 800mb.

I want to build a product that relates to our CO2 emissions and offsets. I envisioned the product closer to Whoop or Oura where the product stopped being about the metric and became about identity and belonging. People wear those rings partly to be part of a community, not just to optimize sleep.

I want to bring that same energy to climate action make it feel aspirational and social, not preachy.

Would love input on:

What actually made Whoop/Oura/Strava work as identity-driven products (not just surface-level vibes)?

I deploy AI workflows into small businesses for a living auto shops, accounting firms, home services. Boring stuff, not products. After enough of them the pattern got obvious, and I think it applies to anyone shipping AI, including the people building tools here.

There are two versions of "we use AI" and from the outside they look identical.

A few months ago, I had an idea that looked pretty convincing on paper.

The problem sounded real.
The market existed.
There were already competitors.
And I could clearly imagine how the product would work.

The dangerous part?

I had done almost everything except proving that the problem was painful enough for someone to change their current behavior.

15 years in client software delivery, with WordPress running through a good chunk of it, not a WordPress specialist by title, a COO who's shipped it alongside everything else at Genetech. A few things that keep proving true no matter how the platform evolves:
1. Updates are the whole game, not a chore. We recently cleaned up a client site that had been hacked twice. It had been deployed in Jan 2026 and had fallen several updates behind. After the cleanup, we didn t change the code, we patched and updated everything that needed updating. No repeat incident since.

2. The admin path being public isn't a bug. It's a decision you have to make yourself. Every WordPress install defaults to the same URL. Nobody's coming to lock that door for you.

3. Deactivating a plugin isn't the same as removing it. An inactive plugin is still a way in. If you're not using it, delete it.

4. Heavier page builders cost you speed you can't see until you measure it. Free-tier drag-and-drop builders load slower than lighter, block-based setups. The tradeoff stays invisible until someone actually checks.

Is it normal to get contacted by someone selling upvotes @ $2/vote?
From the actual email:
"$2/upvote. Growth: $499 250 upvotes, 50 comments, 25 reviews, 10 followers (20% off). "
Needless to say, I will never do this but will happily name & shame the sender.

As of August 2, 2026, the EU AI Act's high risk provisions are enforceable, meaning agentic AI systems now legally require human oversight and conformity assessments. Fines for non compliance can hit 15 million euros or 3% of global revenue.

What's interesting is that "human oversight" isn't clearly defined in most implementations I've seen. Does it mean a human reviews every action before it happens? Only high risk actions? A log someone can audit after the fact?

I've seen a few teams building agent products wrestle with this exact call for every action type, not as a compliance checkbox, but because it genuinely changes how much you can trust the thing day to day.