I'll start.

Supabase. Found it here three years ago. Thought it was just another backend. Now I can't imagine building without it.

Here's what it does for us at Rankfender:

Auth that doesn't make you crazy. We have users across 120+ countries. Supabase handles sign-ups, logins, password resets, magic links, OAuth with Google and GitHub. It just works. We didn't have to build any of it.

I was reading Nika's thread here about free vs paid features. Really made me think.

Link: https://www.producthunt.com/p/ge...
( shout-out to @busmark_w_nika ! )

She talks about giving generalized advice for free, but charging for specific, tailored help. That's a good framework.
But most product owners figure this out after they build, not before.

That's backwards.

For 20 years, SEO was a human game.
You wrote for people, optimized for Google's crawlers, and built backlinks by convincing other humans to link to you.
The inputs were human. The outputs were human.

GEO is different. You're optimizing for language models that extract and synthesize. The inputs are structured data, schema markup, comparison tables. The outputs are citations, not clicks.

So where does the human fit now?

What the data says about AI's performance:

Six months ago, we ran an experiment with our own data.

At Rankfender, we tracked 5 of our own competitors across 8 AI systems. We log their share of voice, citation velocity, content gaps, platform variance. Months of raw numbers sitting in a dashboard.

I pulled 6 months of data and fed it into Claude. One question: "Based on this, who is most likely to overtake us in the next 6 months? Show your work. Use the data. Don't summarize. Give me the numbers."

The answer changed how I think about competition.

Hey PH Community !
We've been heads down building. Four new things in the works. I want to know which one matters most to you.

RASE v1.0 App Store Intelligence

Tracks how your mobile app appears in AI answers (ChatGPT, Perplexity) and in store search. If you build apps, this tells you where you're visible and where you're invisible.

Last week we did something stupid.

We paused all human coding. Gave Claude (Anthropic) access to our GitHub repo. Told it to build new features, fix bugs, and ship.

No human review. No guardrails. Just Claude and our codebase.

For 7 days, it ran the engineering team.

We're enhancing Rankfender's Content Generation Engine (RCGE) and v2.2 is coming in the next few weeks. Before we lock things in, we want to know what actually matters to people who use content generation tools.

Here's what RCGE already does:

• Intelligence. It analyzes the top 10 ranking articles for any keyword and identifies patterns. What structure do they use? What headers? What formatting? What makes them get cited by AI? Then it builds a brief based on what actually works, not guesswork.

• Structure control. You can add, remove, and reorganize H2s before generation. No fixed templates. You decide the flow.

• Inline images. Generated articles include images, not just text walls.

• Regeneration. Mess up one paragraph? Regenerate just that part. Not the whole article.

What we're adding in v2.2:

I'll go first.

Someone told me: "Just be consistent. Post every day. The algorithm rewards consistency."

So I did.

For six months, I posted every single day. Sometimes at 7am. Sometimes at 10pm. Weekends included. I wrote about our product, our features, our roadmap. I followed all the "best practices" hook in the first line, three takeaways, call to action at the end.

We surveyed 3,000 B2B buyers who used AI assistants (ChatGPT, Perplexity, Gemini) in their last vendor selection process.

The goal was simple: find out exactly what they asked and what actually influenced their shortlist.

The results reveal a massive gap between how companies market themselves and how buyers actually discover them through AI.

Last month, I went down a rabbit hole.

Product Hunt launches are every founder's obsession. Everyone wants to know the secret formula.

So I used Rankfender to analyze 1,000 Product Hunt launches from 2025-2026 tracking their AI visibility, citation rates, and what actually correlated with success.

Here's what the top 10% did that everyone else missed.

Two days ago, I shared the 10k mistake product owners make with AI search. The response was overwhelming.

Since then, we've more than doubled our dataset at Rankfender. And many found they were invisible.

But here's what scared me more:

Of those who WERE visible, 43% had incorrect information in AI answers.

Let me start from the creator s perspective:
I personally don t have a product (apart from hiring people for creative work or offering personal consultations).

But as a creator, I constantly share content, insights, and information, value that helps me build trust (for free). Based on that perceived expertise, people eventually decide to work with me (a paid service).