According to @RevenueCat 's State of Subscription Apps 2026 report, "hard paywalls convert 5x better than freemium, but with significantly wider variance."

Day 35 download-to-paid, freemium vs. hard paywall

Does access method impact download-to-paid conversion within 35 days?

I ve been experimenting with different ways to build outbound lists recently.

The usual tools show up quickly.

Clay. Apollo.
A bunch of automations promising endless leads.

And they are useful.

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).

TL;DR: Yes, you can build a strong community.

But if I break it down a bit:

Curious what the community is running for authentication/authorization in their apps (e.g. Auth0, Supabase Auth, Clerk, Firebase Auth, Cognito, etc.)

A few things I'd love to hear your take on:

• What provider are you using and what's your primary stack? (e.g. Next.js + Clerk, Go + Auth0, etc.)

• What's the one thing that surprised you , good or bad ?

• Would you make the same call today? Especially curious if you've hit scaling pain.

For context: I'm building a B2C application with my own database layer, and currently in the process of evaluating which authentication provider best fits the architecture. Trying to understand how others are handling the auth <> database relationship and what influenced your final decision.

Working towards launching my app.
It's too early for meaningful data, growth trends, or any real signal on what's working, and I'm okay with that.

What I've noticed though is that the internet is full of milestone posts. First 100 users, $10k MRR, viral launches. And when you're pre-data, it's easy to accidentally use someone else's month 18 as your week 1 benchmark.

I'm not losing sleep over it, but it did get me thinking about how founders define meaningful progress before the numbers are there to tell the story.

My current approach is staying focused on qualitative signals are the right people finding it, are early users actually engaging, are conversations happening. But I'm curious what others have done:

We've been analyzing demo funnels across B2B SaaS companies, and the pattern is consistent: the "Book a demo" button creates a 5 9 day gap between peak buyer intent and first product contact.

By the time the call happens, half the excitement is gone. No-show rates climb. Reps spend the first 15 minutes on basics the prospect would've preferred to explore alone.
The fix isn't a better calendar tool. It's removing the wait entirely.

We built Naoma to replace that gap with an instant AI demo live, conversational, running in the browser 24/7. The prospect gets a real product walkthrough the moment they click. We route qualified leads straight to sales.

In early pilots, we're seeing 6 20% visitor-to-demo conversion, which for most inbound funnels is a meaningful jump from the default.

One piece of advice we hear all the time in startups is: launch fast. Ship early, test with real users, and improve along the way.

But lately it feels like the landscape is changing. With so many products launching every day, sometimes a half-baked launch disappears instantly, while more polished products seem to get better traction.

So I m curious about your experience:
Is launching fast still the best strategy?
Or is it better to wait a bit longer and launch something more refined?
Have you seen examples where speed helped a product win, or where quality at launch mattered more?

Would love to hear how other makers here approach this balance between speed and quality.

Genuinely curious what the community does here.

We've been talking to hundreds of teams building with Cursor, Claude Code, and other agentic tools and the honest answer from most of them is: "We just run it and hope."

Some do a quick manual click-through. Some write a few spot checks. Some just ship and wait for users to find the bugs.

We built TestSprite to solve exactly this autonomous testing that runs from your PRD and codebase but I'm curious what your actual workflow looks like before you merge.

While building a product, I ve also been trying to run content on social media to bring in more traffic. I experimented with creating AI-generated characters and producing UGC-style videos around them.

During this process, I realized something interesting: there are hundreds of tools that can generate virtual characters and UGC-style videos. But what actually makes a video engaging isn t the tool - it s the authenticity of the person creating the content.

Two conversations. Same week.

First founder said,
Really interesting product. Love what you re building.

Great energy. Smart questions. Strong validation.

We never heard back.

I am a Computer Science student doing research into how solopreneurs and small startups create new apps and what their stack looks like. Particularly, I'm interested in how you handle things like authentication, billing, and permissions/authorization in your apps.

Let me know what you're working on below and how you're going about it -- I'd love to connect for some quick calls to learn about your product and talk about your process in building it!

I recently saw a marketer with 10k+ followers launch and finish 6th with 348 upvotes. They followed a proper pre-launch and post-launch plan, did everything right, and still the outcome felt unpredictable.

Now I m launching @Curatora next week.

I m not a marketer. I have a little over 1k followers. Of course, asking for support helps. But I also keep hearing that a large part of the Product Hunt community shows up mainly for their own launch, then goes quiet until the next one.

That makes me wonder: how much of success here is strategy, and how much is timing and network effect?

With the advent of clawdbots, it's as if we've all lost our inhibitions and "put our lives completely in their hands."

I'm all for delegating work, but not giving them too much personal/sensitive stuff to handle.

As usual, Y Combinator came up with segments that are worth investing:

1. Cursor for Product Managers
2. AI-Native Hedge Funds
3. AI-Native Agencies
4. Stablecoin Financial Services
5. AI for Government
6. Modern Metal Mills
7. AI Guidance for Physical Work 8. Large Spatial Models 9. Infra for Government Fraud Hunters 10. Make LLMs Easy to Train