As an indie software business, we're constantly faced with a tough question:
Do you double down on what s working?
Or hedge your bets and build something new?

The past year at Magic Lasso Adblock, we asked ourselves that very question.

Quick update after launch:

We re now building the Team version of Cencurity.

What we noticed from the comments and DMs is that teams aren t just worried about model performance

they re worried about auditability and control.

I posted a random thread on X about the cost of living in the Netherlands. Nothing about what we're building. Just genuine thoughts about life in the Netherlands.

It hit 1M+ impressions. And here's the weird part we got a ton of signups and paid users for Starnus from it. Without ever mentioning the product.

Meanwhile, my "here's what Starnus does" posts? Way less engagement.

This genuinely messed with my head. I'm sharing the actual X post below

When I first started, I believed that as long as I built a great product, it would naturally become popular. But as I zoomed out, I realized the market is incredibly competitive. Having a good product alone isn t enough to truly convince users.

That s when I began building my presence on social media creating content about myself, sharing my journey, and talking about the product I m building. I ve come to see this as a very effective way to build trust and spark genuine interest not only in what I make, but also in who I am as a founder.

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?

Product Hunt is best known for its homepage, a daily leaderboard of the most creative and innovative products on the internet. Makers go all out to win launch day, because that visibility matters. Product Hunt also plays a significant role in how products appear in Google search results.

What surprised us was that AI assistants like ChatGPT were rarely citing Product Hunt in product recommendations.

This post is actually inspired by a tweet from @sandradjajic + an update here on PH from @chrismessina.

A few days ago I saw this:

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

First of all, I want to thank you for voting for us in yesterday's launch - you still can, the week is not over. HERE

Second thing, I summarised some things that I realised, reflected on, and maybe should have known sooner:

Hey everyone,

I've built my product around traditional SaaS pricing (monthly tiers), but I m starting to wonder if that model is getting outdated, especially with more AI-powered and compute-heavy tools entering the market.
That shift requires real architectural changes, instrumentation, metering, billing logic, and UI changes, not just pricing tweaks. It s something I m starting to seriously think about for my own product.

In particular, AI usage has real COGs (every prompt costs money), and I m seeing more platforms experimenting with usage-based models, or hybrids like SaaS base + usage + overage.

For those of you building AI or compute-intensive tools:

New AI models pop up every week. Some developer tools like @Cursor, @Zed, and @Kilo Code let you choose between different models, while more opinionated products like @Amp and @Tonkotsu default to 1 model.

Curious what the community recommends for coding tasks? Any preferences?