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.

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?

Hi Noodlers!

I'm genuinely excited about this one. Big release today. Let me walk you through it.

Introducing Discovery

As pointed out by The Roundup, the inference space is booming right now.

Last week, @Baseten raised $300M at $5B valuation. They just announced the acquihire of @Inferless to "accelerate innovation in inference infrastructure."

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.

I have been thinking about situations where clients specifically ask for AI agents to simplify a process. On the surface, it sounds reasonable. They want something intelligent to classify, route, or decide. But when we go deeper into the actual workflow, we often find that the logic is completely structured. It might just be routing leads based on budget, geography, or service type. In those cases, a simple if-else condition or a fetch record from a table would solve the problem cleanly.

Another common case is using AI to analyze structured form submissions. If the inputs are predefined dropdowns and checkboxes, there is nothing to interpret. A fetch record or rule-based filter is cleaner, cheaper, and easier to maintain.

So the real question is this: are we adding AI agents because they actually do the job better, faster, or more efficiently? Or are we just throwing AI into the mix because it sounds cool and everyone else is doing it?

Real talk I can vibe-code a feature in hours but spend days figuring out what users are actually complaining about.

  No system. Bugs in DMs. Feedback in emails. Screenshots in random Slack threads.

Today we re open-sourcing the core memory engine behind @Mnexium AI: CORE-MNX.

GItHub

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

Since I haven't been able to meet my work goals very well in the last few quarters, I now plan to approach them more systematically and not push myself too hard on work goals, as that ultimately led to problems that made my plan less sustainable.

So here is my structure and list:

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?

Hey guys!

Christian here again. We launched Ekamoira GSC MCP in January. Thank you for the support!.

Now we're back with something completely different: KraftCV, a resume builder for tech candidates.

Why this exists: I've helped dozens of engineers land jobs over the years. The advice is always the same: tailor your resume, quantify achievements, optimize for ATS.

When we released the first version of the Quiz in Recall, we weren't sure how our users would respond. The Product Hunt launch exceeded our expectations, earning us product of the day, week, and month! Quiz has since become one of our stickiest features, with an average of 70 questions answered per user per month.

Given the strong engagement, we decided to invest further, bringing more question types, more flexibility in your review schedule, and our most exciting addition yet: shared quizzes. Save any content into Recall: YouTube videos, podcasts, PDFs, articles, TikToks, or take your own rich text notes and head over to the quiz tab to get started.

Last year in Unicorns Journal we published an interview with Sergey Bakaev, where we unpacked first-time fundraising strategy expectations vs reality, common mistakes, and what founders often underestimate when raising capital for the first time.

It turned into a very honest conversation.

In your org, who s responsible for videos? Or rather which team creates videos?

Marketing?
Product?
Growth?
Customer success?
Founder?

I ve noticed something interesting:

When we launched Sway here, the idea was simple: To speak out your thoughts and get structure.

Since then, a lot has happened. We shipped quite a few features. But what s been more interesting to me is how people actually use it. A few things surprised us.

First: People don t speak like they type. Voice is messy, circular, emotional and sometimes contradictory.

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

A few days ago I saw this:

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:

Source.

We added two Product Hunt badges to starnus.com.
#1 Product of the Day and #4 Product of the Week.

Feels good having them there. Thanks again to everyone who supported the launch.

Last month, Tailwind CSS fired 75% of their engineering team.

Revenue dropped 80%. Doc traffic down 40%.

Meanwhile, Tailwind is more popular than ever.

Once upon a time, developing for Apple was an exciting, rewarding challenge. But lately, that relationship has soured.

Apple has transformed into a trillion-dollar giant that sees developers not as partners, but as a resource to control, extract from, and when convenient ignore.

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:

After our first launch on Product Hunt, our team spent a little over a month upgrading the product. There were major changes to the UI and several new features added, so the process took time from discussions and redesigning the interface to testing, fixing bugs, and updating AI prompts.

We re also a very small team, so everyone had to push themselves to give 200%. Time and resources are limited, and at the same time, we also had to work on securing funding for the next six months to keep the team running and continue developing the app.

Last year we hired a design agency to build our marketing site for @Basedash. They did an incredible job. The headline makes it sound like I'm dunking on them, but I'm not. The site was genuinely great. They built it in Framer so we could manage content ourselves, which was a completely reasonable bet at the time (and something we explicitly asked for).