I used to think the hardest part of building a product was building the product.

Turns out, creating superfans is harder.

The real challenge is getting people to love your product:

Hey PH community, I counted yesterday. 23 different apps before noon. Slack, Notion, ChatGPT, Figma, Google Sheets, email, Trello... and about 15 Chrome tabs I never closed from yesterday. By lunch I was exhausted and my actual work was still sitting there unfinished. The thing is, we all do this. We've normalized digital whack-a-mole. We have AI that can generate images and write code in seconds. But somehow we're still the ones doing all the clicking and switching. The AI just sits in a chat window waiting for us to feed it context. That felt backwards. So we built HappyCapy basically a computer where the AI can actually DO stuff, not just tell you what to do. Generate images, edit docs, crunch numbers, build sites. Whatever. You just describe what you need and it handles the tool-hopping. We're not replacing your main computer. But for a lot of tasks, it's way faster to just delegate to an agent that gets it done. It's live now. Still rough in places. But if you're tired of being an unpaid assistant to your own AI assistant, it might click. Curious: how many apps are you juggling right now? What's driving you most crazy about it?

We've objectively tested Safari, Chrome, Firefox, and Edge to determine which offers the best:

Speed,

Standards Compliance,

Lums hit #11 organically on Product Hunt yesterday! A massive thank you to everyone who supported us by upvoting, commenting, and downloading the app.

The launch conversations highlighted one thing we ve felt since day one: most budgeting apps ask for way too much effort before giving you any value.

Usually, you download an app and spend the next hour fixing categories, adjusting settings, and correcting transactions. By the time you're "set up," you've already lost the motivation that made you download it in the first place.

@yulia_kuznetsova3 put it perfectly! She said she added her accounts to Lums and it just showed her where her money was going. No fixing things first. Just clarity.
@selina4 shared something similar. After months of bills piling up and small charges slipping by, having everything side-by-side finally made things click.

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

I work closely with product and growth teams, and one challenge I keep running into is explaining user drop-offs to people who aren t deep into analytics.

The data usually shows where users leave, but turning that into a clear, confident explanation without overloading dashboards or making assumptions can be tough. Especially when the audience is leadership or business stakeholders.

I m curious how others handle this in practice:

AI as you know it is disrupting industries, and the software industry is at the forefront of this disruption. So what will be the future of SaaS, a model that presents users value for use?

The first and most important impact as we are already seeing is that the barrier for non-technical people to build software they require will drastically drop. This is evident in tools like lovable, bolt, replit etc... where users with no coding experience can whip up apps in a couple of minutes or hours as the case maybe.

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:

I m experimenting with something new in Trace.

Instead of asking people to check another app, Trace now sends a daily email with the most relevant things for their interests from across the web.

Same idea as the feed:
you tell it what you care about
it adapts based on what you read or skip
no trending-for-the-sake-of-it
meant to be read in a few minutes, then closed

I m curious:

The greatest invention of our time the smartphone has also become one of the biggest consumers of our energy and attention.

Being focused is now an art.

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:

I came to exactly the same conclusion that real startup ideas often come from simple and boring problems. From my own experience: I spent three years on a startup that was supposed to revolutionize online education, but in the end it had 0 users. Now I ve just started solving a simple problem for home appliance repair technicians and immediately got my first paying users on a very rough MVP.