We're working on a weather app that uses AI for voice-powered updates (like read out the weather forecast and wake you up: 'Rain in 30 mins grab your umbrella!').

But it got me thinking: what other cool stuff could AI do?

• Ultra-local predictions? ("Your backyard BBQ at 3PM will be sunny, but your neighbor s patio will be windy")

• Eco-friendly tips? ("Water plants today drought risk increases tomorrow")

• Personalized alerts based on routines? ("Heads-up, temps will drop during your usual jog time!")

The funny thing about building an AI product right now is that the hard part keeps changing.

A couple years ago, I was obsessed with offline evals. They felt clean. You write a test, you run it every time you change something, and you get a number you can trust. If the number goes up, you ship. If it goes down, you fix it. It s the kind of engineering loop that makes you feel like you re in control.

Hey Product Hunt community!

I m about to prepare for my first launch here, and I d love to hear from you all. What s the most valuable lesson you ve learned from your previous launches?

Keep it short let's choose the most impactful lessons. 10 words max ;) Looking forward to your insights!

I built a product backend in 2019. Unfortunately, it didn t work out. But it s a .ai domain with good domain authority. I m not interested in working on that product or niche anymore. I was emotionally attached to it last time, but this time I want to let it go.

What do you think? What do you guys usually do in situations like this?

Hello Product Hunters Friends!

As AI continues to transform digital marketing and content creation, keeping our content authentic and relatable is becoming even more essential.

After putting in significant effort to build Videco, my co-founder and I have parted ways due to differences in vision and commitment. While these situations are never easy, they serve as valuable learning experiences.
Key lessons I ve learned:
Professionalism matters more than personal relationships
Aligned vision and commitment are non-negotiable
Always have clear agreements in place things don t always go as planned
Mutual respect when things go sideway
With that in mind, I m now launching a new venture in the same industry, bringing forward the lessons learned and a renewed focus on building something even stronger.
: . @ . , .
That said, I m proud of what I ve accomplished through my own efforts. Here are the numbers I reached with my personal work:
#1 ProductHunt of the Day, #1 Marketing Tool of the Month
+500 demo's with ICP and partners
Went forward with SaaStock Pitch Competition 2024, and B2B Rocks 2024
+100k impressions and 2k clicks
Ranked Google 1st page as alternative for prime competitors
Now its time to 100x that with a better product and vibes! Onward and upward!
Curious about it? Just DM me and will show you what I mean!
https://www.linkedin.com/in/alex...

Pricing has been one of the trickiest parts of building a SaaS product for me especially deciding when to introduce regional pricing. Some markets are super price-sensitive, while others don t mind paying more for the right features. It s a tough balance set prices too high, and you lose potential customers; too low, and profitability takes a hit.

I ve seen companies like Zoho and Chargebee roll out regional pricing early to stay competitive, while Salesforce and Atlassian have mostly stuck to global pricing, with Salesforce offering regional discounts in some cases.

That got me thinking when does it actually make sense to introduce regional pricing? Should it be based on revenue milestones, number of paying users, or something else?

Would love to hear from those who ve been through this did regional pricing help with conversions, or did it add more complexity?

We've seen so many AI email assistants pop up recently. The one I'm most intrigued by is Cora. I just got off the Cora waitlist and am taking it for a spin this weekend.

I still get shiny penny syndrome when I see new productivity tools but I am starting to double down on the simple approach of doing less is more impactful. Cora sends you email summaries only 2x a day, and crafts different responses you can choose from and only surfaces the most important items so you aren't reacting to every item as it arrives and aren't living chained to your inbox. I'm excited to see if it actually improves my productivity AND impact.

Hey Product Hunt community!

I'm wrestling with a question that I think affects every maker building AI-powered commerce tools, and I'd love your perspectives.

The Question: Where Do We Draw the Line?

As AI gets more sophisticated, it's creeping into every corner of e-commerce. But should it be?