We spent a year building Lovon with a PhD psychologist with 40+ years of clinical experience. What makes it different:
Therapeutic, not agreeable (like gpt). Evidence-based frameworks (CBT, Emotion-Focused Therapy) designed to gently challenge unhealthy thinking - not reinforce it.
It took longer than it should have, mostly because it kept getting deprioritized in quarterly planning. And the annoying part is: the longer you wait on dark mode, the bigger it gets. More components to adjust, more edge cases, more workflows to test.
So we stopped debating it. No justification, no comparisons. We just shipped it.
Today, I read in Techcrunch that India has an ambition to "compete" with the US and China in the startup scene:
India has updated its startup rules to better support deep tech companies in sectors like space, semiconductors, and biotech, which take longer to mature.
Today, the productivity domain in tech is very well developed - there are tools for almost any need!
But at the same time, there s always a feeling that there might be something else, something better. All the time.
What I like about this space is that once people start using tools like Miro, Notion, Trello, ClickUp, etc., they tend to keep testing new things and experimenting with different tools.
10 years ago, when I started in marketing, I had never heard of Product Hunt.
Today I m here and honestly, I feel like a newcomer trying to find my way among people who build and launch world-class products. What I genuinely love so far is how open and supportive this community feels. It s a beautiful ecosystem to witness.
AI is everywhere right now - from copilots and chat assistants to analytics, research, and planning tools. But beyond the hype, I m curious about what s truly useful in day-to-day product work.
From a PM or founder perspective:
Where has AI genuinely saved you time?
What tasks do you trust AI with - and what do you never delegate?
Has AI changed how you write specs, manage roadmaps, or talk to users?
What AI use cases sounded great in theory but failed in practice?
Personally, I see a lot of potential, but also a lot of noise. I believe that in the future, AI should help us much more. Create good roadmaps, convert product specs into concrete tasks, prioritise them, assign people, push for realisation, and much more.
It s almost here for me. In three days, I ll be relaunching a major update for the app I have been collaborating with, and I ve set clear boundaries for myself about what I will and won t do before the launch. I guess these are some general, unwritten rules I try to follow
Definitely DON T:
Accept offers from charlatans promising votes or engagement for money
Send unsolicited messages begging for votes or support
Spam other people s posts with launch announcements
I've been contributing to discussions every single day for over 3 years now, and sometimes it's really hard.
One day, I have a great time coming up with topics, and then there are those days when I just stare at the screen and can't type. But I always manage to find a way.
Hey @ElevenLabs! The voice quality is miles ahead of anything else we've tried. Huge fan of what you guys are building! We re actually using it in our internal tool to generate audio summaries of specific Spotify topics. It works like magic, but we ve noticed one tiny hiccup: the audio occasionally fades out or loses volume mid-sentence. Has anyone else experienced this, or is there a specific API parameter we should look into to keep it consistent? Keep up the great work, looking forward to seeing where you take the product next!
In about 17 days (I hope I m counting correctly), I ll be re-launching the mobile app, and now I m wondering how much the Product Hunt community will try it out.
I spend 100% of my time on a desktop on this platform.
But the majority of the population is mobile-only.
