I still reply to every comment manually. Reddit, LinkedIn, Product Hunt, forums, Twitter, Discord. Every single one.
AI could do this. There are tools that generate replies, post on schedule, analyze sentiment, even mimic your brand voice. But I don't use them. Here's why.
A 2024 study on community engagement across 500 brands found that personalized responses drive 3.2x higher retention and 4.7x more repeat interactions than automated replies. People can tell when a response is copy-pasted. They can feel when no one actually read their comment. The average user only needs 2-3 automated interactions before they disengage entirely.
As founders, calls are part of our daily life. Brainstorming, quick updates, random discussions with the team and there s always value in those moments. But most of the time, all that value just disappears after the call. By connecting Prodshort to your calendar, it automatically joins your calls and turns them into ready-to-post content.
If you're a founder and want to create content, I'm doing short discussion calls. Let's connect !!
Just wanted to share a little "behind the scenes" pain from the OptiClear launch. We all know the Apple App Store review process can be a rollercoaster, and I definitely hit a loop.
I had built this sweet "Invite a Friend" feature. The logic was simple: generate a code, share it with a friend, and both of you earn free premium days. A classic, organic growth loop, right?
Well, Apple hit me with a rejection. Apparently, unlocking premium features outside of their standard In-App Purchase flow (even as a reward) is a big no-no.
TwelveLabs just introduced Pegasus 1.5, their most significant leap in generative video AI, transforming video into a queryable, structured data asset.
Stop paying monthly for an AI wrapper. opencode runs in your terminal, connects to 75+ model providers via your own API keys, and costs exactly what you use nothing more.
I switched from Cursor after my third renewal. The thing that finally pushed me: I realized I was paying for the tool and the model, when I already had API credits sitting unused. opencode let me plug those in directly.
A few things that actually matter in daily use:
Build vs Plan mode. Plan mode drafts what it's going to do before touching any files. Sounds small. Isn't.
I was reading Nika's thread here about free vs paid features. Really made me think.
Link: https://www.producthunt.com/p/ge... ( shout-out to @busmark_w_nika ! )
She talks about giving generalized advice for free, but charging for specific, tailored help. That's a good framework. But most product owners figure this out after they build, not before.
We teamed up with @Vercel for a special launch day, which means there s a dedicated leaderboard full of teams shipping on Vercel, all in one place. More launches, more competition, more reasons to spend too long refreshing the page.
Hi Gang! Excited to announce that @arthur_romanov and I got nominated for our local Forbes 30U30 award - could you kindly support us by visiting the link below and smashing that button (under profile pic) to make sure we get the top vote Huge thank you for all your help over the years
@Wispr Flow launched on Product Hunt back in 2024. Since then it has become one of those tools that quietly sticks. It's the AI dictation tool a bunch of us here use day to day (yes, there are still a few people committed to typing everything out). It works anywhere on your Mac or PC, so you can just talk and have clean text land wherever your cursor is.
For the next three days, it is showing up on the leaderboard in a different way. From April 14 to 16, you can upvote and comment on Product Hunt using Wispr Flow directly. If you use dictation, those upvotes and comments will carry a bit more weight. Try it out by clicking the Wispr Flow unit on the Leaderboard and telling it to upvote a product name
For the first year of building Murror, we optimized for the same metrics every other app optimizes for: daily active users, session length, screens per visit. The dashboard looked healthy. Usage was growing. We felt good about it.
But something was off. Our most engaged users were not our happiest users. People who spent the most time in the app were often the ones who left the harshest feedback. Meanwhile, users who opened the app twice a week for five minutes were writing us emails about how it changed how they handle difficult conversations.
We re trying something new on Thursday: Alpha Day.
The idea is simple. If this is the first time you re launching your product anywhere, you can tag it alpha and get a boost to your points (and land on a special leaderboard).
Lately, I ve been looking closely at how independent builders and small teams are managing AI knowledge bases. It feels like the default "industry standard" is to immediately reach for a complex RAG pipeline and a heavy, paid Vector Database.
But I'm starting to wonder if we are over-engineering this for 90% of standard use cases.
Vector DBs are incredibly powerful for massive scale, but for smaller or non-massive datasets, they can be expensive, complex to query, and act as complete black boxes. If a search returns a weird chunk, diagnosing it is often a nightmare.
I genuinely love listening to podcasts. It's one of the best ways I've found to stay on top of new trends, pick up strategies I wouldn't have discovered otherwise, and come across founders and operators I'd never stumble on through regular reading.
So I'm always on the lookout for new ones worth adding to the rotation.
It featured individuals who managed to build significant profit while running their businesses solo, without employees. Until now, I ve seen these more as exceptions rather than the norm.
Right now we have scenarios covering things like giving hard feedback, managing up, and pushing back on scope creep, and more. But I'm building out the next set and I'd rather build what people actually need than guess.
So: what's the conversation you keep putting off?
What's the one you replayed in your head after it went sideways?
Six months ago, we ran an experiment with our own data.
At Rankfender, we tracked 5 of our own competitors across 8 AI systems. We log their share of voice, citation velocity, content gaps, platform variance. Months of raw numbers sitting in a dashboard.
I pulled 6 months of data and fed it into Claude. One question: "Based on this, who is most likely to overtake us in the next 6 months? Show your work. Use the data. Don't summarize. Give me the numbers."
