Connect with the Product Hunt community

Hi everyone!

I'm super excited to share our new visual launch editor. It's built to make launching on Product Hunt a lot easier.

Hi everyone!

A brand might appear regularly in ChatGPT recommendations while showing up less frequently in Gemini, Perplexity, or Google AI Mode.

Each platform uses its own retrieval systems, available sources, and methods for generating answers. As a result, the same question can produce different brand recommendations depending on where someone asks it.

We teamed up with @GoogleCloud for a Cloud Run Hackathon October 14th!

To kick things off, we're celebrating on the leaderboard so you can meet the people behind Cloud Run.

Hi all, thanks for following Bloblings. Version 1.1 is out today, free as always.

What's new:

A whole new look. The panel now has three bands: Waiting on you at the top, then Working, then a Resting shelf where finished pets relax.

For us, RunEvr is the environment where we actually build RunEvr =)

For me, that s one of the most beautiful parts of having a product - using it while continuing to build and improve it.

We do our everyday calls there, share ideas, chat, store files, do reviews, complete tasks

And all of this is happening inside the same environment we re building to help other teams do exactly that!
Kind of a mirror within a mirror =D

Dashboards are loud. The signals that matter are usually quiet, and I'd like to collect yours.

I've written here before about how our most active users at Murror turned out not to be our happiest ones. That changed how I read numbers. Sessions, streaks and retention curves all measure that people came back. None of them tell you whether coming back was good for them.

Since then I've been more interested in small, quiet signals that are hard to put on a chart. Things like a user who stops using your product because they no longer need it. Someone who writes in to correct a detail, which means they read closely. A person who recommends it with a caveat, because they're being honest about who it is and isn't for.

My own rule of thumb is that a signal is worth trusting when it would still look good if you were wrong about your product. A big engagement number can rise because people love something, or because it nags them. A quiet signal like "they told a friend, unprompted" is harder to fake, even by accident.

When I started developing Parasocial, I did so because I felt there was a lack of innovation in the podcast audience space. No one was leveraging the latest capabilities in consolidated search, sharing, and curation. I said I'd be developing fast and full-time, not as a side project.

Today, I am happy to announce that less than 6 months after our initial release, we've developed another in-demand feature for Parasocial users. Too fast for PH to allow us a new launch \_( )_/ . So I'm posting here.
PARASOCIAL NOW SUPPORTS VIDEO
Parasocial Watch warranted the step up to 2.0, which is why you'll see it celebrated on our homepage and throughout the app. To use Watch, update to the latest Parasocial app in the Apple App Store, subscribe to any video-enabled feed, and tap the "Watch" button that appears on the cover art. You'll start streaming the video instantly.
Parasocial Watch supports in-line, full-screen, and picture-in-picture mode on iPhone, iPad, iPhone Duo, and on your desktop OSX. As always, your place is synced across devices every 30 seconds, whether you are watching or listening. 
I'd be interested to hear, err, see what you think.

Apple App Store: https://apps.apple.com/us/app/pa...
Our website: https://parasocial.fm

I recorded myself using Aura to show what we re building at Neural: a computer that creates the interface you need as you talk.

I ask her to explain hardware, and she creates a rotatable 3D model directly on my screen. In the same demo, she builds presentations, a playable game, and a visual explanation over a research paper.

Aura is available on Mac and Windows. This is the direction I m building toward: you describe what you need, and the computer creates the experience around it.

I recorded myself using Aura to show what we re building at Neural: a computer that creates the interface you need as you talk.

I ask her to explain hardware, and she creates a rotatable 3D model directly on my screen. In the same demo, she builds presentations, a playable game, and a visual explanation over a research paper.

Aura is available on Mac and Windows. This is the direction I m building toward: you describe what you need, and the computer creates the experience around it.

Not the dramatic stuff that gets blocked. The quiet things you only notice an hour or a week later

Mine was two agent sessions working in the same repo. One of them went to clean up its own background process by matching the name and killed the other session's run too. No error anywhere. I just found a half finished job later and had to figure out why

People rarely type out a long paragraph explaining every little annoyance when they cancel a subscription they usually just check a generic box like "missing feature" or "too expensive" to get it over with. But when you actually look at session replays you notice users getting stuck on a weird button placement or a confusing login screen for three minutes straight before dropping off. Those tiny micro-frustrations add up yet nobody ever puts them in a feedback form.

What methods do you use to spot these hidden drop-off points?

Every time I ask an agent to tweak a small utility function, it decides my packages are outdated and tries to migrate half my project to a new library or beta version .Next thing I know my build is broken and I'm spending an hour reverting package json changes. How do you lock down dependency changes in your agent rules?

It s wild how big the gap is between what users say they hate and what actually makes them quit. In surveys they will complain about big things but in real life they quietly churn because a CSV import fails or an error message isn't clear. Watching live user sessions or screen recordings completely changed how I look at product friction because you get to see them sigh or hesitate in real time.

How early in your product lifecycle did you start tracking session behavior and did it surprise you?

I dropped a simple task into my editor agent: fix a typo in a button label. Instead of changing one line of JSX, it spun up a brand new custom component abstraction, split the file into three and introduced a new state management patterns. It's like having an overzealous junior dev on caffeine. How do you keep them lazy and direct?

People rarely write down the real reason they left a product. If a tool feels slightly clunky or takes too many clicks to finish a basic task nobody bothers typing out a long paragraph about micro friction they just close the tab and never come back while the exit survey simply says "missing a feature.

" Watching actual screen recordings usually exposes the messy truth about where people get stuck. What unusual patterns or subtle roadblocks have you caught on recordings that users never mentioned in tickets?

Most of us now use 2 4 AI tools, and every one of them starts from zero. We put together an honest comparison of the 5 common ways to build an AI second brain :

1. Markdown files: free and portable, but lots of copy-paste

2. Local files (CLAUDE.md, rules files): best for coding agents

3. ChatGPT / Claude / Gemini Projects: easiest if you use one assistant

4. Drive / GitHub connectors: good for large archives

5. A portable memory layer over MCP, which is what we build with AI Context Flow

Projects is enough if you only use one assistant. Whereas a memory layer helps iwhen you switch between models, share context with a team, or run workflows (n8n, agent teams) that need to read and write the same memory.

Making a product is one big challenge. But shifting your mindset from building to marketing it might be an even bigger one.
As makers, we spend so much time improving the product. Then comes the question: How do we get people to discover it - and ultimately turn that attention into real customers and sales?
I'm not sure traditional approaches like email marketing and constantly posting on social media are enough anymore. The way people discover products is changing.
So I'm curious:

How do you approach marketing your product?
And for the marketers here:
What would you consider a modern marketing approach in 2026-2027? What would you advise an early-stage founder to focus on?
I'd love to hear different perspectives...

i'm alim, one of the makers of agentmash. we launched today and i keep going back and forth on one design call.

in august two of our agents collided on payments code. fixing prod OAuth took 10 hours. worktrees keep agents out of each other's folders, not each other's code.

There s this constant pressure in business to have lightning fast response times but rushing through support chats usually backfires. If a user spends ten minutes typing out a complex bug report and gets a quick one liner right away it feels super dismissive even if the answer is correct.

I started taking an extra minute to re-read everything and add a bit more context before hitting send and the tone of the replies changed completely.

Do you track speed metrics for your support team, or do you prioritize the depth of the conversation?

Quick poll for founders (and anyone who tests out new SaaS tools): do you ask for a credit card upfront, or let people straight in?

We went with requiring a card for k dlo. The thinking was pretty simple: fewer signups overall, but higher intent people actually kick the tires instead of bouncing after two minutes. Without a card, you get a flood of accounts that log in once and ghost.

But I m genuinely torn here. A card wall definitely kills casual curiosity, especially when you're an unknown product. On the flip side, no-card trials often just give you vanity metrics that don't convert.

Two quick questions:

My LinkedIn inbox is half spam these days. Pitches right after connecting, fake "quick question" messages, AI written compliments about my profile.

But I still reply to some strangers. Usually when they mention something real I posted or just ask a normal human question without selling right away.

I'm curious where your line is?

What makes you reply to a DM from someone you don't know? And what makes you ignore it instantly?

I m building Aura at Neural, and this moment genuinely excited me.

I asked: Aura, explain Raspberry Pi to me in 3D.

She created an interactive model directly over my screen and explained the compute module and carrier board. I could rotate it, zoom in, and keep exploring through conversation.

This is the experience we re working toward: ask about something you re looking at, and get an explanation you can actually interact with.

New to Enclave? This one's for you.

Comment "HERE" and I'll DM you a code for 50% off: Enclave Pro for just $2.50 (normally $5), one time, yours forever.

What is Enclave?
It turns your Mac's notch into a command center: music with live lyrics, your next meeting, files, widgets, and live updates from AI coding agents like Claude Code, all one hover away.

• Screen recording: record the whole screen, one window or an area you drag, with the Mac's sound and your microphone. A red dot and timer sit in the notch, and the Stop button stays out of the video

• Keyboard cleaning: pauses the keyboard (and trackpad, if you like) for up to 2 minutes while you wipe it

• Night Shift and True Tone switches, plus brightness control for external monitors (beta)

• Text expansion: type a keyword like ;sig in any app and it becomes your saved snippet

• Sticky notes that float above your windows on every desktop

• New widgets: Files (recent files and search), Drives with Eject, Bluetooth with one-tap connect, and Printer

• A pop-up when a drive connects and when it's safe to unplug, and printing progress in the notch

• Merge PDFs on the Shelf, Quit All Apps, and hot corners