Connect with the Product Hunt community

We've teamed up with @Y Combinator or to give builders one more chance.

Launch on Product Hunt this Friday, tag your post "YC application" @gustaf will personally review the top launches. One or more will walk away with a YC interview, even though the official deadline has passed.

Let me start from the creator s perspective:
I personally don t have a product (apart from hiring people for creative work or offering personal consultations).

But as a creator, I constantly share content, insights, and information, value that helps me build trust (for free). Based on that perceived expertise, people eventually decide to work with me (a paid service).

1. I've always been on the personal brand side. More and more founders are building it now (sometimes even before the product is ready while it's still in development, before seed fundraising). The CEO builds their position so the product sells more easily at the official launch.

2. But I have experience with people who built the product, scaled it, and only then did we discover who was behind it.

Honestly, with the first approach, I'd be concerned that people invest more in me as a person than in the product. People would idealise the founder and overlook the product's flaws (which could hurt development and constructive feedback).

+ I noticed the most common mistake that many people who started building a personal brand first, connected their product to their personal accounts (emails, social media, etc.) and started having a problem selling these things, because they cannot "give someone keys" to their personal profiles.

I'll go first,
During the launch of Bitgrain, I thought maybe some 10 20 people might upvote or it can be even lesser, Surprisingly it got featured and the numbers went up crazy! I got mails from people who loved the product. It was unexpected but loved it!

AI is incredibly good, I d even say almost perfect.

And for many people, that uniformity of perfect templates is starting to feel annoying.

VibeAround v0.5.8 is live.

This release is a bigger rewrite of the Launch/Profile system, plus a more capable local API proxy for coding agents.

We thought we were ready.

Bigger deals. Fewer customers. Better margins. That was the dream.

So we built enterprise features. SSO. Advanced permissions. Audit logs. A whole new pricing tier starting at $2,000/month.

We spent 6 months. Three engineers. One dedicated product manager. Endless meetings about "enterprise readiness."

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).

Sorry guys I was a little busy I'll have some idea about slapwindows

Agents can now remember your workspace context like a persistent brain for your project making long-running engineering tasks, multi-step workflows, and delegated agent work far more consistent.

Tollecode is a local-first AI coding assistant built for real engineering work:

• File reads

• Shell commands

• Sub-agents

• Full control over execution

Not all context is equal.

So we stopped treating it that way.

Most AI tools store everything the same:

• Writing rules

• Personal background

• Preferences

• Temporary notes

I like working (a lot of working), but sometimes I struggle with my time.
Understand that I am not able to manage/fit everything that I wanted to do in my schedule.

So I had to "re-organise" some activities and was able to learn something or make myself productive.

Our vision has been the same from day one: one knowledge base that works across all your AI tools.
And to achieve that, we launched our MCP Server in February. It connected to Claude Desktop, Claude Code, LM Studio, and most major AI agents. As far as we were concerned, the MCP chapter was closed.
Then we launched on AppSumo.
Within days, users kept asking for one thing: " ?"
Then came the questions about headless agents. CI scripts. n8n workflows. Users had intricate setups. They wanted a memory store for their OpenClaw agents, which they could also plug into Claude, which they could also call from a workflow runner. One memory, three completely different environments.
That's when we realized our MCP Server had a problem: it only supported OAuth. *facepalm*
(Getting a bit technical here, bear with me)
OAuth assumes there's a user sitting at a UI who can click "sign in" in a browser window. That's fine for Claude Desktop. It falls apart the moment you're running a headless agent on a server, or chaining four tools together in an automated workflow. Nobody is there to click anything!
So the team got to work. A few days later, we shipped Personal Access Tokens (PATs) for the MCP Server.
And that's how we ended up being the that works in three places at once:
In your browser, as a sidebar
Inside your chat agents, as an extension or MCP server
In your programmatic workflows, as an MCP with PAT-based authentication
New setup guides for everything are at docs.plurality.network.
Maybe a weekend project: give your OpenClaw or n8n agents a memory. Make them less forgetful, more intelligent, and a lot more useful.
If you are already running such setups, we have a lifetime deal going on for AI Context Flow: https://appsumo.8odi.net/m4n0da

I will go first.

The meeting where everyone nods and no one disagrees.

Not because they agree. Because they have checked out. They do not think their opinion matters. They have stopped investing.

That silence is louder than any argument.

The problem at MindPal was pretty simple: we have hundreds of AI templates to share. We know videos of these templates work - some have gotten us tens of thousands of views. But actually making them was a total nightmare.
We tried everything. At one point, we even hired a freelancer, but the feedback loop was exhausting. It actually took longer to give feedback and wait for revisions than it did to just make the video ourselves. It was slow, expensive, and impossible to scale.
When we did it ourselves, it was a massive grind:
Record the screen of the behind-the-scene agent builder
Record a demo of the agent working
Write a script that didn't sound like a robot
Record a voiceover or an avatar
Spend hours editing everything together
If my co-founder or I were tired or busy, the videos just didn't happen. I assumed this was just the "manual tax" you had to pay for quality.
Last weekend, I got fed up and asked Claude if I could just automate the whole damn thing.
Turns out, I can.
So I spent the weekend cooking something - an internal AI SOP to turn any workflow URL (yes, from just a single URL) into a publish-ready use case video that passes all quality standards in ONE GO.
Here is the new setup:
Playwright: Records the screen and even moves the mouse like a human
@Claude by Anthropic: Writes the narrative based on our actual product info
@HeyGen: Creates the avatar and voiceover
@Remotion: Programs the entire edit - syncing everything into a final file
@Zernio + @Railway: Automatically publishes the video and saves the assets.
Now, I just give the system a URL and a finished video comes out. I don't even have to click "upload."
I just wrote a post sharing the full behind-the-scenes build, the architecture, and the logic behind of this AI video agent. Check it out here if you think this could be helpful for your company: https://mindpal.space/article/ai...

P/s: This is what I wake up to every day now

Hey Hunters!

Quick update on octoscope, the cross-platform terminal dashboard for GitHub. v0.10.0 just shipped and it's the first release where the app steps beyond "summary dashboard" you can now drill into a single repo / PR / issue without leaving the terminal.

What's new:

Action menu press space on any row of Repos / PRs / Issues to open a centered modal:

Most product teams run surveys. We did too. We'd ask things like "What features would you like to see?" or "How would you rate your experience?" And we'd get perfectly reasonable, perfectly useless answers.

The turning point for Murror came when we stopped designing around what people said they wanted and started paying attention to what they were avoiding.

For us, it started from something frustrating: creating content felt very annoying and time-consuming. We tried the classic way: scripting, memorizing, filming, editing. But none of it felt authentic. And honestly, it was eating time we needed to focus on other things.

At the same time, we kept reading the same advice everywhere:
"founders should build in public and create content consistently". Easy to say but harder to do in reality. So instead of forcing ourselves to create content from scratch, we tried something simple: recording our own calls and using those moments as content.

After talking to 50+ small businesses, we kept hearing the same thing

"We're losing customers not because of bad service, but because we can't keep up."

Every day, after launching, makers are contacted on LinkedIn and X by people offering to sell votes. As the Product Hunt team, we are very much aware of this and really hate it. We have systems in place to neutralize this type of gaming. Every vote counts for a different number of points on Product Hunt. A couple examples:

• An account with a recently created gmail address and no history of quality contributions on Product Hunt: this vote will count for 0 points. Yes, this might be a well intentioned user, but we take a conservative approach to protect the community. If the account has a company email or applies for verification on Product Hunt, that's a different story.

• An account with a company email address linked to a legitimate LinkedIn account with a history of meaningful contributions on Product Hunt: this vote carries significant weight.

A couple questions for the community:

• Are there specific accounts on Product Hunt that you suspect participate in vote selling? You can reply here or email report@producthunt.co

• What would you want to see us do differently here?

We analyzed the codebases of 100 startups that hit a scalability wall (*)
The goal was not to find the most exotic bug. The goal was to find the most common, expensive, and preventable patterns of failure.

The results were almost identical across 85% of them. Here is what the data says.

The Timeline to Failure

Months 1 6: Everything worked. Fast releases. Happy customers. No time for architecture.

Hey Product Hunt community

It s been a week since we launched Ovren - and I just want to say a genuine thank you.

We built Ovren because every team has backlog work that never makes it into a sprint.
Not more ideas. Not more AI suggestions.
Real engineering work that needs to get shipped.

So we launched Ovren as an AI engineering execution product for real backlog tasks:
AI frontend and backend engineers that work inside your real codebase, execute scoped work, and return reviewable code updates.

Today, this graphic caught my attention:

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.