Connect with the Product Hunt community

Do you think the idea of setting up an MCP server to be able to use Local Panel s fantastic features alongside AI tools would be unnecessary, or would it be a very useful feature?

We re also thinking of running adverts for Local Panel where do you think would be the best place for that? I m sure it s not Meta.

In 2026 the bottleneck isn't code anymore it's the person typing the prompts. Here's what I do to keep that person functional.

A year ago, "I built a working app this weekend" was a flex. Now it's a Tuesday. Vibe coding went mainstream, agents write most of the first draft, and the gap between an idea and a shipped product has basically collapsed. That's the good news, and it's genuinely great.

Quick update since launch. I have spent most of this week improving reliability, Music.app integration and large library support. Playback with missing local files is now cleaner and should no longer trigger repeated Locate prompts. LMO can now detect moved or replaced files more reliably even when the Persistent ID has not changed, and repaired locations are updated without rebuilding the entire library. Health Check and orphan handling were tightened to reduce the risk of importing replacement files as new Music.app records. Duplicate cleanup was also improved so verified merges no longer create automatic backup playlists, while playlist membership is still protected before removing the duplicate record. I also improved saved Library Index restore behavior for very large libraries and fixed external drive diagnostics so sandbox permissions do not produce misleading unreadable volume results. A Track Flags diagnostic also completed successfully on a test library with 827,100 Music.app records and found no abnormal playback related flags. Most of this work was about making the existing tools safer and more predictable rather than adding more features.

you hit logout. the app says you're out. but somewhere, on another device, on another app using the same login, your session is still alive.

most users assume logout means logout everywhere. it doesn't. it usually means logout from this tab, on this device, right now. everything else keeps running until the token expires.

A completed task is easy to summarize. The work behind it is not.

A short update might say, Fixed the issue and opened a PR. That sentence hides several different kinds of work:

1. Investigation: reproducing an inconsistent bug, comparing logs, tracing data across files, and checking recent changes.

2. Failed approaches: testing fixes that introduced new problems or ruled out incorrect assumptions.

3. Technical judgment: choosing a maintainable solution instead of the quickest one.

4. Review: finding related edge cases and preventing the issue from recurring elsewhere.

5. Unplanned work: handling interruptions and problems that were never part of the original task.

When this context disappears, complex work looks trivial and efficient problem-solving becomes almost invisible. Teammates see what changed, but not why it changed, what alternatives were rejected, or what they should know before working on the same area.

A few hours into our launch, Lenz is now sitting at #3 Product of the Day on Product Hunt.

For a small, bootstrapped team, this is a pretty special milestone. We re incredibly grateful to everyone who has checked out the launch, tried the product, asked thoughtful questions, and shared feedback along the way.

Here is the paradox of 2026.

Reddit now holds 10.24% of Google's top 3 organic positions. One in every ten top results belongs to Reddit .

The number of keywords where Reddit ranks #1 jumped 54% , from 8,993 in March to 13,872 after the May 2026 core update .

Reddit's top 3 share rose in all 20 niches tracked. The biggest gains came in experience-led categories pets, education, sports, and e-commerce.

I ve run into this with longer agent runs and I m curious how others handle it.

The original issue might contain the scope, constraints and evidence required. But when another model or session picks up the work later, those conditions often get reduced to a summary.

hi folks,

we've been hard at work after the Product Hunt launch! Our usage has grown 10x month to month, and with that came a lot of product ideas.

A little while ago, I posted here asking what you'd look for first in a redesigned CodexBar Lite.

The feedback was incredibly useful - especially around glanceability, keeping the app lightweight, and making sure a menu bar utility stays out of your way.

After using the redesign myself for a while and polishing the little things, it's now live.

The goal hasn't changed: keep CodexBar Lite minimal, privacy-first, and focused on doing one thing well.

I noticed a small problem in my debugging workflow with AI agents.

When something broke, my first instinct was:

One thing we ve been thinking about while building Traccia: an agent can get stuck making repeated tool calls, or keep switching to expensive models, without actually making meaningful progress.

And the scary part is that the run may still technically succeed.

So, there obviously have been a lot of tools focused on building AI agents. Very few, however, are talking about what happens after you deploy them.

Coming from a software development background, this feels like the obvious next layer.

We have CI/CD, observability, testing, incident management, version control, and performance monitoring for traditional software.

What does that stack look like for AI agents?

Focusing on signup momentum is fun but customer cancellations quickly shift your focus once revenue is involved.

A lot of cancellation reasons boil down to routine integration rather than minor feature requests. Fixing how a product fits into someone's workday is a much tougher challenge than just shipping another update.

Do experienced founders eventually get used to churn or do you just build faster ways to analyze and act on user cancellation reasons?

You can now translate your Zendesk Help Center from Lingo.dev.

The Zendesk Help Center integration connects your Help Center to a localization engine you host on Lingo.dev. Choose the categories, sections, and articles to cover, and Lingo.dev translates their titles, descriptions, and bodies into your target languages, then writes each translation back to Zendesk. Article bodies translate as HTML, so links, formatting, and embedded media survive the round trip.

There are two ways to keep your Help Center translations up to date. The first, Sync, translates only the articles you have added or edited since the last run. The second, Retranslate, rebuilds every article in scope from scratch, which is what you want after changing the localization engine's glossary, brand voice, or rules and needing your existing translations regenerated against the new configuration.

Hey dear Community !

While building RunEvr, we created different modules for creative teams - Materials, Tasks, Boards, Forums, Reviews, and more.

One part we re especially curious about is team communication

Our Forum module is designed around project-based conversations, and naturally users often compare it with Slack.

We're genuinely excited about this one.
You already start your day inside an AI - Claude, ChatGPT, Cursor. That's where the thinking happens. But the work lives somewhere else, and you spend all day copying between the two.
So we're killing that gap: RunEvr is getting an MCP server. (MCP = the open standard - now backed by Anthropic, OpenAI, Google & the Linux Foundation - that lets your AI securely plug into real apps. RunEvr is becoming one.)
Connect the AI you already use, and just talk:
"Create a task for Sara to review the trailer, due Friday."
"Did anyone reply to my thread about the poster?"
"What's waiting on me right now?"
Your AI does it, and it shows up live in RunEvr for the whole team.
Works with Claude, Cursor, and ChatGPT.
The best part: you don't pay us a penny extra. It runs on your own AI account - your existing free or paid Claude/ChatGPT plan. We don't meter it, don't upsell it, don't touch your bill.
And one line we won't cross: your AI can never see more than you can. Same permissions as you - superpowers, not a backstage pass.
Which AI do you live in - and what's the first thing you'd have it do in your workspace?
---------------------
If you re just getting familiar with MCP, here are a few places to start:
MCP official documentation
MCP Apps
2026 MCP Roadmap

The deal is done.
NVIDIA has officially agreed to acquire Hugging Face, the company known for its GitHub-like repository of open-source AI models, for $12.9 billion.

What it means:

• NVIDIA gets vertical integration. From chips to inference to the model hub itself.

• Hugging Face gets capital & infrastructure. No more fundraising pressure. Access to world-class compute.

• The open-source question: Will Hugging Face stay truly open-source? Or pivot to favor NVIDIA hardware?

• Station F's first mega-exit. This is a W for French tech. Cl ment Delangue just built one of the most valuable AI startups ever (i'm proud of my country !!!)
  And do you think NVIDIA ownership make Hugging Face more useful or less trustworthy?

When i launched @Murmell ,
i found that in mobile, you can see the upvotes before the 4 hours period.

So @rrhoover pleaseee fix that.

Do you guys faced some bug glitches or something you want to improve in Product Hunt ?

When someone raised money, especially from a prominent VC with a strong reputation, like Antler or Y Combinator, the company immediately sounded more trustworthy to me.

But the latest analysis shared by @4kulia showed that in the first half of the year, only 26 launches were VC-funded.

Hello guys,
We are re-opening Murmell after a month of intensively rebuilding, so let's support each other !
I'm relying on you guys for the best support !!
I'll be grateful if you do so and will give back all the support :)

And for the users of the waitlist a BIG GIFT is waiting for you

(a looooot of claude credits hehehe)

This is a question that does not get asked enough.

Right now, if you use a hosted AI memory tool, your context, your decisions, your preferences, your project history, all of it lives on someone else's servers. Governed by their retention policies. Subject to their pricing changes. Potentially readable by their team.

Something we ve been thinking about while building Cloud World Model:

If an infrastructure simulator doesn t model a particular cost, a human might recognize that the estimate is incomplete.

An RL agent may not.

Some features of a launched product are so basic and taken for granted that we don t even think of them as options. They re a sure thing.

Usually, I see them as:

Dark mode

Bond secured #1 Product of the Week on Product Hunt earlier this summer and we ve decided to leak our exact playbook.
Join us on August 13th for a workshop where the Bond team will reveal exactly how we earned more than 800 upvotes in 24 hours without ever dropping below the top spot.
You ll leave with:
- A step-by-step launch timeline, even if you re on a time crunch
- The exact assets to prepare
- A launch-day checklist and distribution plan
- Access to a private community of founders preparing for and sharing advice on Product Hunt launches
We ll also give direct feedback on your upcoming launches and end with an open Q&A.
Sign up HERE
PS. Want research-backed productivity lessons from the world s highest performers, behind-the-scenes Bond updates, and first access to playbooks like this one? Join our newsletter and learn how to win back 10 hours every week.