Connect with the Product Hunt community

Thanks for checking out Audex Trace.

Trace is a small macOS app for Apple Music that shows what s actually playing not just the badge.

It can show:

• The actual playback format: AAC / ALAC / Lossless / Hi-Res / Dolby

• The Mac output sample rate

• Whether playback and output are matched

• Playing Next quality estimates

• Skip warnings before a queued track may fail or skip

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).

Three months ago, we added the most terrifying feature in Murror's history: a single button that lets users permanently delete every insight, pattern, and memory their AI companion has built about them. Months of emotional context, journaling patterns, relationship dynamics -- gone in one tap.

Our investors thought we were insane. Our product team debated it for weeks. The data team warned us we'd lose our most valuable asset: the personalization layer that makes Murror's reflections feel meaningful over time.

That's a lot of AGI, with some substantial firepower:

Anthropic has raised $65 billion in Series H funding led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital, valuing the company at $965 billion post-money.

From Coatue, who lead the round:

...what s changed since three months ago (the last round was only three months ago, believe it or not)?

Three things:

1. We ve seen the shift from co-pilots that help make us more efficient to agents actually doing long-form work tasks on our behalf. This has meant an explosion in both productivity and ROI for customers.

2. Anthropic introduced Mythos Preview, a whole new model class that demonstrates a step change in intelligence level as seen in the METR chart below. It not only shows dramatic improvement to coding and long-running agents, it is also defining a new frontier for security.

3. And finally > use cases spreading from coding to everything else.

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.

Last summer, the idea for my SaaS, Xolora, started to take shape. Around the same time, the concept of vibe coding was blowing up. As a non-technical founder, it sounded like a dream come true. No coding experience? No problem, just let AI handle it.

The beginning was incredibly promising. Using Emergent made me feel unstoppable. I was seeing my idea come to life.

On a Tuesday, the first enterprise question is usually not can you capture AI code? It s who can see the records, how long do they live, and what happens when a policy blocks a change?

That s the part LineageLens is built for. Base gives you local capture. Lite gives a shared team record. Plus and Max move the data into a backend where auth, permissions, retention, and policy live next to the provenance records instead of around them.

The useful thing here is not another dashboard. It s a self-hosted record of prompt, model, tool, file, and outcome that engineering, security, and platform teams can actually govern on their own infrastructure.

I keep seeing AI governance tools start with visibility, then discover that the real enterprise questions are identity, retention, and review. If the record cannot be scoped, retained, and exported on your side, it is not really governable.

Hey Product Hunt

Almost 6 years ago, @Mailwarm launched here.

Back then, the idea was simple: help teams warm up their inboxes and build sender reputation before scaling email.

That launch changed a lot for us.
Mailwarm became #1 Product of the Day and Product Hunt helped us get our first real wave of visibility, users, and feedback.

Last quarter, we built a feature at Murror that our engineering team jokingly called "the empty room." After a user finishes a journal entry, the AI doesn't immediately respond. It waits. For 30 seconds, the screen shows nothing but the user's own words and a gentle prompt: "Sit with what you just wrote."

No analysis. No reframe. No pattern recognition. Just silence.

For months, we celebrated our power users at Murror the ones journaling every day, sometimes multiple times a day. They had the highest session times, the most entries, the best retention curves. On paper, they were our success story.

Then we started reading what they were actually writing.

The Apple Worldwide Developers Conference (WWDC26) kicks off June 8.

It's Tim Cook's last big event as CEO, and the company is expected to use the occasion to present a complete overhaul of Siri, the voice assistant that's been built into every iPhone since October 2011. Starting with iOS 27, Siri is expected to look a lot more like OpenAI's ChatGPT or Anthropic's Claude.

Here's a marketing problem no one prepares you for: what happens when your product's success means people stop using it?

At Murror, our best outcome is when someone works through what's been weighing on them and doesn't need to come back for a while. They journal, they process, they gain clarity and then they go live their life. That's the whole point.

Hey everyone, Elitza here, founder of own.page

A few days ago, own.page reached #2 Product of the Day on Product Hunt.

As a solo founder competing against products backed by much larger teams, this wasn't something I expected - but it was something I was determined to achieve. There were moments during the launch when I thought it would be incredibly difficult.

But this incredible community showed up.

Something that keeps coming up when I talk to teams about AI code governance: everyone focuses on capturing records, but almost nobody asks how confident they are in those records.

There are two very different things you can have.
Record A: a file-watcher noticed 47 lines appeared in auth.py and Cursor was probably running.
Record B:a proxy intercepted the Anthropic API call, matched it to the editor insertion via request UUID, measured 1.4 seconds between the API response and thecode appearing, and computed 0.81 trigram similarity between the model output and what landed in the file.

Both produce a row in your audit database. The second is dramatically more defensible but most governance tooling treats them identically.

In LineageLens, every record gets a confidence score from 0.0 to 1.0, broken into five independent evidence signals. Easy Mode captures (VS Code extension, no proxy) score around 0.27 honest about what you know. Power Mode captures (proxy running, full request interception) score up to 1.0. The score is not about whether the record is useful. It is about how much you can defend it when someone asks.

Hey Product Hunt,

I just shipped Privacy Watch in Room Service 1.4.0.

I will go first.

"Do you do backlinks?"

Every week. Sometimes every day. From prospects. From agencies. From people who read one SEO blog post from 2018.

Backlinks are not the problem. Backlinks are a solution to a problem that has changed.

One thing that surfaced while tightening LineageLens this week: capture is not the hard part. Agreement is.

If the extension, backend, and MCP server describe the same AI edit with slightly different field names or status values, you do not have provenance, you have three believable stories about the same event. That matters because reviewers and assistants start trusting whichever surface they looked at last.

The question I keep coming back to is simple: if a record can look applied in one place and accepted in another, is that still a single source of truth?

Minimi just launched on Product Hunt and we're buzzing from the response.

If you're in the p/shram community - you clearly care about getting more out of AI. Minimi is exactly that: it listens across your Mac - docs, calls, messages, tabs - and gives Claude the full picture. No prompting. All on-device and private.

Tabstack launched on Product Hunt this week, and the team is already thinking about what's next.

What should they launch? Take the poll. Spoiler alert.

I'll be honest I've never liked the feeling that someone "owns" me.

So being employed was very distant to me. [As if I had no power over my income.]

Yesterday s discussion about who is more likely to be replaced (white-collar vs. blue-collar workers) raised another question for me.

So I m asking:

What do we need to do to keep our jobs in the age of AI and robotisation?

What motivates you to build your product? For me with @Bitgrain, it's my passion for creating with graphics. I needed a tool to make grunge posters myself, so I built one, and figured, why not share it with everyone else?
What's yours ??

Tomorrow is Alpha Day

Same deal as before. If this is the first time your product is going anywhere public, launch by midnight tonight (PT time), add the Alpha launch tag, and you'll be put on a special leaderboard. Alpha launches also get a boost on the leaderboard

One thing I keep noticing is that almost everything can feel important when you are building.

Posting content, talking to users, improving the product, replying to comments, checking analytics, fixing small bugs, testing new channels, networking, reading advice, watching competitors.

All of it can be useful.

But not all of it moves the business forward at the same stage.

Memory without version history is dangerous.

Your preferences change. Your beliefs change. Your context changes. An AI that learned you in 2024 and never forgot anything isn't helpful: it's stuck in time.