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I put an upcoming page up four weeks ahead of a launch, exactly like every guide says, so it could gather followers instead of me scrambling on launch morning. Six days later it has one follower and I'm fairly sure I know who that is.

So one of two things is true. Either the page is invisible unless you already know the product exists, which means it isn't doing distribution work at all, it's a landing pad for traffic you have to send yourself. Or people don't follow an upcoming page without a reason, and the reason has to come from somewhere else entirely.

What I want from anyone who has shipped more than once: did your upcoming page ever produce followers on its own, or did every single one come from a thread, a newsletter, or a specific person? If it's the second, putting the page up early is still fine, it's just not the step people think it is. Real numbers welcome, zero included.

Every week we get the same request: "Can I just talk to the AI?"

They want a chat interface. A back-and-forth. Something that feels like texting a therapist at 2am. And honestly, it would be the easiest feature we could build. The AI is already there. The conversation engine exists. We could ship it in a week.

Hey PH

I'm 6 months into building my first product (still pre-PMF, ~20 active users), and user feedback has been the hardest thing to crack. Here's what I've tried so far and what I learned from each:

Every team has access to the same frontier models. Same reasoning, same benchmarks, roughly the same price.
So what's left to compete on?

Not the model. What the model knows about your work your decisions, your customers, the thing you tried six months ago that didn't work, your internal data that is the edge to why you win or lose.

Most AI tools start every conversation from zero. You're the memory layer, and you're expensive.

I think the next wave of AI products won't win on capability. They'll win on how much they remember.

The one where your email finally gets to use the whole window instead of huddling in a 840px column on the left like it's 2009.

Every fix below is the work of @gildas-refacto in #29 who not only found three pixel-level bugs we'd been staring past for months, but wrote commit messages more thorough than most postmortems. Thank you.

Fixed

• The reading pane is now the reading pane. We were capping the message at 840px wide, which meant a big monitor bought you one skinny column of text, a lot of empty pane, and a scrollbar floating somewhere in the middle of the screen. Cap's gone. The mail gets the room.

• Wide emails are no longer quietly guillotined. Some senders lay their newsletters out wider than that old column allowed, and the overflow just didn't exist. No scrollbar, no hint, no right-hand edge. Now a too-wide message scrolls sideways inside its own frame like a civilized document.

• The message stopped growing 8 pixels every time you resized the window. Turns out the frame was measuring its own height, adding a margin, then measuring that, then adding the margin again a small ouroboros of blank canvas piling up under your email, one resize at a time. 788 812 836 860, same mail. It now measures the actual content, lands flush, and stays put.

• Bonus side effect: with that 8px gone, the mail's rounded bottom corners are rounded again. Small thing. Bugged us.

Just shipped the biggest @DevCleaner update yet.

Project Hibernation lets you archive projects you are not actively working on, off your disk into a single file, and restore them in one click whenever you need them. It handles dependency reinstall on restore, is iCloud aware, and verifies every archive before touching the original.

Hey Product Hunt(ers)

We launched Collabwriting for Teams here in 2024, hit #1 Product of the Day, and then went quiet. We went heads-down to build, and told ourselves we'd come back when we had something worth saying.

Two years later, here we are.

Back then, Collabwriting helped you collect paragraphs from webpages. Today, Cluing captures almost anything - articles, PDFs, YouTube videos, TikToks, emails, social posts, even your own real-life thoughts. We went from single Topics to a full system: Clusters, a Knowledge Graph, AI Chat with any frontier model, Canvas, and MCP integration.

Everyone read today's pricing news as costs going down. On agent workloads it doesn't work like that.

A cheap model that gets something wrong rarely fails loudly. It returns something plausible, the next step eats it, and you find out four steps later. By then you've paid for the cheap call, the three calls after it, and the rerun on the expensive model. A call that errors out is nearly free by comparison, because you just retry it.

heyy folks .. am haider, the solo dev behind PopTask .. i'm launching a big update here on july 7 (it's now on iphone + ipad, not just mac) and figured i'd start a conversation instead of just showing up launch day

the whole thing started from one annoyance: every to-do app makes me fill out a form for a 2-second thought .. title, date, time, repeat, reminder .. and by the time am done i've half-forgotten why i opened it .. so i built the opposite: you type the mess the way you'd say it ("gym mon wed fri 6am") and it becomes a real scheduled task in about 3 seconds, no forms

Last month I pulled our engagement data expecting to celebrate. Daily active users up. Session length up. Entries per week up. Every growth chart pointed right and up.

Then I read what our most active users were actually writing.

Eight days after launching Termi Protocol on Product Hunt, we have completed a major round of improvements based on early user feedback.

Termi is evolving into a visual workspace for managing AI coding agents, CLI development tools, agent memory, tasks, and multi-agent workflows from one place.

1. Agent Handoff

Your AI coding agent no longer loses all progress when it reaches a usage, rate, token, or context limit.

Localization Engine Suggestions now come from the corrections human reviewers make, not only from low AI-review scores.

When a reviewer edits a translation whether in-house or through an external provider the localization engine compares the change against what it first produced. When the same fix recurs across jobs, or a correction clearly sets a term, it proposes the glossary, instruction, or brand-voice edit behind it. Apply writes the change into the engine, and the next translation runs with the fix in place.

Suggestions can now be approved or dismissed in bulk select a set and act on all of them at once, instead of one card at a time.

Full changelog: lingo.dev/changelog

Hey everyone, Chelsea here, I m the content marketer at IFTTT. Wanted to kick off something a little different from our usual here s what we shipped posts.

Quick reminder in case IFTTT s new to you: it connects the apps, devices, and services you already use so they can work together automatically. Post once and it shows up everywhere. Get a text the second your doorbell rings. Log every workout, every new item in an RSS feed, into a spreadsheet without touching it yourself. 

Another one from the launch-thread feedback pile, someone asked for a proper before/after view to build confidence in what's moving the numbers. Shipped.

You can now select any specific day and see exactly where your brand stood across total visibility, per-model breakdown, citations, and track how it's grown since. Or pick a date range and watch the whole arc.

AI can get a website to a convincing first draft quickly. The final pass is usually different: a headline needs more contrast, a section needs clearer hierarchy, an image needs replacing, or the closing CTA needs a more deliberate treatment.

Six days since Liso launched here, and thank you genuinely. A lot of what

follows came straight out of things people said in the comments and by email.

Listens are now up to ~45 minutes

The old per-listen cap cut long reads short. You can now paste a full article,

There's a well-documented phenomenon in consumer and user research that most practitioners know intuitively but rarely name directly: people don't report their experience accurately.

Not because they're dishonest. Because self-reporting is hard. In the moment of an interview, participants are performing a version of themselves. They round off hesitation. They describe their behaviour more charitably than it actually was. They say "yes, I'd probably use this" when what they felt was closer to "maybe, under the right circumstances, if the price were different." The social pressure of being in a conversation, even with an AI, shapes what gets said.

This is what we call the Say-Do Gap. The distance between what someone tells you and what they actually feel or do.

It shows up everywhere. In concept tests where participants say they love a product they'd never buy. In usability sessions where someone says "this makes sense" while visibly struggling. In brand perception studies where stated attitudes don't match purchasing behaviour.

I'm referring to the recent situation where Dataroom Corgi copied code from the @Papermark project.

The topic feels even more personal to me because I know one of Papermark's founders, and I've seen how many years she's dedicated to building the project.

Scroll the leaderboard right now and you can predict the next launch before you see it. It's an AI coworker. It lives in your Slack. It answers for you, drafts for you, books for you, follows up for you. The pitch is always the same: do more, automatically, so you don't have to.

I've been building long enough to feel the pull of that pitch. "Indispensable" is a comforting word. It sounds like a moat. It fundraises well.

Hey Community

We're working on a new Premast update that will be launching in the next few days.

We know that many professionals still rely on PowerPoint for creating and delivering presentations. That's why we've remained committed to continuously improving Premast and bringing the power of AI directly into PowerPoint.

Our goal is simple: give you the same amazing AI-powered presentation experience you love, without having to leave PowerPoint.

Spent more time on the "no sign up needed" part of my site than on any actual feature. Not because it was technically hard, it's the absence of something, which should be easy. It's because every shortcut that makes onboarding faster quietly wants an email, a login, a "just to save your results." Fighting that instinct at every step took longer than building the thing people actually came for.

Nobody's going to comment on it. Nobody screenshots "wow, no signup wall." It just quietly removes the one moment where someone almost leaves. That's the part I think gets underweighted when people plan builds, the effort spent on friction you're removing never shows up as a feature anyone can point to, but it's often the difference between someone actually using the thing and someone bouncing in the first ten seconds.

Curious if others have a version of this, something that took real effort specifically because it was invisible by design. What's the thing in your product nobody will ever thank you for, that you know mattered anyway?

You're given one extra hour every workday.

You can't use it for meetings.

How would you spend it?

Curious to see everyone's answer.

When we first launched Murror, our onboarding looked like every other app. Five screens. Set your goals. Pick your interests. Create a profile. Upload a photo.

14% of users made it through. The rest disappeared before they ever journaled a single thought.