Connect with the Product Hunt community

Hi everyone!

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.

Next in our short tutorials, one task each.

This one: a chat on your own site. Pick the name and colour, choose who answers (an AI bot that hands over to your team, or just your team), and paste one snippet. Chats show up in the same inbox as calls, texts and email, with the page the visitor is on.

Video: https://youtu.be/XI9AV-yhn34

What should we cover next?

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

PasteKit currently handles 58+ formats and 48 conversion pairs, all running locally in your browser. Nothing is uploaded, and it works offline after your first visit. I want the next addition to come from you. What format or conversion do you reach for that's missing, or that you still paste into a tool you don't fully trust? Config formats, query languages, data formats, anything goes. Drop it below and upvote the ones you'd use too.

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.

When an AI application misses something, the tempting fix is to retrieve more. More chunks, more documents, maybe the entire attachment. Congratulations, you ve turned your context window into an expensive filing cabinet.

A Graphwise experiment illustrates the alternative. Across 11 questions over a dataset covering 6,000+ companies, graph-grounded retrieval used roughly 75,000 context tokens versus over four million for context stuffing. About a 54 reduction. Their write-up

That s a focused experiment, not a universal benchmark or a claim of 54 lower total costs. Building and maintaining the graph costs something too.

But the architectural lesson is useful. Relationships resolved during ingestion don t need to be rediscovered from raw text on every request. Retrieval can follow explicit connections and return targeted evidence rather than asking the model to reconstruct the connections itself.

i've been talking to a lot of researchers lately and the same thing keeps

coming up. nobody is slow because the ideas are hard. they're slow

because the stack around the ideas is held together with tape.

After reporting earnings, its stock collapsed 30% in a single day.
It's down 44% in 2 weeks.

Some users started saying that they are fed up with strict moderation rules and user toxicity + AI results directly in LLMs reduce platform traffic.

You call a company, explain your issue to the bot, get transferred, and explain it again. Then you message them on WhatsApp the next day and start from zero.

The fix isn't a smarter model. It's shared memory: past interactions, decisions and customer context stored in one place, available to every agent and every human with permission to see it. When a customer says "can we pick up where we left off?", the next conversation should already know where that was.

This turned out to be one of the hardest parts of our platform to get right, especially with permissions.

Have you seen a company do this well? Which product made you feel remembered?
Support our launch - https://www.producthunt.com/prod...

People still ask what to use instead of Stay, and many old threads about it are out of date: Stay is free now. I wrote down where it stands today, the fixes that need no app, and what Display Maid, Moom, Rectangle Pro, Putback, Workflo and Snapset do according to their own sites. I make Many Displays, so the page also says where my app may not suit you.
https://manydisplays.com/stay-al...
If you have moved from one of these tools to another, I would like to hear about your setup and what made you change.

This one is for you as users, not as founders.

When you find a new B2B tool, what do you want first? Book a demo with a real person or sign up and click around on your own?

We see both with k dlo. Some people sign up and start using it the same day. Others write to me first and want me to show them everything on a call.

Personally I almost always go self service. I only book a call when the product looks complex or expensive.

Hi everyone, Dmytro here, CTO and co-founder of Easy-Peasy.AI.

AI Employees goes live on Product Hunt tomorrow, Thursday Nov 5, at 12:01 AM Pacific. You hire AI teammates by role (19 ready-made roles, or describe your own) and brief them in a group chat. The lead splits the work, teammates reply in a thread, and you get one write-up. Each employee has a memory, its own computer and routines that run on a schedule or when an email arrives. Emails, calendar changes and app actions wait for your OK.

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

Archived repositories stop counting as work in octoscope 0.40.0

A recent audit of 212 brands found that the average AI search share of voice dropped from 23.4% during discovery to 15.7% when buyers asked pricing-related questions.

The same audit found that more than half of the brands had zero visibility during pricing searches in their categories.

There are so many different parts, inputs, and efforts that founders put into building a product.

I'm sure everyone is doing their best to achieve the best result.

Netfox 0.53.0 is out

Settings now moves the way System Settings does

Building a team or want to join a startup?

Founders, teams, and startups drop a comment if you're hiring.

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?

So I analyzed past month and 50% of TOP 3 products of the day are directly connected to AI agents (not even "just AI").
How crazy is the pace we are moving forward. Product Hunt is actually a pretty neat incubator and something we can see the trends within technologies and SaaS for almost the first time before it hits mainstream.

I wonder - when you work with AI agents - what is currently your biggest pain?

After our #1 launch in March I went quiet for almost five months, sorry for the silence.
When I came back, my old way of building with AI stopped working.

My Claude and Codex limits were gone in 2-3 days. Codex kept forgetting what the other sessions had done. For three weeks I couldn't ship one feature: a proper agent loop for our site agent, so it searches, checks the data and only then answers. I kept forwarding messages between the two AIs by hand, like a courier.

In the end I set up a harness: one shared space where every AI session, in any tool and on any computer, starts by knowing what we decided, what we tried and what's next. Within two days the stuck feature finally worked. Now my limits last the whole week.

I wanted to share this experience and discuss it here. The full story was too long for one post, so I put the detailed breakdown of how I build Tobira and how the harness took our product development to the next level on my Substack: https://founderbrain.substack.co...

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:

We're planning to split the editor inside OpenMarkdown out as an open-source (MIT) npm package that anyone can drop into their own app. The app itself stays as it is.

Before we do, we'd love to hear from you:

We've been building Dots, a macOS app that turns the notch into a customizable workspace.

And honestly, building the app has been the fun part haha.

We've spent countless hours working on features, fixing bugs, and improving the experience. But once we started putting Dots out there, we realized something.