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One interesting finding from our database is that the number of competitors appearing in AI answers does not determine a brand's share of voice.

In one category with 1,868 named brands, a single brand held 21% share of voice. Meanwhile, two brands competing against fewer than 400 held under 8%.

@Mac Duo 1.1 is out, with a few changes focused on making the fold feel more natural while keeping Mac Duo lightweight when you're just using your Mac normally.

When we started building our SaaS, I wanted to make sure we did everything "right." I read all the tech blogs, looked at how big companies like Netflix and Uber built their stacks, and convinced my co-founder that we needed a highly scalable, event-driven microservices architecture hosted on Kubernetes.

It took us 8 weeks just to get the infrastructure running. We spent weeks configuring Docker containers, setting up API gateways, and writing Terraform scripts. I felt like a genius. We were ready to handle millions of users on day one.

Fast forward six months. We currently have 20 active users, and our infrastructure costs are bleeding us dry. We are paying AWS $450/month for a product that generates $150/month in revenue. Even worse, every time we want to push a simple update (like changing the text on the landing page), it takes three days of wrestling with CI/CD pipelines.

Last week, I finally snapped. I spun up a monolithic app on a single $12/month server, migrated the core logic in two days, and we are shutting down the Kubernetes cluster. The new setup is blazing fast, and I can deploy updates in 30 seconds.

I logged every support ticket for three weeks. 11 total. Six of them were the same problem, phrased six different ways. The users weren't confused about different things. They were confused about the same thing and I had never noticed because they described it differently.

I changed one sentence on the screen where they got stuck. Not the flow. Not the feature. One sentence that explained what would happen next.

Founders launch on @producthunt with one goal: Rank as high as possible, but the first question should be: what is your launch objective?

Maybe your goal is to:
Test an idea and see if there s real interest

• Get more traffic

• Get new users

• Increase conversions

• Get feedback

• Make people try your free plan

• Get your first paying customers

• Build awareness around your product

• Get backlinks ...

Depending on your goal, the way you prepare your launch and how you measure if it was successful can be completely different.
For those who launched on Product Hunt: what was your main goal, and did you achieve it?

Confession time. MCP was one of the last things we shipped before this launch, almost a last minute decision. And honestly, I now think it s the most valuable part of k dlo.

Here s why. Ever since we started showing k dlo to people, we kept getting the same question. Why would I use this if I already have Claude Cowork / ChatGPT / my own agent? Fair question. We tried to answer it by explaining the architecture, the shared memory, how all the agents work from the same context. People nodded, but it didn t really land. Nobody gets excited about architecture diagrams

With MCP, they don t have to. You just plug k dlo into the tool you already use and feel the difference right away.

People already sell with their own AI every day. What they re missing is the context. k dlo keeps everything about your leads in one place, so it doesn t matter if you work in Claude, ChatGPT or a coding agent. That context goes with you, and the selling you already do just gets bigger. On top of that, k dlo gives you what a chat window can t, a real place to list your leads, sort them into campaigns and work on docs and everything else a deal needs.

Hey everyone,

Andriana here, co-founder of k dlo. Today is our launch day and I just wanted to stop and say thank you.

Every upvote, comment and question has meant so much to our small team. We read all of it, and your feedback is already shaping what we build next. Honestly, this is the most valuable part of launching for us!

The day isn t over yet, though, and we re still pushing. If you like what we re building, an upvote and a share with a friend or your team would help us a lot in these hours

Hey makers,

Ever had your fans kick in and no idea why? Today's update answers that from the notch.

Something pretty important changed in AIRUNCODE.

The model is becoming interchangeable.

Claude, GPT, other providers, an API endpoint, Chinese models, or a model running locally on your own machine can now operate inside the same environment and get access to the same AIRUNCODE tools.

That means you don't need a frontier model burning expensive tokens for every stupid little step of a workflow.

Hi everyone,

UX HeatGrid 2.0 launches on Product Hunt today. It is a Chrome extension that opens in the side panel and shows you any page from two angles: what its structure makes stand out, and how it is actually used.

Predict

Maker update: five recent Termexo releases focused on a practical question for people running several coding agents: which terminal needs attention, and what can you trust when you come back to it?

Agent status now follows the actual lifecycle. In v0.10.8 I checked Claude Code, Codex, OpenCode, Grok Build, and Antigravity against their installed CLI behavior. A late startup or idle event no longer overwrites a newer running state. OpenCode 2 and Grok Build also received updated integration paths for execution, input requests, failures, and completion.

v0.10.9 puts compact status icons in workspace order: gray for idle, animated green for running or thinking, red for errors or approval requests, and a green check for completion. Hovering shows the terminal's current name, including renames. Completion is a reminder to review the result: open the terminal, check output and code changes, then use Confirm completion to clear it.

ReSO AI is at #1 right now and we re barely a few hours away from Product Of The Day!

ReSO is a generative engine optimization platform that helps brands show up in AI search results. It s built for founders, CMOs, and growth teams who want to turn buyer intent in ChatGPT, Perplexity, and Google AIO into visibility, citations, and traffic.

If you believe LLMs are reshaping search behaviour in real-time, please support us on Product Hunt. We absolutely value your honest feedback on what works, what feels unclear, and you d like to see next.

A couple of my recent posts led to good conversations. Now I m trying to figure out what gets someone from reading about a product to actually trying it.

For those who ve launched something: where did your first users come from? Were they following what you were building, or did you find them somewhere completely different?

I m getting Inquir Compute ready to launch. It s a platform for running apps, databases and background jobs. I ve been sharing what I m working on here, but I m still figuring out how to reach the people who might use it.

Share your product and one specific thing you did that brought in users.

biggest upgrade since launch. until now your AI could only read about the videos on refs, now it sees them

new

frame sheets: a real frame for every shot in all 3,138 videos, plus hook sheets of the first 3 seconds

DungeonQ is designed to give security teams time and space to investigate and respond while a designated suspicious session works inside a persistent synthetic world.

The current public source now makes both sides easier to operate:

1. Participant workspace: read an order, save a multiline review note, read the saved value back from the server, and use a world-only ticket for a bounded read.

2. Control room: with separate operator authority, inspect the same world records, successful observations and a request timeline correlated with route evidence. A participant's account of what happened is not the operator's only source.

One brand went from zero AI visibility to 22% share of voice across 180 prompts in 90 days, with structured data, AI-readable product pages, and a few technical fixes.

I've been watching how brands measure SEO success, and the gap between what gets tracked and what actually drives decisions is widening. Traffic and rankings still dominate most dashboards. But in a world where over 60% of searches end without a click, those numbers tell an increasingly partial story.

Hi everyone,

Thank you again for the support on launch day. Ghostifier finished #9 with 111 upvotes, and I m still reading every comment.

I just set up an Instagram account, @ghostifier_app, to share what we re learning as we build:

The ranking is definitely exciting, but the BTS, the months of build-up, the entire village that took off to create this one product in one cramped room, and now it is available to such a HUGE audience is absolutely amazing. 

What really stood out to me is how people are actually concerned about the actual problem where LLMs are actually taking charge of search.

The best feedback has come from people who d never heard of us before.

I ve spent five years on the sales side of B2B, so I know how outbound works when there s a team, a brand and a budget behind it. What I don t know is how it works when it s just a founder with a half-finished product and no name yet.

The advice I keep running into is do things that don t scale and talk to every user. That s fine, but it doesn t tell me what people actually did on a Tuesday morning.

For those of you who ve landed your first customers:

-Where did the first 3 to 5 come from? A cold email, a DM, a community like this one, someone you already knew?

A new NBER paper tracks 500,000+ GitHub developers against their actual AI telemetry. The task-level gains are enormous and they mostly don't survive the trip to a shipped release. Across four app marketplaces: a sharp rise in new apps, no rise in total usage.

Most of the AI-productivity argument you've read this year is two camps shouting single numbers at each other. There's a paper out that makes both camps right and is more useful than either, and the revised version went up this month, so it's worth twenty minutes before you write your Q4 plan.

Ever copied something, come back to it later, and had no idea what it was? A clipboard history helps, but once it holds a few hundred items it turns into a pile: a screenshot, a hash, a paragraph, another screenshot. The thing you wanted is in there, you just can't tell which one it is.

1.3.2 is about that problem.

Select any item, press Control-Shift-N, type a name and a few tags separated by commas ("wifi, office"), press Return. The name becomes the item's title in the list, so you can tell at a glance what it is. Names and tags are searchable, so "wifi" finds the Wi-Fi QR screenshot even though the image contains no such word. And an item with a name or tags is not removed by the count or age limits, so the things you keep coming back to stay put while the rest of the history keeps churning. Clear the name and tags and the item goes back to normal.

Snippets get the same tags field. If you had a keyword on a snippet, it is now a tag.

HtmlDrag is back on Product Hunt today.

Once you have an existing or AI-generated HTML page, there are often a few things left to fix: an image, some text, or part of the layout.

I built HtmlDrag to make that editing pass more direct. Upload or paste your HTML and make visual adjustments. When you want AI s help, select the elements you want to work on, describe the change, and review the result.

I run a daily checklist for my social accounts, and this week I pulled the numbers to find out why Reddit had gone flat. Comment karma sits at 125. My last post there was 20 September, 47 days ago.

The strange part is that I already knew posts were the lever. My best post drew 62 comments. My best comment ever scored 8. On 20 September I wrote that into a plan: post 2 to 3 times a week. On 17 October a second review said it again: one post this week.

You can now connect content sources to your localization engines in Studio, translate content with your team's glossary, rules, and brand voice, and write translations back to your repositories, CMSs, or help centers.

Connect GitHub, Payload CMS, or Zendesk Help Center, or submit content through the CLI and API. Each source uses the localization engine you choose, with your team's glossary, rules, and brand voice. Product and content teams submit content from their own tools, while the localization team runs the localization infrastructure.

The CLI. Engineers use lingo push to submit source files through the localization engine's configured pipeline. lingo pull writes the completed translations to local target files on the same machine and checkout. Studio lists each submission with its status by language.

The GitHub App. When source files change on the default branch, the app translates the changes and opens a pull request with the translated files. Enable the pull request workflow to commit translations directly to a pull request branch. Require approval before automatic runs, or use /lingo translate to request specific files and languages.

I ve worked in investing and trading since 2008, and one problem has followed me throughout that time: investors have access to more data than ever, but turning that data into a clear decision remains difficult.

That s why I built Stocks 2 Buy, a platform designed to help investors: