Connect with the Product Hunt community

Most knowledge tools put the connection work on you. Tag this. Link that. File it in the right folder.

Second Brain v2 builds the graph automatically.

We finished #5 Product of the Day. Here's what three days of 60+ comments actually taught us.

We launched Cloud World Model on Product Hunt last week. The pitch: simulate AWS, GCP, Azure, OCI, and DigitalOcean infrastructure without provisioning real resources. You describe an architecture compute, databases, load balancers, serverless functions and the simulator models latency curves, CPU saturation, autoscaling behavior, failure propagation, and cost. No cloud bill.

We expected interest from learners. The comments told a different story.

Last week, I launched Fikry an AI that starts with good intentions, gets close to the right answer, and then confidently takes a completely wrong turn.

Today, I m launching its biggest update yet: Fikrypedia.

Adomate is now live on Product Hunt!

We'd greatly appreciate your support and feedback. If you get a chance, please check it out and let us know what you think.

https://www.producthunt.com/prod...

Thank you for your support!

The one where Skim learns to smell a phishing email from across the room and does it all locally, offline, without phoning a single reputation service. Your inbox, now with a healthy sense of suspicion.

New

• Phishing detection, built right in. Skim now quietly vets every message for the classic tells and warns you before you click something you'll regret.

  • Sender checks reads SPF / DKIM / DMARC results, catches "reply goes to a totally different domain" tricks, spots when the friendly display name hides a stranger's address, and flags lookalike domains (paypa1.com, we see you).

  • Link checks a link that says one thing but opens another, user@evil.com sleight of hand, and raw-IP links get stopped cold. Shorteners, plain http, punycode, weird ports and endless subdomains get side-eye too but only when the sender already looks shady, so your newsletters full of tracking redirects don't set off alarms.

  • A link gate click a suspicious link and Skim tells you where it actually goes and lets you bail or proceed. No more mystery destinations.

  • "Check for phishing" with AI one tap to have Skim AI read the sender, the auth results, and the links, then explain the whole thing in plain language.

• All of it deterministic, all of it offline. No thresholds to tune, no data leaving your machine.

Not building lookalike list.
All of us must be having some customers. Some customers came inbound, few via referrals, few via word of mouth- it does not matter.
What matters is that these customers are able to solve their pains with your product.
Hence, once they are your customers- you should be "finding more of these".
This is by far the most underrated GTM hack I have come across.
There are few lookalike tools you can try- Ocean, Jesse (my product).
While using these tools, you should be able to find out why certain new customers were surfaced- what were the logic behind these new suggestions, and then run a focussed outbound/ABM campaign on those list.

We run an automated pipeline that drafts articles for our product. During our first test attempts we let the model do almost everything, including the mechanical bits: fixing dashes and quotes, tracking which stage each article was in, creating SEO json, naming image files etc. It worked, but the quality was uneven, sometimes the model would miss some things, and, of course, it was rather expensive in terms of tokens.
Then we changed our approach and started treating AI like a creative employee and providing it with "software" (python scripts) to help with any mechanical tasks that could be automated by code. The model only does the part that actually needs intelligence and creativity now.
And honestly, the result surprised me - quality went up, because we now let it focus on what it's actually good at. As a pleasant bonus - the costs of running the pipeline dropped too. One of the first things we scripted was stripping the em-dashes the model loves to add but my co-founder has an allergy for

How do you improve the quality of your AI results, especially automated pipelines?

before my last two launches I wasted weeks building before checking who else was in the space. don t be me. here s the 30-min competitor check I do now, all free tools:

1. search PH archives (5 min)

search your keywords on Product Hunt. sort by launch date. note how the top 5 positioned themselves the gaps in their taglines are your opening.

I was prepping my YC application. I wanted to know: has anyone already done this idea?

YC's search gave me nothing useful. So I spent a weekend scraping their Algolia API, built a local database, ran embeddings against my pitch... and found 3 companies that had tried it.

After nearly 11 hours, Adomate is still holding the #1 Product of the Day spot on Product Hunt!

A huge thank you to everyone who has supported us so far. Your upvotes, comments, and feedback have helped us stay on top.

If you haven't supported Adomate yet, we'd really appreciate your help. Please consider giving us an upvote and sharing your feedback on Product Hunt.

https://www.producthunt.com/prod...

Hey everybody! I am very grateful with what Jam-Pod made on the launch day, I didn't expect this at all! And a great part of it was for your comments and feedbacks. You were great, and I took your comments very seriously. I am already working to improve Jam-Pod with these new ideas. They will be (in part) in the new release of the app in the store, hopefully tomorrow. That said I would like to give back what received. The app will be free to you, who supported me during the launch. So if interested write me and I will send a promotional code by email. :)

Hey all ahead of our Aug 2 relaunch, I'd rather be useful than hypey. Here's the honest map: what we test, what we don't (yet), what languages it works with, and where we're going.

The failures we test for (the "it passed, then broke in prod" stuff):

• Double-processing the same webhook arrives twice; do you charge the customer twice?

• Out-of-order / late events a "canceled" and a stale "active" land in the wrong order; does a canceled account come back to life? (live for Paddle today)

• Sad paths card declined, payment failed, thing-not-found; does your code handle it, or quietly mark it "done"?

• Rate limits the API throttles you (429); do you back off, or silently drop data?

• Wrong-shape responses the API returns a field you didn't expect or renamed; does your code break downstream?

• Auth slips bad/expired key, or a read-only key doing writes; caught or not?

• Fake / replayed webhooks unsigned, tampered, or old signed events; rejected?

• Slow + flaky delivery delays and dropped webhooks.

Every run hands you a receipt: the failure reproduced, then gone after the fix.

Most knowledge tools put the connection work on you. Tag this. Link that. File it in the right folder. Organize it or lose it.

But the whole point of using AI is to spend less time on busywork, not more.

Second Brain builds its knowledge graph automatically. When you save a memory, the system extracts the people, projects, decisions, and concepts mentioned. It scans the existing graph for related entries and creates links where it finds meaningful overlap.

A few examples of what this surfaces in practice:

I ve spent years working on B2B customer acquisition for products moving from early traction to real scale. We tested every channel, built lightweight systems for volume outreach and partnerships, ran hundreds of experiments, and eventually created repeatable processes that a small team could run without constant firefighting.

Distribution is the #1 bottleneck you ll hit. Features get copied. Messaging gets borrowed. What actually compounds is a clear system for identifying the right accounts, testing quickly, and turning early signals into consistent pipeline.

By the end of this you ll know:

- What each major acquisition channel actually buys you (and why most teams misuse them)

Hi Product Hunt

Thank you again for the incredible support and thoughtful questions.

I guess that when you're pre-revenue, AI tools and the occasional freelancer are often more than enough to get an MVP out the door and test the waters.

But eventually, every growing product hits an inflection point where "good enough" visuals and quick-and-dirty copy start holding back growth. To build real authority and category leadership, a curated identity becomes important.

We recently joined @appsumo Radar , which got me thinking about the role AppSumo plays for early-stage SaaS products after a Product Hunt launch.

My impression is that it's a great opportunity to connect with engaged early adopters who are willing to explore new products, provide honest feedback, and help shape the roadmap while also becoming early customers.

I'm curious how other founders see it.

If you've launched on AppSumo, what was your experience?

Everyone told us the AI browser extension space was crowded.

They were right. It's crowded with half-products.

Most do one trick, summarize a page, manage your tabs, maybe fill a form. That's it. You still need 5 other tools to actually get work done.

The more AI tools I used, the stranger their memory systems started to feel.

Claude knew one part of my life. ChatGPT knew another. Cursor understood a project until I switched tools. Every new assistant meant rebuilding context from scratch.

I'm launching an AI-powered Google Sheets add-on next week that extracts data into columns from website URLs.

I'm curious how everyone currently collects web data in spreadsheets.

Are you copying and pasting?
Using IMPORTXML?
Writing scripts?
Using another tool?

I'd love to hear your workflow and biggest pain points.

First, thank you. Thank you. Thank you! The response today has been more than we expected, and your comments have been sharper and more useful than any survey we could have run.

Here is what we are hearing so far, what we are building next, and where we would love your help.

What is landing

Hey everyone, Jane here from the Publora team

On June 10th, on a day when 700+ products launched and only 21 made it into Featured Publora hit #1 Product of the Day.

Hey Kalendar fam!

We've been listening to your feedback and shipping. Here's what's new:

MCP support Connect Kalendar to Founding.dev, Claude, or Cursor and manage your calendar from chat. Ask your AI agent to look up your clients and bookings, or to create, reschedule, and cancel meetings for you. Just create an API key in your settings and you're connected.

Hey everyone,

I launched Foyer here last month. It's a small app that turns ambient sound into a place. You sit in the middle of a black canvas as a point of light, and each sound is a glowing orb you can drag around yourself: a hearth, rain, a stream, a city somewhere in the distance. Pull one closer and it gets louder. Slide it to the left and it moves to your left ear. It's real binaural audio, so with headphones on it feels like you're sitting inside the room instead of listening to a track.

Udaya here, founder of PlugThis. We're #1 right now and honestly still processing that.

But upvotes aren't the point of this product. Extensions are.

So here's the thread: if you used your free builds today, post what you made. One line on what it does. Screenshot if you have one.

Weird ideas especially welcome. The stranger the prompt, the more I want to see it.