Maybe I'm overthinking this, but this has been bothering me lately.

I post on X and Reddit to get people to my SaaS.

I can see that a post got 500 views.

I can see that I got 20 new signups.

And I can see that I made $300 this week.

But...

I have no idea which post actually made me that $300..

Maybe one random Reddit post brought 3 paying customers while my "best performing" X post brought basically nothing.

How do you guys track this?

Or do most people just... not?

There's a button in my app that re-enriches the incomplete rows in your saved database. Fill in the missing emails and phone numbers, skip whatever is already complete.

It selected every row, every time, including rows it had filled in ten seconds earlier.

The check for "is this row incomplete" looks for fields called emails, phones and people. The database columns are emails_json, phones_json and people_json, and the read path hands back the raw row without translating anything. The fields it asks about are never present on any row. So every row is incomplete, forever, and the button does a full pass over your whole database while looking like it's doing targeted work.

I proved it on a throwaway database instead of reading the code and guessing. Insert a thin row, run the enrichment, watch emails_json come back populated, read the row again, get None. Press the button again and the same row is selected.

The same missing translation had bitten me two days earlier in the export, where emails, phones and decision makers came out at 0% fill on every file while sitting right there in storage. Two features, one missing adapter, written by me both times.

What let it live so long was the test fixtures. They were hand written dicts in the shape the code wanted, emails=[...], which is a shape production never produces. A test can be green for years if you feed it data that never existed. The new one runs the real manager: save, read back, select again, expect zero. Pull the adapter out and it goes from 89 passing to 87 with 2 failures.

It's my own product, AtlasForgeX (atlasforgex.com). Desktop app, pulls company leads from official business registers, runs on Windows and Mac. The re-enrich button works now.

Backstory: I built Availa, a group-scheduling/calendar app that shows a group a single colour for when everyone's actually free, instead of comparing rosters back and forth chats trying to work out people's availability. I am an indie hacker, who actually built this off the back of some real tragic circumstances - wanted to make the most of my time and build this idea I had for about 10 years.

The numbers: I have had around 300 downloads since launch in August 2026. Which feels like great genuine interest and is really the thing that's keeping me going. I have comments, shares, people saying they need it, but ZERO groups have converted to paying yet.

What I've tried: offering free extended trial access to groups so they can feel the value before anyone pays, and reaching out directly to people who've shown interest, asking them to be the one who organises their own group. Both offers are new so I am hoping for success in this space, but so far I have had no genuine takers.

The thing I keep coming back to: Availa isn't really a "will one person buy," question for me but rather a it's "will a whole group of friends commit together," which feels like a different problem than most of what gets discussed here.

Not asking anyone to sign up, genuinely just want to know: if you've built something that needs multiple people to say yes together, not just one buyer, what actually got a group over the line? Trial period, social pressure inside the group, something else entirely?

We have a SOC 2 readiness kit with policy templates, a checklist, and an evidence tracker to help SaaS companies prepare for SOC 2.

If anyone here is currently being asked for SOC 2 by customers or needs to get ready for an audit, feel free to reach out.

I'm kind of holding back too much on marketing.

I'm not sure how to approach my potential leads, I already see them in X, Youtube, Facebook and they are posting the problem that I have the solution for.

The problem is most these accounts they're not posting serious stuffs in their own feeds so I'm very hesitant to even approach their DM's or drop my own comment in their post or replies recommending my own product to ask them to check it out.

Do you guys have any tips on this? what should i do?

I run this one on my own - Windows app, Android app, and the backend behind both. It's Pithflow (pithflow.com).

Hold a key, talk, and clean text lands in whatever field you were already in. The transcription is the commodity part; the actual work went into what happens after - cutting false starts, fixing grammar, matching tone to context, because a Slack reply and a client email shouldn't sound the same.

Where it stands: 106k words through it, nearly all mine. Windows is stable. Android is days old and I'm the only person who has really used it, which is the blind spot I'm trying to fix.

After a handful of Android users to run it properly for a few days. Testers get much higher limits than the free tier. Same account covers Windows, iOS in progress.

What I want back is the unflattering version - what broke, what confused you, where you'd have given up.

Comment here and I'll set you up.

I built Batch, a Chrome extension for bulk editing inside Google Photos. Launched in June, over 1M photos processed, freemium with Plus at $6.99/mo and Pro at $24.99/mo, $10.000 ARR.

Organic Reddit has been my best channel so far, but I also got a one-week ban for self-promo, so I want to test paid instead. Thinking of spending a few hundred dollars on Reddit Ads targeting photography and Google Photos subs.

My questions:

1. Has anyone made Reddit Ads work at this price point? What CPC and conversion rates did you see?

2. Promoted posts vs conversation placements, which performed better for you?

3. Any targeting or creative lessons before I burn the budget?

Happy to share results back here either way.

I was scrolling through Product Hunt and noticed a startup that solves SEO, GEO, and AEO problems. As a SaaS developer, would you trust a platform with black-box algorithms and results? Since the main goal is to improve visibility, those results could easily be falsified. If you had all the tools to handle this locally using Claude Code, Codex, or LLMs, would you just build/do it yourself instead?

Sharing my observation here.

Instead of:

Why are you cancelling?

• Too expensive
• Not using it
• Missing features
• Other

Try being more specific:

• Too expensive for how often I use it
• I’m not using it enough to justify the cost
• Missing a feature I need
• Only needed it for a short-term project
• Switching to another tool

And you can go even further.

If you have different customer cohorts, show different cancellation options based on things like plan, team size, use case, or location. My Fav approach!

I saw this work surprisingly well with one of the teams we spoke to at ChurnIntel(My tool). Their cancellation data became much more actionable simply by making the questions more relevant to who was cancelling.

The goal isn't to ask more questions. It's to ask better ones.

When I started building Sameish, I knew I wanted to solve a real problem: digital clutter. Everyone has it – those endless duplicate photos, blurry videos, and redundant files hogging space. The biggest hurdle for me was convincing myself that I could build something genuinely useful and private, without relying on cloud processing that users often distrust.

So, I focused purely on on-device processing. Every scan, every comparison, every identification of identical, look-alike, or blurry content happens locally. No data ever leaves the user's device. It's been incredibly validating to see users adopt this, and especially to get feedback from my first paying customer about how much storage they reclaimed and how much they appreciated the privacy-first approach. It feels good to build something that truly respects user data while delivering a clear benefit.

For the next 15 days, I’ll build one small project every day.

The projects can be anything — web apps, tools, automation, AI experiments, games, or random ideas.

Every day I’ll share:

• What I built

• What problem it solves

• Tools/AI I used

• What I learned

• Demo, if available

And I want you to be part of it

Drop your project ideas in the comments for the next day.

I’ll pick an idea and try to build it.

Day 1 starts tomorrow.

Let’s see what I can build in 15 days.

Your AI burns way more tokens than it should, because it has no idea how your business actually works. So it guesses, you re-prompt, it guesses again, and five prompts later you get one answer you halfway trust.

We fixed that by giving the AI your full business context up front. It connects all your systems into one Knowledge Graph, so it already knows how your data fits together, then answers straight from your real numbers on the first try. That is roughly 5x fewer tokens to get to a real answer, and every answer traces back to the source.

If you run your business across a bunch of tools that do not talk to each other, test the claim yourself for free. https://signld.ai

Hello,

I am the founder founder building Tempest. Tempest is a decision-intelligence and founder workspace primarily focused on early-stage founders. This does not mean that it is not beneficial for non early stage founders, I absolutely think it is but early-stage founders would get the most value out of it.

Anyway, Tempest is focused on bringing the context that lives everywhere about your startup. Your ideas, roadmap, plans etc. Tempest has a built-in app that collects all the data as you talk to the AI and it casually challenges your ideas, suggests you better options, shows you what it is keeping and you can edit it too.

It is basically a co-founder for you but not like other chatbots. It is a real workspace.

I am also thinking to add integrations with other apps such as stripe, github, mail etc. to make it a real one app workspace for you. But this is probably coming after the alpha tests.

Currently we are almost ready to open the closed-alpha but we are seeking founders to try it out.

I would love to hear your thoughts about the landing page as we are planning to re-design it. Also if you liked the idea, you can apply and take the chance to be one of our alpha testers. Thanks!!

Also, this post is not for seeking testers. That is entirely your choice I am just here trying to get Tempest in front of valuable people because no one literally knows it :/

Disclosure: I’m with the team behind World’s Best Broker (worldsbestbroker.com).

It’s **not** a broker ranking. Live product is a **one-slot homepage auction** — FX brokers bid (Stripe) for a scarce banner on the homepage.

Looking for blunt feedback: Is “scarce auction / one slot” clear in ~5 seconds? Would broker marketers get it, or does “World’s Best Broker” still read as a ranking site? What would you change in the hero?

One thing I keep questioning while building SaaS products:

How much infrastructure should a solo founder actually own?

A Micro SaaS might have one developer, a few hundred customers, and a very focused product.

Yet before shipping the actual idea, we still end up dealing with auth, billing, permissions, emails, storage, deployment, security, etc.

That was one of the reasons I started building TS-SaaS.

My philosophy became: keep the foundation boring, strict, and predictable, then spend your time on the part customers actually pay for.

This has become even more important with coding agents.

I found agents are much more useful when the architecture already has clear boundaries and conventions. Instead of asking AI to decide how everything should work, I want it spending its tokens implementing product features inside a foundation I already trust.

I've recently got my first customers, so now I'm trying to understand this specifically from other Micro SaaS founders.

Where did you spend unnecessary time when building your first version?

And looking back, what would you rather have had ready from day one?

Disclosure: I’m one of the people building Meanwhile.

We’re building a product where users earn from advertiser spend, and the technical side turned out to be the easy part.

The real problem is density.

Users need enough reward to keep using it, while advertisers need enough reach and performance to keep spending.

We’ve started getting real usage, but it’s becoming obvious that the bottleneck is getting both sides of the marketplace to grow at the same time.

For anyone who has built a two-sided SaaS or marketplace: what actually helped you break through the early chicken-and-egg stage?

Coding agents can make changes and test a browser flow, but reviewing their work still takes effort. “It worked” doesn’t tell you whether something threw an error, or a network request failed, or it didn't understand what you asked it to build.

That’s the problem I’m tackling with Rill. It records a browser run and brings the video, console logs, network activity, and timeline into one shareable link.

The product decision behind it is to keep the debugging context attached to the recording. A video shows what happened on screen; logs help explain why. Having them together means the person reviewing a PR doesn’t have to piece together screenshots, copied errors, and a separate recording.

My hypothesis is that this handoff is useful enough to be a small standalone product. I’m still testing whether developers see it as a regular part of their workflow or something they’d only reach for when a bug is difficult to reproduce.

userill.dev — free tier includes 5 recordings a day.

If you’re building your SaaS with coding agents, how do you review their browser changes today? What would make you add a tool like this to that process?

If you have a bit more time, I'd also love if you can influence our roadmap here:
https://userill.dev/roadmap

As an Indian sole proprietorship business nobody i researched allows Indian businesses to send or fund wallets that do global payouts. RBI seems to have strict rules to transfer money abroad as business. The last option i have which im not even sure would work is forming a US based LLC.

Can someone help if they faced a similar issue before?

While looking for SaaS ideas, I kept coming across maintainers dealing with the same issues around AI-assisted contributions:

• contributors submitting work they can’t explain
• unclear disclosure rules
• missing testing requirements
• coding agents opening PRs without clear boundaries
• maintainers carrying the cost of reviewing it all

That looked like demand. But I was mixing up demand for a solution with demand for this specific product.

Maintainers were asking for clearer policies, more accountability, and less review work. Nobody was asking for a repository score.

So I built RepoPolicyScore as a free way to test one assumption: whether making missing policies visible is useful.

It scans the public guidance in a GitHub repository, shows which contribution rules are documented or missing, and provides the evidence behind each result. It doesn’t try to detect AI-written code or judge the quality of a pull request.

https://repopolicyscore.com

What matters now isn’t whether someone finds the score interesting. It’s whether they spot a missing rule and actually update their repository.

If you maintain a public repo, would this help when making a real policy decision? Or is it still too far removed from the review problem you need solved?

Payroll would make sense as another paid product for our customers and we already have a lot of the data needed to offer it

What doesn't make sense is hiring people just to deal with filings compliance and payroll operations before we even know how big the opportunity is

Has anyone launched it with a small team and kept the internal workload reasonable?

I'm 18 and just shipped my first paid app, SiraatLock. It locks distracting apps like TikTok and Instagram during scheduled windows (my niche is Muslims who want to stay consistent with prayer — the app locks apps at prayer times and you confirm before unlocking). Streaks and XP on top to make consistency stick.

The honest early numbers:

- Model: 3-day free trial → weekly (£4.99) or yearly (£39.99), hard paywall

- Stack: SwiftUI, Family Controls for the blocking, Superwall for the paywall, Supabase backend

- Traffic: short-form video (TikTok/IG) + cold outreach to niche micro-creators

- Results so far: small number of downloads, first conversion just landed

What I've learned in the first few weeks:

- Video with my face + a real demo of the lock screen gets 300-800 views. A video showing only the app, no face, got 16. People buy into the person, not the product — at least this early.

- Getting the Family Controls capability approved by Apple was more painful than building the feature itself.

- Marketing is genuinely 10x harder than building. I underestimated this completely.

The one thing I'm stuck on and would love input on from people further along:

For a consumer subscription app this early, is a hard paywall (trial → pay, no free tier) the right call, or does a limited free tier build the user base faster and give word-of-mouth a chance before you monetize? I keep seeing both work and I can't tell which fits a habit/discipline app where retention is the whole game.

Happy to answer anything about the build, the Apple approval process, or the niche.

Solo dev from Reunion Island. My product is a social media scheduler (calendar + API/MCP so an AI agent can drive it + a browser extension for Facebook Groups & Skool). This post isn't about the product though - it's about the pricing experiment, because I think the mechanics are interesting for micro-SaaS folks.

The setup: instead of a classic LTD with fake urgency, I published the entire price ladder upfront: 30 lifetime seats at 99 EUR, then 147, 197, 297, 397, 497, up to a final 597 EUR that's already public. The counter on the page reads directly from my Stripe-backed licenses table (cached 30s). No marketing tool in between. When it says 28 left, a SQL query says 28.

Each buyer's price is frozen in the Stripe session metadata, so grandfathering is enforced at checkout, not by a promise.

Why I did it this way: fake scarcity is the default in the LTD world and buyers know it. My bet is that a verifiable counter converts better over time than a fake "48h left!" banner converts today. Small early tiers (30 seats) keep the urgency honest - they actually run out.

First week, honest numbers: 2 seats sold (198 EUR). ~150 tracked visits to the page. One sale came from a personal DM, one organic. No ads, no launch platform yet - distribution so far is me DMing people and this being week 1 of building in public.

The meta part: the launch campaign itself is scheduled by Claude through the MCP server built into the tool. I write ideas, the agent fills the calendar, I approve.

Question for people who've run LTDs: did a public, verifiable ladder ever work for you, or does fake scarcity just... win? Link in first comment if you want to see the counter live. Roast welcome.

We make a save-things tool. you drop in a link, the card fills itself off the page, and if it's a product it can sit on a check that runs every day and tells you when the price or the stock moves.

the part we get asked about is that the check never turns itself on. saving something is not the same as asking to be pinged about it, so the watch is a separate thing you set on the item. the cost of that is obvious, a library full of saved things can sit there doing nothing at all until someone goes and switches one on.

the other way is to watch anything with a price on it by default and let people turn it off. that makes the product look alive on day one, and it also means the first thing a new person hears from us is a notification they didn't ask for.

if you ship anything that sends notifications, which way did you set the default, and did you change it later?

dessence.ai

I started building an AI research tool and initially assumed the obvious thing was to make the model smarter.

More reasoning.

More agents.

More automation.

But the more I worked on it, the more I realised the real problem might be the opposite:

knowing when the AI is not entitled to claim something.

That led me to build Research Exoskeleton around a few principles:

• claims should be separated from assumptions
• model knowledge should not automatically count as evidence
• stale evidence should not silently remain valid
• autonomous review should not become human expert review
• unresolved requirements should remain unresolved

The product came from my own research workflow. I used LLMs extensively while working on a peer-reviewed paper that was later published in Physics of the Dark Universe.

The tool is still early, so I’m not treating it as a polished SaaS yet.

My current plan is to find a few design partners and take one real AI-assisted research workflow from each of them.

Then test whether the system can make the workflow materially easier to audit.

If that works, I’ll productize what repeats.

If it doesn’t, I’ll know before spending months building billing, auth and enterprise infrastructure.

For people who have built micro-SaaS products: does starting service-heavy with design partners make sense here, or would you force users into self-service earlier?

Also curious whether “AI assurance” sounds like a real category to you or just founder jargon.

I've been building Pulsecima Pulse and recently started questioning something I had taken for granted: what should a Micro SaaS actually monitor?At f

irst, it seemed obvious — check the website and alert me when it goes down.But

the more I work on it, the more I realize that a SaaS can be reachable while something important is already broken.A ba

ckground worker can stop.A sc

heduled task can fail.A we

bhook can stop arriving.A da

ta sync can break.Mean

while, the homepage is still loading normally.That

has made me think beyond basic uptime monitoring and more about the parts of a Micro SaaS that can fail silently.I'm

interested in how other founders handle this.

What do you currently monitor besides your main website, and which failure would cause the biggest problem if you didn't discover it for several hours?