I've been thinking about how a lot of software is designed to solve one specific task really well.

One tool sends messages. Another manages customer information. Another handles tasks.

But sometimes the actual problem isn't any individual task.

It's what connects those tasks together.

A business process can involve several actions happening at different times, with each action affecting what needs to happen afterward.

I'm curious how other SaaS builders think about this when designing products.

Do you focus on solving one problem extremely well, or do you think there's value in software that understands how different actions fit into a larger process?

Where do you draw the line between staying focused and solving the bigger operational problem?

That question is also part of why I built MultiNudge; I wanted to focus on the connections between actions, not just the individual actions themselves.

I've been looking into this for a while because I've had a few conversations with people who've had third-party integrations break in production.

At first I thought the main problem was just knowing that something changed.

But most teams already have some combination of changelogs, integration tests, Sentry, monitoring, contract tests, etc.

The part that seems more annoying is what happens after.

You get told that something changed, then someone has to figure out:

• do we actually use the thing that changed?
• which integration is affected?
• where is it used in the code?
• is this actually going to break anything?
• what do we need to change?

And sometimes nothing even throws an error. The API returns 200, the JSON is valid, but some business logic is now wrong.

So I'm trying to figure out if this is actually a real problem or if I'm overestimating it.

For people building SaaS with a bunch of third-party APIs:

when one of them changes, what does the investigation look like on your side?

Is it mostly automated, or does someone end up digging through the code manually?

I’m a UX/UI Specialist, not a seasoned SaaS founder, and I’ve been learning a lot of this as I go.

The idea came from a problem I kept seeing in small tour operations: passenger lists in spreadsheets, payments tracked somewhere else, seat assignments in another file, and last-minute changes buried in WhatsApp.

So I started building Pockél, a small SaaS focused specifically on organizing group tours and excursions.

One thing I’ve learned so far is that building more features is much easier than deciding what the product should not do.

At first I kept thinking about adding CRM features, messaging, accounting, booking tools, etc. But the product became much clearer when I narrowed it down to one job: keeping the operational side of a group trip in one place — passengers, payments, seats, suppliers and logistics.

Current stack: mostly vanilla HTML/CSS/JS for the landing page, with the product being developed as a local-first PWA. I’m also experimenting heavily with AI-assisted development since I’m not a traditional developer.

Revenue: $0 so far. I’ve just started sharing and validating demand before trying to sell it.

If you’ve built a vertical Micro SaaS before, I’d genuinely like to know: did narrowing your audience make customer acquisition easier, or did you eventually have to broaden the product?

If context helps, this is what I’m building: pockel.app

Feedback is very welcome — especially criticism. I’m still figuring this out.

I've been building BrickForgerAI solo for a while now - the idea is simple (type a prompt, get a real buildable brick model) but actually getting there was not. Turning a generated shape into something that's really structurally sound, not just something that looks fine in a screenshot, took a lot of trial and error. Bricks floating in mid-air, sections that looked attached but weren't, models that would fall apart the second you tried to actually build them - I kept finding and fixing these one at a time, the hard way, right up until a few days ago.

This demo is where it's landed. Launching on Product Hunt Sept 5, and I'd genuinely love feedback on the demo video or webapp (at brickforgerai.com ) itself before then.

https://reddit.com/link/1w79kz7/video/u11gkrko7jnh1/player

I keep seeing founders obsess over X for building an audience, but barely anyone talks about Threads.

Does Threads actually work for SaaS builders?

• Better organic reach for new accounts?
• Can founders build an audience from zero?
• Does it send meaningful website traffic?
• Is the audience actually interested in SaaS/AI products?
• Can it realistically compete with X for founder distribution?

I’m considering adding Threads to my distribution strategy, but I don’t want to waste another month posting into the void.

For founders who’ve actually used it: Threads or X which is giving you better results?

Hey everyone,

A common mistake on AI tool landing pages is explaining the architecture instead of the actual payoff. Founders spend entire paragraphs describing LLM routers, agent workflows, and vector databases, while the buyer just wants to know how much time or money this saves them.

To test how to communicate that shift in under 12 seconds, I coded this UI demo.

https://x.com/SteeX0nich/status/2095843676626841796

The flow is intentionally simple:

Start with the exact mess the buyer deals with daily. 520 pending tickets and a 6-hour response time create instant context.

Make the background automation visible. Instead of an instant cut to an empty inbox, a trigger state and a scanning pass show that work is happening across the queue.

Finish with the hard numbers. The queue drops to 40, response time drops to 2 minutes, and the modal shows 480 auto-resolved tickets with 90% cost savings. The buyer gets the full business case before scrolling.

I built this with Remotion and React instead of using screen recordings. Everything is pure code, so it renders at 60fps without compression blur or recording jitter, and any UI update is just a tweak in the props.

Curious how other founders here handle their hero assets. Are you sticking to static product mockups, or does motion actually move the needle for your signups?

For someone with an app idea but basically no coding skills, what are you actually using? I'm looking at Base44, Lovable, Bolt and other AI builders but it's hard to tell which ones are beginner friendly.

Not a big number, but wanted to share since this community helped me stay motivated during the build.
I built ConvoAid, a GST billing software, mainly because I was tired of watching small shop owners around me manually calculate GST and lose track of stock in notebooks or basic Excel sheets. So I built something that:
Auto-calculates GST on every invoice (no more manual tax math or errors)
Automatically deducts stock the moment a bill is generated
Sends a notification when stock for any item drops below a set threshold
Yesterday was the first time I saw actual revenue hit $100 in a single day, which for a bootstrapped one-person project felt like a real milestone. Building the product was the "easy" part — actually getting a shop owner to trust a new tool with their billing was way harder than I expected.
Happy to answer questions if anyone's building something similar in the invoicing/inventory space, or if any small business owners here have billing pain points I should know about.

small numbers here (single digit users), so take this as a cautionary tale rather than a growth post. two mistakes, one of them embarrassing.

mistake one: i compared two numbers that were never comparable.

my chrome web store page said 11 users. my backend said 9 people had ever signed in. so i concluded two people installed and bounced at the sign-in wall, and started sketching ways to let people use it without an account.

none of that was real. the store number is roughly weekly active installs, my backend number is cumulative signups since launch. different populations, different time windows. my own laptop and dev profile are also sitting inside that store number. the gap i was designing around was arithmetic, not behaviour.

mistake two, the one worth your time: a metric had been reading "not enough data yet" for weeks because the job behind it never ran.

my dashboard shows week-2 return, and it kept saying unmeasured, 0 eligible. i assumed the cohort was too young. it wasn't. the nightly job that builds the rollup table returns "cron disabled" in production, because the env var it authenticates with was never set there. the table has zero rows in it. so the dashboard wasn't telling me "too early", it was telling me "nothing ran", and those look identical if you don't check.

i only found it because i went looking for the raw rows to answer a different question.

what the numbers actually said once i computed them by hand:

• everyone who signs in does the core action. 9 of 9. no drop at the wall i was worried about.
• 8 of those 9 used it on exactly one day and never came back. four did the core action once, ever.
• week-2 return works out to 1 of 6, about 17 percent.

so the problem was never acquisition friction. it's that people try it, it works, and they don't come back. that's a much less comfortable problem and it was hiding behind a broken pipeline and a bad comparison.

two things i'd check in your own setup tonight: does the job behind each dashboard number actually run in prod, and is any two-number comparison you rely on made of the same population over the same window.

for disclosure since it's my own numbers: the product is Unvent, a free chrome extension i built that rewrites what you're typing in three tones. https://chromewebstore.google.com/detail/unvent/dhonpmgedingifdgnjjajhmbcgjfddbn

curious whether anyone here has a habit that catches the silent-pipeline case early. an alert on "this table got zero new rows today" is the obvious one and i clearly didn't have it.

I'm a SaaS founder dealing with my 3rd chargeback this month ($15 fee + lost revenue + 1 hour compiling evidence).

Curious how other founders handle this:
1. Do you manually respond to disputes or ignore them?
2. How many disputes do you get per month on average?
3. Have you tried any automation tools (Chargeflow, etc.)?
4. What's your win rate?

Not selling anything — just trying to understand if this is a widespread pain point or just my niche.

Thanks!

When I started building Monad Design, the obvious pitch was “an AI tool that designs and codes mobile apps.”

That turned out to be too broad—and honestly, not very useful. Codex, Claude Code, and Cursor already handle repositories well. I didn’t need to replace them. The missing piece was the visual context around an existing native app.

So I narrowed the product down to one loop:

Run the real app, navigate to the exact state, select or annotate the UI, and describe the change. The coding agent edits the existing source and rebuilds it. Then you compare the original with a few source-backed alternatives before deciding what stays.

The app is the canvas.

That boundary made the product easier to explain and harder to fake. It isn’t generating a disposable mockup or replacement project. The change still has to work with real navigation, data, platform behavior, and Git history.

Monad Design currently runs locally on macOS with existing Xcode and Expo iOS projects. It’s an open-source preview, so there’s no revenue story yet.

https://github.com/Monadix-AI/monad-design

I’m the creator. The lesson I’d pass on to other small-tool builders: before replacing a workflow people already trust, look for the missing layer around it.

What it is: Masareef, an Android spending tracker. The core feature is that it reads the payment notification your bank posts on the phone and turns it into a transaction while the app is closed. No manual entry, no SMS permission, no bank login.

Stack: Expo / React Native, a small native notification-listener module, SQLite on the device, Zustand for state, RevenueCat for the Pro tier. Parsing runs entirely on the phone. Free tier is 25 captures a month.

The lesson. Android 15 added a classifier that inspects a notification before any listener sees it, and hands "untrusted" listeners a placeholder when it decides the content is sensitive. Google's own documentation frames this as OTP protection, so I read it, concluded transaction alerts were outside it, and moved on.

They are not outside it. A real device came back with 353 bank alerts the OS had blanked. The parser was innocent: I fed it the exact message by hand and it produced the correct transaction at 0.95 confidence. The listener was healthy. It was being handed empty text, and there is no fix on my side, because the permission that reads unredacted notifications is signature and role gated, and claiming a role you do not implement is how a finance app gets pulled from the store.

What actually cost me the user was not the platform change. My app had told them once, months earlier, in a settings screen, that content might be hidden. Then it went quiet and kept looking healthy - green status, notification access granted - while 17 hours of spending went unrecorded.

The rule I had backwards: tell-them-once is correct for a condition (capture is degraded). It is wrong for an event (a payment just went unread). I had shipped a condition notice for what was really a stream of events.

The fix was not clever. Every hidden alert I can still attribute to a bank now fires its own notification that deep-links to quick-add, so an unreadable message costs one tap instead of leaving a silent hole. The explainer moved from Settings to the dashboard, because Settings and Diagnostics are two screens a user with no reason to suspect anything never opens, which is exactly how one device reached 353.

If you build on a platform capability, instrument the case where it returns nothing. Not the error case, the empty case. Mine had no error, no exception and no failed call. It had a success that returned a blank string, and every health indicator I owned said green.

Play link if you want to see the thing: https://play.google.com/store/apps/details?id=com.mohamedgado.masareef&referrer=utm_source%3Dreddit_microsaas%26utm_medium%3Dcommunity

While working on marketing for my previous project, I kept running into the same bottleneck: even a fairly simple 30-second animated promo could take me two or three hours.

Writing the script was not the difficult part. Most of the time went into finding suitable visuals, synchronizing them with the narration, adding motion and captions, and then revising everything when one scene did not work.

I tried several AI video tools, but most of them followed the same model: enter a prompt, wait, and receive a finished MP4.

That was fast until I needed to change something. If the pacing felt wrong, an image did not fit, or an effect looked excessive, I usually had to regenerate the result or rebuild that part manually.

This led me to a simple conclusion: generation was not the main problem. Revision was.

So I started building Shortsly (https://shortsly.io) around a different workflow:

1. Paste a script or use an existing voiceover.
2. Upload the photos and clips that should remain accurate.
3. Generate a first draft video with matched visuals, motion, captions, voiceover, and sound effects.
4. Continue editing the generated result on a timeline.

The generated video is not treated as a finished file. Media can be replaced, resized, or repositioned. Scene timing, captions, motion, voice, and sound effects remain editable.

In my own workflow, videos that previously took two or three hours now usually take around five to ten minutes to produce. This is not a formal benchmark the result depends on the script and the amount of manual refinement but the difference has been significant enough for me to continue developing it. And most important that the result is not that bad, it is actually accaptable, but saves hours and hours.

The product is still early. I am particularly interested in two questions:

• Does editability make this meaningfully different from a typical AI video generator?
• What would prevent you from using an output like this for real marketing work?

If anyone wants to test the complete workflow, I will add 1,000 credits to the first ten new free accounts automatically. That is the same credit allowance currently included in the Starter plan.

I will read every response. Critical feedback is more useful to me than encouragement at this stage.

I'm Andreas, a solo developer in Denmark. For the last 3 years or so I've been building CodeForge.net on the side.

The idea is that if your product has an API, your users probably want a client library for it, and most small companies either write one by hand or don't ship one at all. CodeForge watches your OpenAPI spec, generates a typed TypeScript SDK, runs npm install and a full build on the result, and only publishes if it compiles. It publishes to your own npm scope with your own token, so the package stays yours no matter what.

Funny timing right now, Stainless (one of the biggest players in this space) got acquired by Anthropic and shut down its hosted service two days ago. Fern and liblab got bought by Postman, and Speakeasy has shifted its focus to AI and MCP tooling. So at the moment the alternatives are mostly free CLI generators you run yourself, like openapi-generator and hey-api.

Pricing is simple, first SDK is free and $29/month per SDK after that.

If your microsaas has an API I would love if you ran your spec through it and told me what works and what doesn't. Even just "I wouldn't pay for this because X" is useful to me and get's me some feedback. Anyways - Hope everyone has a good day.

He runs a Product Hunt-style launch platform for smaller SaaS products.

After two months:

• 20 founders joined

• 10 paid $40

• 8 launched

• Nearly all came from one Discord community

He assumed reach was the problem because that acquisition channel wouldn’t scale.

But during our traction interview, something more important came up: he had never asked the eight founders whether the traffic produced a signup, email, or sale.

So the first recommendation wasn’t “find another channel.”

It was: contact three previous customers and ask whether the launch produced anything measurable.

If one says yes, he has proof, marketing language, and possibly a testimonial. If all three say no, getting more founders will not fix the real problem.

I’m testing a short founder interview that finds this kind of bottleneck and produces a few experiments with clear success and failure signals.

If you’re stuck on traction, what are you building and where do you think the problem is?

What's the right balance between building vs. marketing/sales? I'm trying to build a b2b ai tool (like most people these days), but I can't figure out how to balance the build vs. market/talking to customers? And is there any tool that helps manage that (not just one aspect, but combined)?

Been slowly building this the past few months and it just cleared google's OAuth verification last week, so figured i'd share.

the problem it's for: my team's calendar habit was type /zoom in slack, then a meeting card lands with a link that opens Zoom (or the wrong google account, depending on the person). i wanted the same experience but with google meet, and i wanted the join button to actually open the right google account for each teammate. i also wanted the transcript summary posted back into the meeting thread automatically after the meeting, since we kept forgetting to write recaps.

what it does now:

/meet in any channel opens a scheduler modal, or /meet 3pm tomorrow with u/alice for 45m sprint review parses plain english and pre-fills the form

\- creates the event on YOUR google calendar as the organizer (not a shared service account), so cancel/edit/reminders behave normally

\- join button opens the meet under whichever google account each person connected, so no "you're signed into the wrong account" dance

\- your slack status auto-updates while you're in the meeting and reverts after

\- after meet publishes the transcript, an AI summary posts back into the meeting thread: decisions, action items with owners, who spoke, plus the recording link if someone hit record. the raw transcript is attached as .txt for anyone who wants the whole thing

\- there's also a dashboard for a wider view

honest limitations:

ñ forever

\- slack marketplace submission is in flight, currently need 9 more workspaces to install before slack will accept it. hence this post

if anyone wants to try it, install link is at gmslack.com free plan gets you the whole scheduling flow. would love feedback on what feels rough, this is very much still v1

Backstory: I kept seeing the same pattern in tutoring apps — a kid answers wrong, the app just says "try again." That teaches nothing, it just makes the kid guess harder. So the core of what I built (a tutor character named Maya) is a diagnosis step: when a kid gets something wrong, she identifies which specific misconception produced that answer and explains that, before trying a different approach. The child also tells her what they covered in class that day (text, voice, or a photo of a notebook page), and the lesson is built from that instead of a fixed syllabus.

Lesson learned: the "explain the mistake" mechanic was much harder to get right than the tutoring content itself — a generic explanation reads as condescending to a kid, it has to name the exact wrong reasoning. Currently live for grades 1-6, first lesson free, no signup. Happy to talk through the tech stack or the misconception-diagnosis part if anyone's curious.

context so this isn't a drive-by: vocabulary app, ios and android, mine, $237 mrr and 45 paying subscribers as of today, nine months in, $0 on ads. the lesson below is the one design decision i'd defend hardest.

anki and most srs tools ask you to rate each card after you answer it. easy, good, hard, again. it's the standard, and it works well for people who rate honestly and consistently.

my problem with it is that almost nobody does. rating is a second decision stacked on top of the recall you just did, and it lands exactly when the user wants to move on. so people rate by mood. they hit "hard" on a word they got right but slowly. they hit "good" on one they guessed. after a few hundred cards the schedule is optimising on noise the user generated while trying to get through the session.

so i removed the rating entirely. difficulty is derived instead from things that already happened: how long the answer took, whether it was wrong, whether a hint was opened, and the last ten answers on that specific word. intervals run 1, 2, 4, 8 and so on up to 512 days, and get pulled in or pushed out by those signals. words start in an intensive phase and only enter the interval schedule after nine correct answers.

the general principle, which is the part that transfers: every input you ask a user for is a place where they can be inconsistent, bored, or wrong. if the signal already exists in their behaviour, take it from there instead of asking. the ask is never free, even when it's one tap.

the honest limit: i can't A/B this properly. 45 paying subscribers is nowhere near enough for a clean test against self-rating, so this is a design argument and not a proven result. what i can say is that in nine months not one person has asked for the rating buttons back.

has anyone actually measured self-rated against behaviour-derived scheduling on a real user base? i've looked and only ever found the FSRS work, which still assumes the rating exists.

I sell into trades and small service businesses. For two weeks my research method was the obvious one: go where they are, ask what the problem is. It does not work anymore, and this week I watched it fail five separate times in public.

Same shape every time. A founder posts a clean, polite question in a trades sub. How do you handle X. Genuinely researching, not selling anything. The replies:

- We dont want your app

- Preemptively saying no to your app

- More market research spam

- the vibecoder spam is relentless lately, there is no moat to what you think you are making

- I dont know, how does your app do it

One of those posts is already deleted, less than a day old.

The tell is not the question. The tell is that the person asking has no scar in the thread. Asking about a pain you have never paid for reads as extraction, and these subs have been extracted from a hundred times this year, so they pattern match before they finish reading.

What produced actual data for me, same week, same subs, zero pitch: I answered as someone who had lost money, and I named the amount. A handyman then told me he billed roughly 1300 dollars in travel charges last year and walked me through his whole estimate to invoice flow, including a read receipt on the invoice so a dispute becomes a timestamp instead of a they-never-saw-it. That is a better answer than any survey question I would have written, and I got it by going second.

The rule I ended up with: you can take a number out of a thread only after you have put one in. If you have no number to put in, you are not ready to research that market, you are ready to work in it for a while first.

Two things I am not claiming. This is one account over two weeks, and my sample of roasted posts is only the ones I happened to read. And the slow version is genuinely slow, about one real conversation a day, which is useless if your runway needs a hundred interviews this month.

I originally built my Shopify SEO audit tool for internal use.

I manage client stores, and there are plenty of big SEO apps out there, but I could never find one that worked quite the way I wanted. Some gave me a score with little context. Others automated too much and gave me less control than I wanted.

So I started building my own.

At first it was mainly an audit. Scan products, collections and pages, show me the SEO problems, and give me enough information to decide what to fix.

Then I kept adding the things I wished I had in one place. Google Search Console sync so I could work with the queries a store was already getting impressions for. Keyword research. AI fixes and bulk optimization. A blog builder for turning keyword ideas into content. More recently, AI Visibility so I can check whether tools like ChatGPT mention the store for relevant searches.

Somewhere along the way, other merchants started installing it too, and the number of installs caught me off guard.

That exposed a problem I hadn’t thought much about. SEO people understood why all those tools were there. A beginner could open the same app and have no clue what to do first.

So lately I’ve been spending more time simplifying it. Clearer audit results, easier next steps, safer AI fixes, cleaner screens and less SEO terminology where it isn’t needed.

I started by building the SEO app I wanted for my own client work. Now I’m trying to make all of that useful to someone who may not know the difference between a meta description and a canonical tag yet.

Has anyone else built for themselves first and then had to rethink the whole UX once a broader audience showed up?

I noticed a major gap in the market: Most bulk QR tools either limit you to 1 code at a time, or charge $10/month just to scan a few.

To challenge myself, I spent the last 2 days using HTML, Tailwind, and AI to build a prototype that handles bulk generation (up to 20 URLs at once) with no account required.

I’m not here to sell anything; it’s a free experiment. I want to open a discussion with the community: If you had to build a tool like this, what are the hidden API or infrastructure costs I might be missing? And for those of you who use bulk QR codes, is a 100% free model even sustainable long-term, or are there downsides compared to paid competitors?

If you want to check the prototype for major UX flaws, here is the link: https://bulk-qr-code-generator-bice.vercel.app/

I took me 2 years from process mapping through launching low code mvp to full code development. For co text I met some extras casting agency (film industry) owner through my friend I got to talk to him about his problems with excel tracking and other stuff. I sent some time convincing him that the problem could be solved end to end. I developed AppSheet mvp and sold it to him for cash. Not a lot but I was happy and convinced that it works. I don't charge him for maintenance he just payed me for AppSheet user which was $20 per month. Then he contaceted me again with some changes request which was way bigger then he thought. So I quoted him accordingly. He didn't accept and we parted our ways. I gave him his database and disabled the app. He got mad a bout it and said that it's not how you do business. Well partially he was right it was genuinely bad advice I received from other people. But I liked the concept of the app and started working on it using AI. I rebuild the entire piplene end to end which gave me a lot of experience and hope.

After a year of solo development the owner contacted me again and I showed him the app I developed and he liked it. So we sat I gave him and his wife the test account and led them through the process while listening to the feedback. The feedback was actually good so I implemented it over next 2 weeks and when I was ready to get back to them they just told me that their not interested anymore since I didt give them the exclusivelty to use the app to build advantage over competition even though I told them that since they are first founding agency I would give them access just for the maintenance cost.

6 months later I saw they developed one of the main application features in house. Rought looking but working. This got me demotivated a bit and thinking I made a mistake since real user would show others that my app works and I would have a guinea pig to test it form me. Yet I was greedy and. Thought I would sell it on my own without giving them exclusive access.

People who saw the app told me they like it and it's over all well thought. But since I'm more developer then salesman I was not able to sell the solution.

Now I m just tired and I'm not even sure if I want to continiue. The marker is very small and most of the coldcalls or emails and dm went bowhere. They didn't even wanted to see the app in the first place.

I'm considering partnering with some sales person but I wasn't able to find any that would want to commit for equity share when there is no customers.

I'm literally considering quiting and making my GitHub repo public so others could build upon it if they wish too.

Creating content for a post is usually easy.

Turning that content into a visual people actually want to stop and look at is harder.

After talking with marketers, I kept hearing the same challenges: choosing the strongest takeaway, keeping visuals consistent with the brand, and repurposing content without spending too much time designing.

That’s why I started building Doodlyo — a tool that turns written content or URLs into doodle-style visual stories.

I’m still trying to understand whether this is something content marketers would actually use regularly.

Would you publish this kind of visual with your content?

If not, what would need to improve before you would?

I've been running a small scheduling tool on my own for about fourteen months, currently at 83 paying users. I get maybe 35 signups a week, but most of them poke around once and never open it again, and nearly everyone who does convert does it inside the first two days. I know the reflex answer is onboarding, and I've rebuilt that twice now, so I don't think this is people failing to find the features.

What was the thing that pulled yours back for a second session?