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I built my app in months. Marketing has been the hard part. There's no "vibe marketing" yet, but a few tools made specific jobs much easier. Here's what I used, task by task:

1. Launch video ElevenLabs

• What I used: its image, video, voice, and music tools. I made one reference image of my character and generated every scene from it, so his face stayed the same. The voices use Eleven v3 dialogue with tags like [tired] and [pause].

• Tip: avoid the AI agent editor. It used about 3x the credits I expected. Generating each piece yourself is cheaper.

2. Editing, captions and motion graphics Claude

When churn started ticking up, our immediate reflex was to poll canceling users and build whatever feature they asked for next. Unsurprisingly, it didn t move the retention needle at all.

They weren't leaving because of a missing button; they a missing button they were leaving the core loop felt like extra homework on top of their existing stack.

How do you separate genuine product gaps from fundamental friction when diagnosing why paid users slip away?

Product Hunt newsletters have taken on two different pacing schedules. The Leaderboard is on weekdays, and The Roundup comes on Sundays. I subscribe to both of them, but my reading behavior ended up being something I had not anticipated.

The Leaderboard can be read alongside my cup of coffee on weekdays and I generally remember at least one of those products by the time lunch rolls around. The Roundup is longer and so I just skim through it.

A friend who had never coded anything in their life asked me last week how to begin working with AI tools. I did not seem to have an easy answer to that, so I am trying to come up with one.

I would recommend taking a problem which you have yourself, but making it small enough to solve it within one day. Packing list, plant tracker, or bus schedule page for today only.

I m a product designer, and I m not sure what my job will look like in 3 years.

A couple of years ago, being good at Figma, understanding UX patterns, and building clean interfaces felt like a pretty solid skill set.

Now AI can generate decent-looking screens in minutes. And it s getting better at the things designers used to spend hours doing.

I don t think designers are going to disappear. But I d be lying if I said I wasn t thinking about what makes us valuable anymore.

I ve been working on SEO and website optimisation for e-commerce stores, and one thing I keep thinking about is the relationship between getting visitors to a website and helping them find what they actually need.

There are plenty of discussions about rankings, keywords, backlinks, and content. But once someone lands on a store, the experience itself matters too.

For example, a customer might search for a specific product using a term that doesn't match the wording used in the store's categories. If the navigation, filters, or product descriptions aren't clear, that customer may leave even if the website ranks well.

I m interested in how other people approach this problem, particularly on stores with large catalogues or products from multiple categories.

There is a weird kind of numbness that sets in after you ship a few projects. You get your deployment pipeline dialed in you avoid the major bugs, you get a predictable handful of users and... you just feel completely blank. You stop taking creative risks because playing it safe becomes a comfortable habit. The emotional highs and lows fade away, and suddenly work feels more like ticking boxes on a spreadsheet than creating something cool.

Did you notice your own enthusiasm flatlining as your processes got more organized?

We spend so much energy trying to remove all the stress and uncertainty from launching that we end up killing the fun along with the bugs.

I realized recently that I planned every single detail of our last release so carefully that there was zero room left for surprise or joy. Everything went right, but it felt hollow because there was no skin in the game.

Aura farming is the deliberate curation of one's image to build social capital. A calculated gym video. A well-timed silence. An aesthetic grid. It all counts.

I've been noticing how this plays out in founder culture. The "just shipped this" post with the perfectly messy desk in the background. The "here's what I learned from failing" essay that conveniently skips the part where they had a safety net. The "I work 4 hours a day" humble-brag.

It's not lying exactly. It's just... curated. Strategic. Designed to build a certain perception.

And I catch myself doing it too. Every post I write, I'm thinking about how it'll land. What it says about me. Whether it adds to the aura or subtracts from it.

We spent months setting up a private community, posting daily updates, and hosting discussions to drive organic acquisition. While the community members are super engaged, we looked at our attribution data and realized it brought in almost zero paying customers.

It made me realize there s a big difference between building a loyal audience and building a revenue channel.

How do you measure the actual ROI of community building, or is it mostly a long-term brand play for you?

During the year of our business I answered all the support emails myself. It was hard. I did not like it. Looking back it was the important thing we did and I almost handed it over too soon.

Analytics showed which buttons were pressed. The inbox showed which actions users wanted. These are two types of information. One day a user wrote: "I expected the export button to send the report to my accountant." Our button saved a file. No one would have ever noticed this difference in the funnel chart;. In the next month three other users had the same issue. We added an email button. The problem went away.

Now I keep a spreadsheet with four columns. The words that the person uses the screen they were on what they were hoping for and what actually happened. Patterns start to appear after forty entries. It is important to write down the words since they will become your landing page copy and button labels.

There is a risk. Support emails are more likely to come from customers and less likely from happy quiet ones. That feature no one ever asks about could be the thing that keeps everyone coming which is why I look at the email box along with the retention numbers not instead of them.

I used to fall into that exact loop arguing with an LLM for half an hour over a broken function pasting error logs back and forth like it was going to magically figure it out.

Total waste of time. The moment I actually drop a breakpoint or check the browser console I usually spot the stupid typo in two minutes. AI is great for scaffolding code but it's terrible at blind guessing.

I keep getting feature requests from people who want to use the product in a way I never intended. Not better versions of what it does completely different jobs. They want it to be more configurable, more customizable, more "just give me the building blocks and I'll figure it out."

Part of me wants to say yes to all of it. Flexibility widens the market, makes the product valuable to more people, and means I never have to turn a customer away. The more it can do, the harder it is to outgrow.

We keep a human in the loop for safety. It s the standard line during demos, and on paper, it makes total sense.

But in practice, human review quickly becomes the bottleneck. If someone has to check every step or approve every small update, the speed advantage vanishes. Worse, alert fatigue sets in people stop reading traces and just start blindly clicking "Approve."

When evaluating HITL setups now, my test is simple: Can someone make a confident decision in under 3 seconds?

If reviewing takes as long as doing the task manually, the agent isn't saving time it s just turning real work into an auditing job.

We promised direct, instant 24/7 founder-led support to every new customer to stand out from larger competitors. At first, customers loved the personal attention, and our retention rates were higher than ever.

But as our user base grew, this turned into a constant stress point. Our team is now overwhelmed by midnight support tickets, resolving minor edge cases, and hand-holding users through basic onboarding. As a result, zero time is left for high-level strategy, product improvements, or scaling our marketing.

It made me realize that over-servicing customers early on builds unsustainable expectations that break the moment you try to grow.

Have you ever over-indexed on manual customer support, and how did you transition to automated or self-serve systems without upsetting your early users?

People talk about churn like it's just a cold spreadsheet number, but every single cancellation email still feels like a personal rejection.

Even when you look at the exit charts and realize they just weren't a good workflow fit it's hard not to take it personally after pouring months of work into the product. You tell yourself you'll get used to it but seeing someone downgrade or leave still stings.

For those of you who have been building for years does that feeling eventually fade, or do you just learn to deal with it quietly?

We spent way too much time tweaking our dashboard metrics and digging through cancellation feedback trying to find the exact reason someone left.

Sometimes users don't even know why they churned they just realized the tool didn't become part of their daily routine. Fixing that habit loop and workflow fit is infinitely harder than writing new code or shipping flashy features.

When someone cancels on you now do you spend hours analyzing their exit reason, or do you just focus on the active users who are actually sticking around?

When users cancel their subscriptions their automated exit survey feedback is almost always polite and vague usually citing budget cuts or lack of time. Those generic answers never gave us detail to fix our actual product flaws.

We changed our email template to ask one question: "What specific task were you trying to finish today when you decided to cancel your account?" That shift in wording changed everything because it forced people to talk about a concrete workflow moment.

Of getting vague complaints about pricing we started hearing exact details about confusing button placements and slow load times. Those specific insights gave our design team direction on what to fix each week.

What phrasing works best when you ask departing users for feedback, about your product?

I've been building a SaaS with Lovable + Supabase that handles pretty sensitive stuff bank data via Open Banking, tax-related info. It's still in beta with very few users, but I want to get security right before opening it up more.

I know the basics (HTTPS, not exposing API keys in the frontend), but I'm not confident I've covered what actually matters for something handling financial/tax data.

For anyone who's dealt with this:

What would you consider the absolute minimum before letting real users connect their bank accounts to something you built solo?

We had a live support widget on our landing page, thinking instant replies would build trust and close more sales. Instead, sales calls were cluttered with basic, repetitive questions.

We removed the live chat widget and invested that effort into a clear, searchable FAQ and interactive demo video.

Qualified leads increased because users actually spent time reading the offer instead of relying on chat support to explain basic details.

It turns out immediate chat support was becoming a crutch that prevented buyers from truly understanding the product.

It takes a lot of honesty to pull the plug on something you built with so much excitement.

The hardest part isn't even the wasted effort it's letting go of that initial high when you thought the idea was going to change everything.

I usually just leave my failed repos in a hidden folder on GitHub because completely deleting them feels a bit too painful.

When you decide to move on from a side project, do you wipe the slate clean or save parts of the code for later?

We ve been debating between offering a 14 day free trial or a permanently free tier restricted features. Freemium seems great for virality, but managing storage and server costs for inactive free users gets expensive fast. On the flip side, time-boxed trials create urgency but turn away casual explorers.

For early-stage SaaS, which model helped you convert high-intent users faster without burning resources?

Our most requested feature from feedback forms took us three weeks to build and ship. We launched it with an announcement email and in app banner but less than 5% of active users have touched it since.

It was a good reminder that what users say they want in a survey often differs from what actually fits into their daily habits.

How do you validate feature requests before committing engineering time to build them?

We recently saw a bump in churn and assumed our pricing was off. But when we looked deeper at the canceled accounts, most of them were users who bought on impulse during a promo and never really fit our core use case in the first place.

It made me rethink whether price sensitivity is the real issue or if we re just attracting the wrong audience.

When your churn spikes, how do you determine if it's a value fit problem or a pricing structure issue?

Spent four months on something that was never going to work. knew it for at least two of those months. kept going anyway because quitting felt like admitting i wasted the time.

Deleted the whole repo last week. it was weirdly emotional. like closing a door on a version of myself who really believed in it.

The thing is i don't actually regret the four months. i learned more from that failure than from anything that worked. i just wish i had been honest with myself two months earlier instead of pretending.

How long do you hold on before you call it? and does it ever get easier?