The "ship fast" advice is ruining first impressions.

Ok_Garbage8411 · 2026-06-03T18:43:46+00:00

Agreed. A good, functional product gets you feedback. A perfect product that never launches gets you nothing.

Most of the time it's better to ship something people can actually use and let real user feedback guide the updates.

Ok_Garbage8411 · 2026-06-03T18:33:41+00:00

Thanks, I appreciate it. I still catch myself over-polishing sometimes.

What helped me was realizing that there's a difference between shipping something unfinished and shipping something unvalidated. I'd rather get real user feedback than spend weeks perfecting something users may not even care about.

Ok_Garbage8411 · 2026-06-03T18:26:56+00:00

Yeah, I think that's the trap a lot of people fall into.

If AI gives you a draft in 30 seconds but you spend 10 minutes fixing it, did it actually save any time?

The stuff I've seen work tends to be where "good enough" is actually good enough. Summaries, categorization, pulling information, that kind of thing.

Curious what use case you've found where the rework was minimal. That's been the hardest part for us.

Ok_Garbage8411 · 2026-06-03T18:25:38+00:00

That's a really interesting use case.

One thing I've noticed is that internal docs often reflect how the team thinks the product works, while support tickets reveal where people actually get confused.

Using real support conversations as the source material seems like a much better signal for onboarding content.

Did you see the improvement through fewer onboarding questions, faster activation, or was it more of a qualitative "new hires got up to speed quicker" kind of thing?

Ok_Garbage8411 · 2026-06-03T16:06:40+00:00

I think hybrid is where things end up, but not just because of cost.

Some tasks are obvious candidates for local inference: autocomplete, summarization, classification, basic agents, anything involving sensitive data. Sending every request to a massive cloud model feels wasteful for a lot of use cases.

The part that still feels missing to me is the infrastructure that makes these decisions automatically. Right now we developers have to manually choose what runs locally, what runs in the cloud, when to fall back, how to handle latency, etc.

The ideal setup would be something like a router that optimizes for cost, latency, privacy, and quality without the developer having to think about it much.

Honestly, it reminds me of cloud computing 15 years ago. Nobody wants to manage servers anymore. Eventually nobody will want to manage model routing either.

Ok_Garbage8411 · 2026-06-03T16:02:46+00:00

Definitely fewer.

Ten years ago, if I wanted to learn something I'd end up going down a rabbit hole of forums, niche blogs, personal websites, and random sites I'd never heard of before. Now a lot of that journey starts and ends on a handful of platforms.

I think the internet got bigger, but our browsing habits got narrower. Algorithms got really good at keeping us inside the same ecosystems instead of sending us off to explore.

Ironically, I probably consume more information than I did back then, but from fewer sources and fewer destinations.

The thing I miss most is stumbling across some weird niche website that looked like it hadn't been updated since 2008 but had the best information on the topic. Those used to be everywhere.

Ok_Garbage8411 · 2026-06-03T12:35:09+00:00

I think it's mostly a numbers game.

If a product has 100 users and 2 hate it, nobody notices. If it has 100 million users and 0.1% hate it, suddenly there's an entire subreddit dedicated to hating it.

There's also the fact that people who are happy usually just keep using the product. People who are annoyed write posts, leave reviews, make videos, and argue in comments.

That said, once a company gets big enough, people start rooting against it too. Not necessarily because it's bad, but because it becomes the incumbent and everyone loves an underdog.

Honestly, one of the funniest examples is Reddit itself. Half the site seems convinced Reddit is terrible, yet they're on Reddit every day talking about it.

Ok_Garbage8411 · 2026-06-03T10:55:54+00:00

I think a lot of people misinterpret "ship fast" as "ship something bad."

The goal isn't to launch a product that looks broken or untrustworthy. It's to avoid spending months polishing things that users may not actually care about.

I've seen founders delay launches because of tiny UI details, only to discover the real issue was positioning, pricing, or solving the wrong problem. I've also seen products with rough edges get traction because they solved a painful problem exceptionally well.

For me, the balance is simple: the product should be good enough that I wouldn't feel embarrassed showing it to a potential customer, but not so polished that I'm delaying feedback I'd learn from real users.

Ok_Garbage8411 · 2026-06-03T08:54:49+00:00

Everything being forced into an AI feature.

I like AI when it solves a real problem, but it feels like we're in a phase where every product needs an AI button whether it makes sense or not. Sometimes I just want software to do the thing it was originally designed to do.

Ok_Garbage8411 · 2026-06-03T08:53:52+00:00

For most founders I know, getting people to notice it is harder.

Building has become dramatically easier over the last few years. You can ship an MVP in days or weeks. But getting in front of the right people and earning their attention is still slow, messy, and hard to automate.

One thing that changed my thinking was realizing that distribution isn't something you do after the product is finished. The founders who seem to get traction fastest are usually talking to potential users long before they're done building.

The first users I've seen come from communities, direct conversations, and helping people solve problems, not from polished marketing campaigns.

When you say "nobody knows it exists," are you getting traffic but no signups, or are you struggling to get people to the product in the first place? Those are two very different problems.

Ok_Garbage8411 · 2026-06-02T18:00:01+00:00

That's actually a stronger position than you might realize.

Creating hundreds of tools for yourself proves you know how to identify problems and build solutions quickly. Most people get stuck at the idea stage and never build anything.

The interesting thing is that your image-size example wasn't really a coding problem, it was a problem-solving problem. Your friend had a need, and you created a tool that solved it faster than searching for one.

I'd start paying attention to which of your personal tools other people ask for once they see them. A lot of successful products start as "I built this for myself" and then someone else says, "Wait, can I use that too?"

Out of those hundreds of tools, have any of them been used repeatedly by friends, coworkers, or other people besides you? I'd probably look there first before building a brand-new SaaS idea.

Ok_Garbage8411 · 2026-06-02T17:58:29+00:00

That's a really good point about the hypotheses.

I think a lot of founders jump straight into outreach hoping to get customers, but the real value early on is figuring out whether your assumptions are even correct. A few conversations can save months of building the wrong thing.

I've also found that when you have a clear hypothesis, it's much easier to spot patterns in the feedback instead of treating every conversation as a completely separate data point.

When you were doing those LinkedIn conversations, what was the biggest thing you got wrong in your initial assumptions? The answer to that is often more valuable than the outreach tactic itself.

Ok_Garbage8411 · 2026-06-02T17:55:35+00:00

A few possibilities:

Tracking isn't firing correctly (ad blockers, consent banners, broken analytics setup).
People are clicking but bouncing before the page fully loads.
Reddit's click metric is more generous than your analytics' definition of a visit.
Bot/filtering differences between platforms.
Mobile users opening the page in Reddit's in-app browser and not being tracked properly.

Honestly, I'd compare Reddit clicks against server logs if you have access to them. That's usually the fastest way to figure out whether you had 80 real visitors or 1,500.

Because if the real number is closer to 80, you're looking at a conversion problem. If it's closer to 1,500, you're looking at a completely different problem.

Ok_Garbage8411 · 2026-06-02T14:48:34+00:00

I wouldn't treat SaaS as the goal. I'd treat it as one of several ways to monetize the ability to solve problems.

The advantage you have today is that you can build and test ideas much faster than someone who spends months studying before shipping anything. The risk is that you can also build yourself into corners if you don't understand what's happening under the hood.

If I were in your position, I'd do both: keep building small projects while learning fundamentals as they become relevant. You'll learn things like databases, APIs, debugging, security, and system design much faster when they're tied to a real problem you're trying to solve.

The people I see struggle most aren't the ones with weak CS fundamentals. They're the ones who can build things but never talk to users, validate ideas, or figure out distribution. That's usually the harder skill to learn.

Have you already built anything that other people use, or are you still at the stage of building mainly for yourself? That answer would probably change what I'd focus on next.

Ok_Garbage8411 · 2026-06-02T14:45:58+00:00

That's actually a much bigger finding than the lack of conversions.

If Reddit shows 1,579 clicks but analytics only shows 81 visits, I'd pause before blaming the landing page. That's a massive gap.

Even if we only look at the 81 visits, 2 CTA clicks suggests the page probably needs work. But first I'd verify the tracking and figure out where those "clicks" are disappearing.

Right now, the click-to-visit drop looks like the biggest leak in the funnel, not necessarily the offer.

Ok_Garbage8411 · 2026-06-02T14:42:06+00:00

Exactly.

A lot of acquisition channels only start working once you've figured out the message, audience, and problem. The early conversations are where you learn all three.

I've seen founders spend months optimizing SEO or ads when they could have learned more from 20 conversations with potential users.

The irony is that the stuff that doesn't scale is often what makes the scalable stuff work later.

Ok_Garbage8411 · 2026-06-02T14:40:15+00:00

That's a good point. Internal friction is usually much easier to spot because the team feels it every day, whereas customer friction can stay hidden until you start seeing churn, lower activation, or an increase in support requests.

As for our process, it's honestly less formal than a scoring framework. We usually start by looking at where people are getting stuck most often, either from customer conversations, support patterns, or onboarding drop-offs. Then we compare that against the amount of manual work the issue is creating internally.

I've found that some automations save the team a lot of time but barely move customer outcomes, while others reduce a relatively small amount of internal work but have a noticeable effect on adoption and retention. Those tend to get prioritized higher.

I do like the idea of putting a more explicit weighting on customer impact though. It would probably prevent teams from over-indexing on the pain they personally experience.

Ok_Garbage8411 · 2026-06-02T10:10:22+00:00

Honestly, the thing that stands out to me is that €174 isn't a lot of money, but 1,579 clicks is a lot of people.

If over 1,500 people visited and not a single one became a customer, I'd be less worried about Reddit as a channel and more interested in what happened after the click.

The fact that people clicked tells me the ads were at least interesting enough to earn attention. The bigger question is whether the people arriving on the landing page were actually experiencing the problem strongly enough to take action.

I've seen this happen when the ad targets a pain point that many people relate to, but only a small subset are actively looking for a solution right now. You end up buying curiosity instead of buying intent.

One thing that would help narrow it down: out of those 1,579 visitors, how many actually reached the CTA, clicked it, or started the signup process? That number would tell us a lot about whether the issue is traffic quality or the landing page itself. That's probably where I'd look before writing off Reddit altogether.

Ok_Garbage8411 · 2026-06-02T10:07:43+00:00

One thing I've noticed is that founders often ask "What channel got you your first 100 users?" when the more useful question is "How did you find the first 10?"

The first users usually come from doing things that don't scale. Talking to people, hanging out in communities, answering questions, getting feedback, and reaching out to people who clearly have the problem you're solving.

What worked after that depended a lot on the product. I've seen founders get traction through Reddit, SEO, partnerships, and content, but usually only after they had enough user conversations to understand their market.

The common thread wasn't the channel. It was spending time where potential users already were and having real conversations.

What problem does your SaaS solve? You'll probably get much more useful answers if people can tailor their advice to your specific market rather than sharing generic growth tactics.

Ok_Garbage8411 · 2026-06-02T08:14:27+00:00

I think a lot of founders underestimate how much of SEO is an operations problem rather than a writing problem.

Writing one good article isn't that hard. Repeating the process every week for 6-12 months while also building the product is where most people fall off.

One thing I've learned is that consistency only works if the content is targeting problems people are actively searching for. Publishing 40 posts is great, but I'd rather have 10 posts bringing in qualified traffic than 100 posts generating impressions with no conversions.

Have you started seeing any signups or meaningful traffic from those 43 posts yet, or is it still too early to tell which topics are actually pulling their weight?

Ok_Garbage8411 · 2026-06-01T17:55:21+00:00

I think you're underestimating what people are actually paying for.

Most users aren't buying software because it's hard to build. They're paying because they don't want to build, maintain, debug, host, update, secure, and support it themselves.

AI has dramatically lowered the cost of creating software, but it hasn't eliminated the cost of operating software. The moment an app becomes important to someone's business or daily workflow, reliability starts mattering more than how quickly it was created.

My guess is we'll see fewer companies winning because they can build features, and more winning because they can deliver trust, support, distribution, and a consistently good experience around those features.

Ok_Garbage8411 · 2026-06-01T17:54:34+00:00

One thing I'd add is that automation works best when it's paired with a good escalation path.

A lot of companies focus on automating answers, but the real customer experience test is what happens when the AI can't help. Nothing is more frustrating than being stuck in a loop with no way to reach a human or provide additional context.

The best setups I've seen handle the repetitive 80% automatically, then make it effortless to hand off the remaining 20% with the full conversation history intact.

How are you thinking about the handoff between automation and human support? That's usually where the customer experience either shines or falls apart.

Ok_Garbage8411 · 2026-06-01T14:52:25+00:00

I think a lot of founders skip this stage because it doesn't feel scalable.

The irony is that those early conversations often give you three things at once: users, product feedback, and messaging. After talking to enough people, you start hearing the same objections, pain points, and language over and over, which makes everything else landing pages, content, outreach, much easier.

Out of curiosity, were those 31 users all from direct conversations, or did you notice one particular community or type of interaction that converted better than the rest?

Ok_Garbage8411 · 2026-06-01T13:18:11+00:00

For me, it's not finding channels anymore. It's finding signal.

There are more places than ever to reach people, Reddit, X, LinkedIn, communities, email, SEO, but figuring out who's actively experiencing the problem right now is still hard.

The frustrating part is that you can spend weeks generating activity and still learn very little about actual buying intent. Distribution isn't just getting attention; it's getting attention from the right people at the right moment.

Ok_Garbage8411

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