Building in public: I’m realizing most problems aren’t what they seem.

This really resonates. I’ve noticed “need more features” is often just a cleaner-sounding version of “I’m not sure the positioning is landing yet.” The painful part is you can spend weeks fixing the wrong layer of the problem. Have you found a reliable way to tell whether it’s a traffic problem, a positioning problem, or just a mild-pain problem before you build more?

Seen this play out a lot on the sales side too. Founders convince themselves they have a pipeline problem when the real issue is they haven't talked to enough people to know who actually has the problem badly enough to pay for it. Building my current company taught me that pretty quickly.

That “avoiding a hard decision” one really hit for me.

For a while I told myself my hiring problem was just “not enough candidates.” But the deeper issue was that I had no real process, which meant I also had no consistent way to evaluate people.

Blaming the pipeline was way easier than admitting that.

This resonates a lot.

I think this shows up even earlier than most people realize — at the idea stage itself.

A lot of founders don’t have a traffic or positioning problem, they have a “this isn’t a strong enough problem to begin with” problem.

Everything else becomes hard because of that.

Curious if you’ve seen that too?

This happens a lot with product metrics too.
Teams try to fix traffic or pricing when the real issue is users never actually finish the core workflow.

Thought my problem was messaging — sent 125 cold emails and got zero replies. Spent weeks rewriting copy.

Turned out the real problem was deliverability. Guessed email addresses, no domain warmup, no SPF/DKIM setup. Everything was landing in spam before anyone even saw the message.

Now building Bidexco and the lesson stuck — always diagnose before you optimise.

This hit close to home. I spent a week trying to "get more traffic" when the real issue was that my landing page headline was confusing. People were arriving and bouncing because they couldn't figure out what my tool actually does within the first few seconds.

Once I rewrote it to focus on the outcome instead of the mechanism, things shifted. Same traffic source, better conversion. The problem was never distribution — it was clarity.

Misdiagnosing bottlenecks is so easy because the surface-level symptoms always look like "not enough X." More traffic, more features, more content. But usually the real fix is smaller and more specific.

In counseling psychology there's a concept called the "presenting problem": what someone says is bringing them in vs. the actual underlying need. They almost never match. I find the same thing happens in product discovery.

With my current tool, I thought the problem was that neurodivergent people needed help organizing their thoughts about themselves. Turns out the real problem was exhaustion from having to perform and re-explain their identity to every new person in their life. The first framing points toward a journaling app. The second points toward something people can hand to others so they never have to explain themselves again.

Completely different product. The reframe only came through after enough conversations where I kept hearing: "I'm just so tired of starting over with every new person."

Built a habit tracker and spent months obsessing over the streak mechanic because I figured that's what keeps people coming back. Turns out the real problem wasn't motivation to continue. It was the guilt spiral when they broke a streak. People would miss one day and just... abandon the app entirely.

Once I reframed it as "how do I make missing a day feel okay" instead of "how do I make streaks more engaging," the whole product changed direction. Completely different onboarding, different notifications, different tone.

I think the pattern is that we tend to diagnose problems through the lens of what we already know how to build. If you're good at gamification you see a gamification problem. If you're good at UI you see a design problem. Talking to actual users is the only reliable way to break out of that loop.

This really hits home. I'm going through this exact thing right now. I assumed the problem I wanted to solve was "people don't know the best destinations to visit." But the more I talk to actual travelers and digital nomads, the more I realize the real pain isn't WHERE — it's WHEN. They already know where they want to go. The frustration is showing up at the wrong time — wrong season, peak crowds, overpriced everything — because no tool connects timing with weather, costs, and crowd data together. Completely different product than what I would've built if I hadn't started asking questions first.

Had a similar realization building Monk Mode (https://mac.monk-mode.lifestyle). I thought the problem was "people need a website blocker." Turns out most blockers already exist and people just quit them when willpower drops. The real problem was that blocking entire sites doesn't work — you still need YouTube for tutorials, X for work stuff. The painful part is the feed, not the site. So I built something that blocks feeds specifically (homepage algorithms gone, but search still works) and locks you in during focus sessions so you can't just quit. Completely different product than what I would've built if I stayed at the surface level.

This really resonates with me I am 17 years old from Kerala India building my first startup in public while standing for my board exams the biggest thing I am realizing is that the problem I thought I was solving keepings getting sharper and more specific the more I talk to real people what I thought was a simple problem turned out to have layers I never expected it what does the moment you realize your original problem assumption was wrong

this is real. I spent two months convinced the main problem coaches had was "no automated transcription." turned out the actual pain was the 45 minutes of admin after every session — the recap email, the homework followup, the invoice. transcription was just one piece of a bigger workflow they hated.

found this out by asking different questions. not "what tools do you use" but "walk me through exactly what you do the hour after a session ends." the specificity changes everything.

now the whole product is built around that workflow instead of the feature I thought they needed.

Oh man, yes. I spent a full week optimizing what I thought was a slow AI pipeline in tubespark.ai. Nobody told me the real problem - users had no idea what the feature did. They weren't even getting to the slow part. I ended up fixing the copy and adding a tooltip. That was it. Now I ask "is anyone actually hitting this?" before I open the code.

This hits close to home.

I just launched something yesterday and I'm already catching myself in this trap. Kept thinking "I need more Twitter followers" when the actual bottleneck is probably that I haven't talked to enough real users yet.

The "solving a mild problem, not a painful one" point is the scary one though. I built StoryVault to auto-archive Instagram stories because the manual screenshotting was genuinely driving me crazy every day. But I keep second-guessing: is this pain real for other people, or was I just solving my own itch?

Still figuring out how to get those honest signals faster without building more features as a distraction.

Spent months building for "anyone who wants to improve themselves." Turns out that's nobody
The real problem wasn't the product. It was that I hadn't decided who it was actually for. Everything else was just noise until I fixed that
Also solving a mild problem instead a painful one is really hard to admit. You need to be grounded to catch that

This really resonates. I'm building a visual bug reporting tool for web agencies (ReviseFlow), and I spent way too long thinking my problem was "I need more features to compete with bigger players." Kept adding things — integrations, better screenshots, console log capture — thinking that would be the differentiator.

Turns out the real problem was much simpler: I wasn't talking to enough people. I was building in a vacuum, assuming I knew what agencies needed because I used to do freelance web dev myself. When I finally started reaching out, I realized the pain wasn't about features at all — it was about how annoying the onboarding was for their clients. They didn't need 50 features, they needed one script tag and zero friction.

The "avoiding a hard decision" point hit hard too. For months I avoided the pricing conversation entirely. Kept telling myself "I'll figure it out when I have users." But that was just fear of discovering my product wasn't worth paying for. The moment I actually put a price on it and started getting honest reactions, everything got clearer — even the nos were useful.

What frameworks or habits have helped you catch these misdiagnoses earlier? I'm trying to build a routine of weekly reality checks but curious how others approach it.

I kept diagnosing 'need more traffic' as the issue. Showed the landing page to my mum. 'What does this do?' she asked. Problem located.

@Josh234 great question. From what I've seen, failed payment issues almost never surface through user complaints — customers rarely reach out to say "hey my card got declined." They just quietly lose access and disappear.

Analytics is the only reliable way to catch it, and even then most founders aren't measuring it explicitly. They see churn spike without understanding the split between voluntary (chose to cancel) and involuntary (payment failed silently).

The tell is usually: churn rate that's higher than cancel rate. If more people are churning than are actively cancelling in your data, the delta is almost always involuntary.

That asymmetry — where the signal points to growth/retention while the real leak is billing infrastructure — is what I built RecoverKit to fix. The moment you put an automated Day 1/3/7 sequence on payment failures, that invisible churn becomes visible and recoverable.

This really resonates, especially the "avoiding a hard decision" part.

When I started building, I thought my problem was "not enough users." So I focused on outreach and features. But after 30 days of dogfooding my own MVP (becoming my own first user), I realized the real issue was different.

I was tracking activity but not progress. The data showed me I was spending energy on features that ~40% of users wouldn't actually need. The real problem wasn't acquisition—it was that I hadn't yet made the core value visible enough for people to feel it.

Once I started logging my own decisions and reviewing patterns (reactive vs. proactive, needle movers vs. noise), the product direction got clearer. The hard decision wasn't more features. It was stripping away the ones that felt productive but weren't moving the needle.

Appreciate you sharing this—it's a good reminder that the surface-level metric is rarely the root cause.

Totally relate to this.
When I first started building, I thought the biggest problem was always “not enough users”.
But after talking to a few people, I realized the real issue was that I hadn’t fully understood the problem they were facing yet.
It’s easy to jump into building features before validating the actual pain point.

honestly the "avoiding a hard decision" one hit me the hardest. spent months trying to make our workspace tool work for everyone instead of just picking a lane. the moment we narrowed down to dev teams specifically, everything clicked. positioning > features every time. great post Josh

this hits hard. i spent weeks thinking my problem was "not enough features" when the real issue was that people couldn't understand what my product did within 10 seconds of landing on the page.

i was building a dev tool and kept adding more functionality thinking that would convince people. turns out i just needed a clearer headline and a 30-second demo gif. signups went up immediately after that, zero new code.

the "avoiding a hard decision" one is real too. i kept delaying picking a niche because i didn't want to say no to potential users. but trying to serve everyone meant my messaging was generic and nobody felt like it was built for them specifically.

Relatable. The one I misdiagnosed longest: churn.

I kept thinking customers were leaving because they weren't engaged enough — so I focused on features, onboarding, activation flows. Months of work.

The actual cause for a significant chunk of it: payment failures. Cards expiring, bank declines, limits hit. Stripe retries 3-4 times, then quietly cancels the subscription. The customer never meant to leave — they just didn't know there was a problem.

Once I looked at the data, roughly 30% of what I was calling churn was actually involuntary. Different problem, completely different fix (recovery emails vs. engagement loops).

The fix was much simpler than any feature I'd been building. But I'd been looking at the wrong signal the whole time.

100% been there. I spent months thinking my calorie tracking app needed more downloads, tried every acquisition channel I could think of. Turns out the real problem was retention. People downloaded it, tried it once, and bounced because the onboarding didn't communicate the core value fast enough.

Once I focused on making the first session actually useful (instead of chasing installs), the numbers started moving in the right direction. Same traffic, way better outcomes.

I think the trap is that acquisition metrics feel actionable. You can always try one more channel, run one more experiment. But the uncomfortable truth is usually that something upstream is broken and more traffic just amplifies the leak.

I had a similar experience. At first I thought the problem was low traffic, but later realized the real issue was unclear positioning and messaging. Once I improved the value proposition and first impression, conversions started improving even with the same traffic.

I’ve run into this a few times. I used to think my problem was traffic too. I kept trying different channels, SEO tweaks, social posts, etc.

But after looking closer, the real issue was that visitors didn’t immediately understand what the tool actually did or why it mattered. The positioning was fuzzy.

Once I clarified the value on the page, conversions improved even with the same traffic. That was a pretty humbling lesson.

Spent ages convinced my problem was 'not enough features.' Kept adding stuff nobody asked for because it felt productive. Turns out the real problem was I hadn't properly explained what the thing did in the first 10 seconds someone landed on it.

Rewrote the landing page copy, removed half the feature bullets, and sign-ups went up. The product didn't change at all. Just the way I talked about it.

Biggest misdiagnosis for me was with a habit tracker I built (Tiny Steps). I kept thinking the problem was feature gaps. People wanted reminders, charts, streaks, social features. So I kept building. Downloads stayed flat.

Turns out the actual problem was that I was competing on features against apps with 10x my resources, and nobody could tell from the App Store listing why mine was different. The real unlock was repositioning around the one thing that actually resonated: no streak guilt. People with ADHD kept telling me they hated how other habit apps made them feel like failures when they missed a day. That was the angle the whole time, buried in support emails I almost ignored.

Now I lead with that in everything and it clicks way more. The feature list barely changed. The story did.

This hits home. I'm building an AI tool for construction site management, and for months I was convinced the problem was "not enough features." So I kept adding more - document generation, compliance checks, audit tools. Turns out the real issue was that site managers didn't even understand what the tool did from the landing page. The positioning was completely off. Once I rewrote the homepage to speak their language (not tech jargon, but actual pain points like "stop drowning in paperwork"), signups started moving. The feature list was fine - the first impression wasn't.

I would say this is true. I also think that sometimes this is being attached to your solution/idea over what the market feedback is telling you, as an addition to the root causes you identified above.

I just posted a deep dive on the March 5th math we discussed. Would love to know if my 2.5x retry multiplier for DeepSeek V3.2 feels right to you!

The traffic vs positioning thing is so real. I spent weeks messing with my landing page thinking that was the problem. Turns out I was just talking to the wrong people the whole time. The sneaky part is that misdiagnoses feel like progress. You tweak something, a number budges, and you convince yourself you're moving. But the real stuff like positioning and who you're even building for? That's uncomfortable to revisit because there's no clean finish line.

I kept thinking I needed more traffic. Nope. People were landing, reading, and bouncing because the value wasn't clicking in the first few seconds. More traffic would've just made the leak bigger.

That's absolutely true, the customer care about your product value/solution not about your product. You need to deliver what benefit people not what you feel is benefiting you. Most styles that people waste time on, don't even matter as the proportional given value by the product.

Analytics — specifically Stripe dashboard showing invoice.payment_failed events with no follow-up action. The customers weren't complaining because most of them didn't even know the payment failed. They just quietly stopped having access, assumed something was wrong on their end, and moved on.

That silence is the most dangerous part. User complaints at least tell you something broke. Failed payments just disappear.

That's exactly why I built RecoverKit — to make the invisible visible and intercept it automatically before the customer even realizes what happened.

Very true. The more you build, the more you realize the real problem is usually different from the first idea.

I'm currently building a small tool for editing static websites and I'm constantly discovering new problems users actually care about.

Running into this right now. I'm building an iOS grammar checker on Apple's Foundation Models and kept thinking my problem was the technical implementation (I'm a backend dev learning Swift from scratch, so the obstacles are real). Spent a week on it.

Then I realized the actual blocker is device reach: Foundation Models requires Apple Intelligence, which excludes roughly 40-50% of active iPhones. All that technical work doesn't matter much if half your potential users get a "not supported" screen before seeing anything.

The real problem isn't the code. It's figuring out how to communicate the device requirement clearly enough that people self-select before downloading, without killing conversion on everyone who can actually use the thing.

Very true. I am working on a side project and tend to over-polish and over-think different trades off. Instead, now I am trying to move faster, fail early and use idea validation / feedback as guidance and signal.

This is real. . Growing gets overwhelming sometimes . But one thing that's helped some founder...actually most is having handled inbox, scheduling, and task coordination, so they can focus without burning out and save time.

This is very real.

Something I’ve noticed with early-stage SaaS is that many “growth problems” are actually clarity problems.

Founders try to fix traffic, ads or features, but sometimes the real issue is that the product’s value isn’t immediately clear when someone lands on the page.

When that clarity improves, a lot of other problems suddenly become easier to solve.

This hit home. I spent a month thinking my problem was "not enough users" — fixed onboarding, rewrote copy, added a demo. Then I looked at the actual data: 23% of my existing users were silently churning because of failed payments, not product issues. Completely invisible.

The surface metric (user count) pointed me at acquisition. The real problem was involuntary churn happening quietly under the hood.

Once I reframed it: the problem wasn't growth, it was retention leakage. The fix was a dunning email sequence, not more traffic.

This hits close to home. I spent months convinced my problem was "not enough features" on one of my apps. Users were asking for stuff, so I kept building. Conversion didn't budge.

Turns out the real issue was onboarding. People were bouncing before they even got to use the features I was so proud of. A simple walkthrough screen did more for retention than three months of feature work.

The frustrating part is that the signals pointed to features (people literally asking for them), but the actual bottleneck was upstream. Now I try to look at where users drop off first before looking at what they're requesting.

Spot on, Josh. I hit this exact wall recently. I thought my bottleneck was 'API performance,' so I spent weeks tweaking code. Later I realized the real problem was Unit Economics. I was avoiding the hard decision of switching models because I feared a quality drop. I ended up building a 'Retry Tax' simulator to visualize the actual pivot point between GPT-4o and cheaper models like DeepSeek. It turned out the problem wasn't technical; it was a lack of clear math on my margins. Once the math was clear, the decision was easy.

I ran into something similar building Franklin Prompt Studio.

At first I thought my problem was “better prompts.”

But after working with AI more I realized the real issue was that many answers look correct but aren’t decision-ready.

Missing assumptions, missing risks, incomplete reasoning.

That shifted my thinking from “better prompts” → “better decision clarity

If I work like 16 hours a daym they all will be solved.

I know we will never achieve the Holy Grail, but we are making our projects better and better!

built QR menu for reataurants only to discover the popular POS systems has it as feature.

This resonates a lot with what I’m experiencing right now while building Gnobu.
At first I thought the biggest challenge was the technology itself — making the prototype work perfectly. But after talking to people, I’m realizing the real challenge is something deeper: helping people understand why identity infrastructure matters and where it fits in everyday systems.
The interesting shift for me was moving from “build more features” to “clarify the vision and the real problem we’re solving.”
I’m curious — have you noticed that founders often discover the real problem only after showing an early version publicly?

This resonates. We've seen the same thing in the billing/payments space. Founders think their problem is churn, but when you actually dig into their Stripe data, a chunk of what looks like churn is actually billing configuration issues - expired coupons, failed migrations, ghost subscriptions. The real problem is often hiding behind the obvious one.

This hits hard.

I’ve seen (and experienced) the same pattern. What looked like a “traffic problem” was actually a positioning problem. More visitors didn’t fix it clarity did.

A few common misdiagnoses I’ve noticed:

Thought we needed more features → actually needed a sharper core value proposition.

Thought ads weren’t working → landing page wasn’t communicating the outcome clearly.

Thought churn was pricing-related → the product wasn’t solving a painful enough problem.

Thought growth was slow because of competition → we weren’t differentiated.

The uncomfortable truth is that deeper issues usually involve messaging, focus, or saying no to something.

The hardest problems to fix are often the ones that require changing direction not adding tactics.

Would love to hear specific examples from others too those “oh… that wasn’t the real issue” moments are always revealing.

This resonates hard. I just launched my first project and spent way too much tim worried about the design being "perfect" before posting. Turns out nobody cared - people just wanted to know if the comparisons were useful.

The meta-problem thing is real too. Started building because "comparing AI tools is annoying" but the actual problem is "how do I get people to trust a random comparison site?" which is way harder to solve than just building pages.

What's been your biggest meta-problem so far? Curious what shifts you've had to make.

This resonates deeply. When building TubeSpark (tubespark.ai), I spent weeks debugging what I thought was an "AI quality issue" with script generation. Turns out the real problem was my maxTokens formula — the AI was fine, I was just cutting it off too early. The symptom and the root cause were completely different.

This really resonates with my experience building products.
I’ve also found that what initially looks like the problem like needing more traffic, more features, or better ads often turns out to be a deeper issue such as unclear positioning or solving a problem that isn’t painful enough for users.

Building in public makes this clearer because feedback exposes those root causes quickly.

It’s a good reminder that the real work is often stepping back, questioning our assumptions, and diagnosing the actual bottleneck instead of just optimizing the visible symptoms.

Thought my problem was the tool itself. Turns out it was that I was building before validating. Spent time on features nobody asked for. The real fix was talking to people first.

I’ve experienced this too.

At first I thought my problem was I need more tools on my site. So I kept adding features. But later I realized the real issue was clarity — people did not immediately understand what the site was or which tool to use first.

Once I simplified the homepage and made the main tools easier to find, usage improved more than when I added new features.

Sometimes the real problem is not growth… it is how clearly people understand what you built.

great vision

We learned that the hard way. 2 Founders and we quickly got to $150k ARR, that was 2021. We since then rebuild the software a gazillion times to "fit better for other customers". The 150k were, and still are, from a single customer and we tried to double down on that. It did not work. Now we're out here trying to pivot while staying in related field. Let's see, but one thing is crystal clear. If we would have thought about the whole business for a non-engineer pov, then we would've pivoted 4 1/2 years ago.

Interesting point, Josh. It's easy to get tunnel vision and focus on surface-level issues. Thanks for sharing!

I was the one of person who used to think you need a most unique idea to build something. An idea which doesn't exist yet. No one knows about it. And which takes 1-2 months of building with some amount of money to start (But I don't have money to spend). But now I'm building small micro-SaaS products in public and made 2 sales yesterday.

There are lots of confusions when it comes to building in public. The only way is to try fail and learn. Do experiments, fail, gather data, make predictions.

It make sense for me too.

Am belightful to meet you sir

This resonates. I'm currently validating a SaaS idea and the biggest lesson so far is that the problem I thought I was solving isn't exactly what users describe when I talk to them. The framing changes everything.

Nice project!

I'm a UI/UX and graphic designer. I help startups with landing pages, SaaS dashboards, and product UI. If you ever need design help, I'd love to collaborate.

I've done that too! Spent so much time thinking "if only I had more users," only to realize the real problem was how confusing my homepage looked. Zooming out really changes everything.

This framing is gold. I've seen the same pattern - founders treat symptoms instead of root causes. "Not enough traffic" is often actually "unclear value proposition" or "weak first impression." The hard part isn't admitting the problem exists - it's having the discipline to stop shipping features and start fixing the foundation. How do you decide when to dig deeper vs. just execute?

spent weeks thinking my problem was "not enough social media followers." the real issue was no conversion path — people were watching, visiting the profile, and had nowhere to go. the followers were never the bottleneck, the missing bridge was.

Biggest one for me was spending months adding features thinking that was the bottleneck. More integrations, more edge cases handled, more polish. But the actual problem was that people landing on the page couldn't tell what the product did within 5 seconds.

All those features were invisible if someone bounced before understanding the core value. Repositioning the landing page around the problem instead of the feature list changed everything more than any backend improvement I'd made.

The hard part is admitting you're building features because it feels productive, when the uncomfortable work is sitting with your messaging and being honest about whether it actually communicates.

This resonates.

For me recently, I thought the issue was the product itself, but the deeper bottleneck has been distribution and getting consistent feedback loops.

The people who see it are interested. The challenge is making sure the right people see it regularly.

Still figuring that part out.

I’ve noticed a similar pattern - surface problems are usually execution symptoms.

Traffic, ads, features - those are levers.

The deeper constraint is often decision clarity at the top: what are we actually committing to, and what are we explicitly not doing?

When that’s fuzzy, everything downstream looks like the bottleneck.

This is exactly it. I spent weeks thinking the problem was "AI tools are expensive." The real problem was "nobody can see how much they're actually using."

Once I reframed it as a visibility problem, TokenBar (https://www.tokenbar.site/) basically designed itself — menu bar icon, usage meters, reset countdowns. $4.99.

The lesson: the surface complaint is rarely the actual problem. Dig one layer deeper.