The hardest part of building in public isn’t shipping.
I thought building in public would be mostly about momentum and accountability. What I didn’t expect was how much of it would be about sitting with uncertainty. Sharing something early, watching the response (or lack of it), and trying to understand what that actually means.
Is the silence a signal? Is it timing? Is it clarity? Or is it just too early?
Learning to separate ego from signal has been harder than writing any code or shipping any feature. Most days, building in public feels less like progress updates and more like learning how to listen without overreacting.
Trending on Indie Hackers
What's the point of AI generated comments?
Why can't your target customers always find your product? - Experience sharing
The exact prompt that creates a clear, convincing sales deck
AI lighthouse - AI readiness analysis for your website
This resonates deeply. The same pattern shows up on the user side: silence doesn't always mean confusion, and engagement doesn't always mean understanding.
When users go quiet after signing up, is it because your product is confusing? Or because they're busy? Or because they got exactly what they needed and left satisfied?
The parallel is striking: as builders, we separate ego from signal by learning to read silence correctly. But we rarely extend that same nuance to our users. We assume silence = friction, when sometimes silence = clarity.
jackfranklyn's point about "one DM from the right person" hits hard. The same applies to product usage: one user who truly understands your product (even if they churn) teaches you more than 100 who signed up but never really got it.
We built Demogod (demogod.me) to help products communicate intent clearly from the start - voice-guided demos that eliminate the "is this confusion or indifference?" guessing game. But your framing made me realize: maybe the bigger challenge is accepting that some silence is healthy, not a problem to solve.
I really appreciate this perspective ,it cuts through the noise that “building in public” has to look like endless updates, tweets, or Instagram.
In my experience building private tools (not public SaaS), the hardest part isn’t shipping , it’s knowing exactly who you’re solving the problem for before you start sharing anything. Once you have clarity on who actually needs what you’re building, it becomes a targeted conversation rather than broadcasting to everyone, which makes the inevitable social side a lot more purposeful and less exhausting.
Curious if others have noticed that clarity on customer definition matters more than visibility in early stages of a product that’s meant for a small, specific audience?
Definitely the uncertainty is the scariest part of starting any SaaS, but the lack of responses at the start is totally normal, consistency stacks and compounds with time.
The hardest bit for me has been learning that most feedback comes from the wrong audience. Early on I'd get excited about engagement from people who'd never actually use what I'm building - other builders, general startup enthusiasts, etc. The silence from the people who would use it was deafening.
Now I try to pay more attention to who's engaging, not just how many. One DM from someone in my actual target market teaches me more than 50 likes from fellow indie hackers.
Still working on the ego separation though. Some days a well-timed "this looks useful" from a stranger makes my whole week. Other days I convince myself that silence means I should pivot everything.
I’ve fallen into the same trap of mistaking builder engagement for validation early on, even when those people were never going to use the product. The silence from the actual target audience is tougher, but it’s also more honest. One real DM from the right person beats a bunch of surface-level reactions.
The "separating ego from signal" framing resonates. Early on I kept reading into every like (or lack of) until I realized most engagement is just noise.
What helped me: treating silence as neutral data, not negative feedback. If no one responds, it might mean the post timing was off, the audience wasn't there, or the format didn't work — not that the idea itself is wrong.
Curious: have you found any patterns in what actually drives responses vs what falls flat? For me, posts with specific numbers or concrete learnings seem to get more traction than general reflections.
That's a good lens — specifics without chasing engagement. The balance between sharing openly and performing for metrics is tricky. I've been leaning toward "share what was genuinely surprising" as a filter.
That framing helped me too treating silence as neutral data instead of negative feedback. I’ve noticed that posts with something concrete (a specific mistake, number, or unexpected outcome) tend to spark more real responses, while general reflections often just get quiet agreement. Still trying to share specifics without chasing engagement for its own sake.