Our first Product Hunt launch is over. Here is what 53 points and 61 followers taught us so far
Our first Product Hunt launch gave us 53 points, 61 followers so far and something even more useful: a much clearer view of the product from the outside.
People tested parts of Techietribe AI we had become too familiar with ourselves. They questioned how it should behave, found edge cases in the AI editor, and showed us where reporting an issue still takes more effort than it should.
It also helped us better understand who we are building for. Small businesses are still at the center, but the same need exists for solopreneurs, independent professionals, and one person businesses trying to build a serious online presence without a technical team.
Some of that feedback is already shaping what we improve next.
Thank you to everyone who tested the product, asked difficult questions, shared feedback, or followed the launch. The numbers are encouraging, but knowing what deserves our attention next has been the bigger outcome for us.
For makers who have launched before, what did your first launch make you change about your product?
Replies
Dial
haven't launched a product of my own here, but I've followed enough launches now to notice the same pattern you're describing: the gap isn't usually in the core feature, it's in the edge case a founder never hits because they only ever use the product the "intended" way. The reporting-takes-more-effort-than-it-should point stood out to me specifically, that's the kind of thing that's invisible until someone hits it under real conditions, not a demo. Curious whether the edge cases people found in the AI editor were things you'd tested for and just hadn't prioritized, or genuinely new failure modes you hadn't considered at all.
@galdayan Thanks, Gal. Really appreciate the thoughtful perspective.
Most of what surfaced was already within areas we were actively testing and improving, but real users naturally interact with a product in ways that are difficult to reproduce fully before launch. A few cases helped us see where the editor could handle unexpected inputs more gracefully.
For us, that is exactly why early feedback matters. We take reliability seriously, so anything reported is reviewed, reproduced where possible, and prioritized based on its impact rather than simply treated as launch noise.
Dial
@tayyab_ahmad1 that reproduce-then-prioritize-by-impact approach is the right instinct, a lot of teams just fix whatever's loudest post-launch. good luck with the next round of changes