It's a really weird feeling having a decent number of signups on paper but having zero clue what your actual ideal customer looks like. You look at your analytics and see one group living inside your app daily while another batch signed up months ago and never came back. When you're trying to design features for two completely different types of users at the same time you end up satisfying nobody.
Looking back do you wish you had niched down right from day one or is it better to cast a wide net early on just to see who sticks around?
A successful product is often seen as one that is well-commercialized, with users willing to pay for it. But is that always the case?
Today, I came across many products that are incredibly fun and creative. It made me wonder: are there products that don t fit the conventional definition of success? Maybe some exist just to bring joy, even if users simply visit, smile, and leave.
Some might argue that if something brings value, people will naturally be willing to pay. But is that always true?
I ve been testing a safety check for an AI app by running a script of test messages many times against the model. Every run was fine until it wasn t: after a day of repeated runs, calls started failing with 429 errors, and waiting 60 seconds between retries stopped helping.
I assumed the limit was per minute. It wasn t. On the free plan for the model I use, the limits are 30 requests a minute, 1,000 requests a day, 8,000 tokens a minute and 200,000 tokens a day. I believe I hit the daily cap, because the app itself also stopped generating responses at the same time. My tests and the app share one account, so they share one budget.
What I m changing: run tests in small batches, never repeat full runs, and plan a backup provider so a quota problem doesn t become an outage.
How do you keep testing from eating your production quota? Separate accounts, a cheaper model for tests, or something else?
most audit trails answer 'did this action happen.' the ones that hold up under legal scrutiny answer something harder: 'would the reviewer who signed it still say yes if you asked them today.'
ive been calling this consent-of-record. not just reviewer id, but reviewer knew X at time of sign-off and stands behind it now. it sits above the usual forensic level (timestamp, user, action, immutable hash chain). that layer proves it happened. it doesnt prove the human is still endorsing it.
When a free user complains, it's easy to ignore. But when a long time paid customer drop a harsh cancellation note or leaves a blunt review, it hits differently even if the overall churn rate is low.
Early on, every churned user feels like a personal failure of your product vision.
As you scale, do you naturally build a thick skin toward churn feedback, or do you just learn to separate product noise from signal?
From listening to different people and their journeys, I ve realised that before they built their first profitable product, many of them failed multiple times.
Similar stories were shared by @marclou , @levelsio or @iuliia_sh to name a few.
Starting out, I found that the best connections came from showing up consistently rather than trying to network with everyone at once.
Local meetups, hackathons, demo days, and online founder communities are useful, but only when you participate. Share what you are building, ask specific questions, offer help, and follow up with the people whose work genuinely interests you.
We used to think high onboarding ratings meant we built something sticky. Turns out, getting a 5-star review during a test run doesn't mean people will actually open your app next week.
If a tool demands extra mental effort instead of sliding smoothly into a daily routine users just drift away.
How do you design your product to become an automatic part of someone's morning workflow?
