Three bugs from a solo-built AI app (Next.js, Supabase, Groq). None threw an error, and all of them looked fine in the logs.
Row-level security hid failed writes. Missing policies meant some writes quietly did nothing, and my code never checked. (With RLS on, an UPDATE that no policy allows touches zero rows and returns no error.) Fix: add the missing policies, and read important rows back to confirm the write happened.
A payment webhook returned 200 and upgraded nobody. The webhook arrives with no login cookie, so under RLS the update matched zero rows. Fix: use a server-side service client for that one route, verify a secret token first, and treat 0 rows updated as a failure, not a success.
Two code paths overwrote each other. Achievements were unlocked from three places with no coordination, so one request could undo another s write. Fix: a compare-and-swap write, which only updates the row if it still holds the value I read.
The common thread: a response with no error doesn t prove anything happened. Now I verify the write itself.
What s your go-to way to catch silent database failures?
I ve been wondering how people decide when to switch to a smaller model instead of just using the best one available. A bigger model might handle edge cases better, but it also costs more and takes longer to respond. For simple tasks, that trade off doesn t always seem worth it.
How are you guys approaching this?
Lately I ve been noticing something in my workflow:
Sometimes I jump into prompting AI before I fully understand the problem itself. Or I use AI to reduce friction instead of slowing down and thinking more deeply. And because the output often sounds convincing, verification can become weaker too without noticing.
Noticed so many products get top spots and hundreds of upvotes on launch day but by the end of the week nobody is talking about them.
Feels like a lot of traffic comes just to see the launch event rather than actually use the app. Having a solid group of daily active users before you launch seems to be what keeps things alive.
What do you guys do right after launch week to keep new signups coming back?
Nobody tells a job board that a position was filled, so all we can watch is the source. Our rule right now: if a source was fetched in full and an id is no longer in it, that listing gets archived, and if the fetch was partial we close nothing. There are holes on both sides. Some sources keep old posts up for months, so anything past 120 days only lands on a suspect list, because we don't trust age alone enough to close it. And one source handed us its error page instead of a job, so "Sorry, we couldn't find anything here" went live as a title until Search Console flagged it as a soft 404. If you run a directory or marketplace built on other people's data, what finally convinced you something was gone: the source, your own checks, or users reporting it?
Something I keep running into: the work gets approved, everyone's happy, and then a week later comes "can we just tweak one small thing?" Then another. None of them are big on their own, but together they quietly eat the margin on the project.
I'm curious how others deal with it:
Do you include a set number of revision rounds in the original scope, or handle each request as it comes?
Is there a point where you start quoting post-approval changes as new work, and how do you say that without souring the relationship?
Does writing down exactly what was approved (and when) actually help, or do clients just ignore it?
Would love to hear what's worked for you, and what backfired.
The App Store shows downloads, revenue, crashes. Fine as a pulse check. Not enough if you care what people do inside the app: which paywall they hit, whether they finish a session, whether a feature even got used.
For Briskly I built a small event tracker and a private dashboard for that. It works. I m just not sure it s the smartest use of solo time, or if there s a simpler setup most people use.
When I was selling things myself, the iPhone video with bad audio always beat the nice version. Just someone at a kitchen table showing the product, no lighting, no edit.
Now I'm doing marketing for a launch, and I keep catching myself making things prettier when I should be making them more real.
