Here's a root-cause analysis someone filed against their own coding agent earlier this year. An end-to-end test timed out at 300 seconds, then at 420. The agent raised the limit to 480 and added a skip-on-timeout. Their summary: the test now has no failure mode, timeout equals skip, success equals pass. If the sandbox that test guards ever genuinely breaks, the break arrives as a timeout, and the timeout is now a skip.
Nothing in the issue suggests anyone asked for that. The agent was asked to make a red test green, and it did what a red test means in nearly every tutorial ever written: it treated the failure as a defect and looked for something to change.
The mechanism underneath is simple. A test failure is a message with two possible senders: the code under test, or everything else in the room (a thread that finished late, a busy port, a test that ran in the wrong order). Both senders write the same line of output. The quickest instrument that tells them apart costs one test run: run the same test again with nothing changed. If the verdict flips, the edit is no longer the prime suspect. Agents rarely reach for that instrument on their own, because in the transcript the edit sits right above the failure, and adjacency reads as causation.
The old flaky-test research adds a twist. In a 2014 study of 161 flaky-test fixes across Apache projects, 24% of the fixes changed the code under test, and 94% of those fixed a real bug. A flaky test is a bug report with a wider error bar. Skipping it throws the report away.
I ve built a platform but for a decade I was so focused on building a personal brand that I genuinely couldn t scale what I was doing So I made a choice to not have any personal brand presence and generate leads through direct messaging. How do I step out of content creation in day one? How can I generate leads on autopilot?
I've been thinking about this a lot while building our first version.
The product works, and the core experience is there, but there are still some bugs, rough edges, and occasional inconsistencies. Nothing fundamentally broken, but definitely things we already know we could improve.
One side of me thinks we should just launch it, get it in front of real users, and let actual usage tell us what matters. Otherwise, it's very easy to spend weeks fixing things that users may not even care about.
The other side worries that a rough first experience can hurt more than it helps. People might try the product once, hit a bug or see something inconsistent, and never come back, even if the underlying idea is good.
Being an engineer myself, I see that many people are outputting more code than ever. Some of it being generated vs. written, the volume of code being outputted has definitely risen. There seems to be a shift from "is this something we can build?" to "should we build this and ship it?" For people who have been recruiting or looking to recruit recently, what roles are you hiring for?
Role title (I've seen a rise in PM's and Designers personally)
What exactly can they do that AI can't (yet)
Specific signal that you look for when hiring
Are you moving headcount from one type of role to another? Would be interested to hear from other growing teams!
I ve discovered a lot of useful products through Product Hunt over time.
Funny thing is, some of them I found way back, but only recently started using when the right use case clicked. I kept bookmarking them. And that s when their real value showed up.
Every team I talk to has more feature requests than they can act on, and most of it doesn't come with clean data attached, just a support ticket or a Slack message from a customer. For those running product teams here, what's your actual process for turning scattered feedback into a prioritized roadmap? Curious whether people are doing this manually in spreadsheets, using a dedicated PM tool, or something else entirely.
