Yesterday, I came across a job posting from a specific SF company that offered Yesterday I came across a job posting from a specific SF company that offered a salary of 250k 1M (including equity), but realistically, I don't think they have that money; they're just grinding to satisfy investors and succumb to too much hustle culture.
Requirement: be available on-site from 9 AM to 9 PM 6 days a week in the office (and I bet even Sunday would be dedicated to meeting some team members in "free time"). In addition, they were willing to hire those who would relocate to SF.
I often find myself pushed forward by various challenges. When time is tight and work pressure is intense, do you have any good work-life balance suggestions?
There's so much out there on HOW to launch here on PH, but not so much of a discussion on whether it's worth the effort. After our launch where we took #1 product of the day, I sat down to run an analysis on whether it was worth it or not. Put all our findings here:
https://www.alpeaudio.com/post/i... Curious to hear your thoughts on this topic!
Product Hunt was created specifically to showcase what you do. But let s face it, with the progress of AI, there are more and more products and you don t have time to test them all (respect to @gabe , who does this job brilliantly).
I noticed that as my following grew throughout social media, more people contacted me wanting to test products. Of course, I don t have room for everyone, and what s even more shocking is that to get to me, they want to compensate me for testing.
Lately, I ve been looking closely at how independent builders and small teams are managing AI knowledge bases. It feels like the default "industry standard" is to immediately reach for a complex RAG pipeline and a heavy, paid Vector Database.
But I'm starting to wonder if we are over-engineering this for 90% of standard use cases.
Vector DBs are incredibly powerful for massive scale, but for smaller or non-massive datasets, they can be expensive, complex to query, and act as complete black boxes. If a search returns a weird chunk, diagnosing it is often a nightmare.
