Hey PH I'm a solo dev. I built Cadence because editing tutorials always took me longer than recording them. You record a guide as short steps (60s cap each), and it auto-stitches them into one clean MP4 titles, chapters, no timeline. Mac app, one-time price.
Launching here June 21 follow Cadence to get notified In the meantime I'd genuinely love feedback: what makes you abandon a tutorial halfway? That's the problem I'm trying to kill. cadence.dashovia.app
For the 5th time in 28 months, I ve just submitted our application to Y Combinator.
Over the last two years of building VertoX, we ve kept shipping regardless of external validation. We are building with or without YC. But let s be real, YC is an insane lever. The network, the founders, the speed, it just accelerates everything.
Honestly, this time feels completely different. We ve grown, our tech is way sharper, and the foundation is stronger than ever. I have a really good gut feeling about this batch.
If you ve gone through YC or made it to the interview stage: what were the most unexpected or brutal questions they hit you with? What should I be relentlessly preparing for right now?
The biggest damage actually happens every single day.
UV rays fade your paint. Dust creates micro-scratches. Bird droppings can permanently damage the clear coat. Tree sap is difficult to remove. Unexpected rain leaves water spots.
We built CoverX to protect cars from everyday damage not just bad weather.
Quick context: I run Reporting SaaS, a Shopify app that automatically emails merchants their sales/order/product reports, so they don't have to log into Shopify Analytics manually every week.
A couple weeks ago I posted an honest recap on Indie Hackers fixed a bunch of App Store listing issues, built some SEO content, and admitted installs hadn't moved yet. Pretty unglamorous stuff.
One comment stuck with me more than the rest. Someone pointed out that most of my feature list was just "automation of a habit" competing with Shopify's own free analytics emails, which is a race to the bottom on price. But one feature I'd almost buried as a minor bullet point a revenue-drop alert wasn't automating anything. It was catching something. Their framing: stop selling "avoid checking manually," start selling "insurance against a bad week."
I didn't want to just nod and move on, so I actually built around it:
I m curious how people here handle vocal removal in real workflows. When you need an instrumental version of a song or audio clip, what do you usually use? Do you care more about speed, audio quality, file size, browser-based editing, or being able to use it without installing anything? I m working on a small browser-based vocal remover tool and trying to understand what actually matters to creators, video editors, and makers. Would love to hear what your current workflow looks like.
We've been running a data pipeline for about 18 months now, and one metric I keep coming back to is the real cost per successful request not just the price per GB, but the total cost including retries, failed requests, and the engineering time spent debugging.
Here's what I've learned about calculating the true cost:
1. Sticker price is only half the story
Most providers advertise a per-GB rate, but that number doesn't include the requests that fail and get retried. If your provider charges for bandwidth and you're burning bandwidth on failed requests, your effective cost per successful request can be 2 3 higher than the advertised rate.
The other day I was struggling with LinkedIn, its support, overpriced packages, and terrible UX, and thought: this can t be real. In the age of AI, there s still this massive legacy platform sitting on a pile of data, acting as a gatekeeper to the B2B world, yet outdated as hell.
