Hey PH, Sunil here.
Quick context: AI Velocity Pods isn't a tool or platform. It's how we structure engineering engagements, AI agents paired with senior engineers, fixed price, tied to a defined outcome instead of hourly billing.

We built it because billing by the hour meant slower work was more profitable. We wanted the opposite incentive.

Happy to answer questions about how it works, what a typical engagement looks like, or anything else.

Ask away.

Hey Product Hunt!

Tired of messy browser tabs? ArkGroups to solve that. It automatically organizes your tabs into smart, color-coded groups in real time based on rules you set. No more manual dragging, just open tabs and they sort themselves.

Hey everyone

I didn t think I d get into an accelerator. I had no team, just an idea, VertoX. And then I got accepted. So I did what felt right at the time: I started building a team. That turned out to be my mistake.

I spent around 3 months trying to build a local team. Around 8 10 people joined and left during that time. Some did very little, some did nothing, and overall progress was almost zero. At the same time, the accelerator expected fast results, but VertoX is not a simple product; you don t build real-time voice AI in a few weeks.

In the end, I didn t pass the accelerator. But I learned something important from that experience. Early decisions matter much more than you think. I was limiting myself by focusing only on local hiring, and that slowed everything down.

I kept liking the promise of AI nutrition trackers more than the actual habit.

For me the friction was not taking the photo. It was fixing bad entries, losing detail, and paying before I knew if I would stick with it.

I ve been building PageLens AI after seeing the same thing over and over again with AI-built websites and apps.
The product looks done .
But then you look properly and find the stuff that gets missed when people are shipping fast:
Missing security headers
Weak mobile CTAs
Poor accessibility basics
Broken social previews
SEO basics not set up

Analytics/consent problems
Confusing copy
No clear trust signals
Logged-in routes that nobody has properly reviewed
I don t think this is because builders are careless.
I think tools like Cursor, Lovable, Bolt, Replit and v0 have made it incredibly easy to build quickly, but most founders still need a proper launch-readiness pass before sending real users, investors or paid traffic to the site.
So I m building PageLens AI as launch QA for AI-built websites and apps.
The idea is:
1. Scan your site
2. Get a ranked report of what s hurting trust, SEO, accessibility, security, mobile UX and conversion
3. Export the fixes as Markdown for Cursor / Claude / Lovable / Bolt
4. Fix the issues
5. Re-scan and prove it improved
I d love feedback from other makers here:
Do you run any kind of launch QA checklist before sharing a new product publicly?
Or are most people just shipping and fixing issues after users notice them?
For context, this is what I m building:
https://www.pagelensai.com
Not looking for upvotes here, genuinely interested in whether other makers see this same gap.

Hello everyone,

I ve spent the last few weeks building Pika Review, a CLI tool designed to shorten the feedback loop for code audits.

While cloud-integrated review bots are great, they trigger after code is pushed. I wanted to shift that intelligence to the local terminal, acting as a gatekeeper for staged and unstaged changes before they ever reach a remote repository.

Key Capabilities

Know when to book flights, not just what they cost today

Hi! I've spent the last couple of months building a flight price prediction tool and launched it publicly today. Would love your honest feedback on it if you have 5 minutes.

https://www.producthunt.com/prod...

One of the things we re testing with Zapic is replacing parts of agency workflows.

Content, scheduling, optimization.

If an AI gave you similar results at lower cost and faster speed, would you switch?

Or is human involvement still non-negotiable?