I m the founder of ProspectB2B.com, a platform I m building to help B2B teams discover, qualify, and organize prospects more efficiently.
One thing I kept seeing in B2B prospecting is that teams don t just need more leads. They need better-fit companies, cleaner data, and a faster way to know who is actually worth reaching out to.
With ProspectB2B, we re focused on making that process simpler: helping founders, sales teams, agencies, and growth teams identify relevant companies and contacts without spending hours jumping between spreadsheets, search tools, and outdated databases.
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.
A couple of days ago OpenAI released "ChatGPT apps". Almost at the same time, we allow for creating similar types of apps or "widgets" and inject into the chatbot on demand.
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.
I'm building TriageAI. A lightweight Gmail native tool that auto-classifies your support emails and drafts replies based on your tone and past responses. The problem it solves: founders waste 30-40 minutes every morning manually sorting the same support emails before doing any real work. Pricing questions, bug reports, refund requests, feature asks same categories every single day. Existing solutions are either too expensive like Intercom at $74 plus a month or too DIY like stitching together Zapier and GPT which breaks constantly. How it works: connects to Gmail via OAuth, classifies incoming emails into categories, generates draft replies. AI drafts, you approve, nothing ever sends automatically. No helpdesk migration, stays inside Gmail. Currently in early validation. $9 a month flat, no per seat pricing. Would love honest feedback from this community especially if you've felt this pain before or tried to solve it another way. What would make you actually try something like this?
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.
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.
