When I first started cold email for my AI automation agency, I was reaching out to pretty much anyone that looked like they could “maybe” use automation. But after sending ~3500 emails and only booking 3 meetings in a month, I realised most of the people I was targeting didn’t actually need what I was selling. So after watching a few yt videos and a bit of trial and error i managed to final learn how to build a high intent lead list of businesses that where actively looking for my solution. All of a sudden my reply rates went up because I could make the emails way more relevant, and the calls became much easier because the people replying already had an active pain and were basically pre-qualified. Eventually I got to the point where I was consistently booking around 7-10 meetings a week from cold email. So I put together a quick guide for you on how to build high intent lead lists so that you can start getting more replies and having calls with better qualified leads. You can access it here, hope it helps 👍

I’m 19, not some hardcore telecom engineer, and I just built a fully custom low-latency AI voice receptionist for a client that’s nearly 90x cheaper than relying on expensive voice AI wrappers like Vapi. Honestly… did we just expose how overpriced some of these platforms are? The stack:• LiveKit• Deepgram Nova-3• Gemini 2.5 Flash• Cartesia Sonic-2• Modal• n8n• Vobiz SIP telephony This wasn’t just another AI chatbot. The system:• answers real phone calls• handles multilingual conversations• interrupts naturally• captures leads automatically• extracts emails from noisy calls• triggers backend automations• runs with extremely low latency One of the funniest problems:The AI once heard:“[email protected]” as:“[email protected]” Ended up building custom spoken-email normalization logic just to make email capture reliable over phone calls. And honestly, n8n was one of the smartest decisions in the stack. Because voice AI systems don’t stop at conversations.You eventually need:• CRM integrations• lead routing• webhooks• follow-ups• notifications• scalable workflows Feels like we’re entering a phase where more builders realize they can create custom voice AI infrastructure with better control, lower latency, and dramatically lower costs instead of depending entirely on expensive plug-and-play platforms. Curious:Do you think custom voice AI stacks will eventually replace most voice AI SaaS platforms?