Here's the full breakdown of what it does: Runs daily on a schedule trigger. Pulls all leads from Google Sheets, filters out anyone already contacted, bad domains, wrong countries, SEO-polluted keyword entries. Passes each valid lead through a keyword cleaner that strips generic legal noise and extracts the actual practice area. Groq (Llama 3.3) writes a personalized cold email based on the specific practice area — personal injury, family law, immigration, criminal defense, whatever the lead actually does. The pain point is derived from their niche, not a fixed template. Email sent via Gmail. Thread ID saved back to the sheet. Second workflow runs at a different hour. Checks days since initial send. At day 4 — if no reply detected via Gmail Thread Get — it generates and sends follow-up 1 in the same thread. At day 9 — follow-up 2 (breakup email) with a direct Calendly link. Each step updates the sheet: Follow up 1 Sent, Follow up 2 Sent, error states handled separately. The reply detection works by checking messages.length > 1 on the thread — if someone replied, the system skips them. Tools: n8n · Groq · Gmail · Google Sheets

Now I can post😁 I am currently at the day 4 of the #AISChallenge, looking forward to start the AI OS course!! I'm going to deploy my first automation, feel free to share any general advice :)

I've spent over 500 hours inside Claude's ecosystem, so I ranked every feature from D tier all the way up to S tier based on how much each one actually changes my day-to-day knowledge work and automation. Then I walk through my top 12 in order and explain exactly why each one earned its spot. Keep in mind I'm doing a lot of automation and knowledge work, not heavy software engineering, so you'll probably disagree with some of my placements. That's the point, you value these features differently based on how you use Claude Code.

I'm new here. I am looking to connect and get inspired from you guys. What are you currently building with AI? Looking to hear about your objectives and challenges. Perhaps we are all going through the same thing.

Who is building their own personal AI OS from the ground up? I would love to talk to you about your strategies and frameworks you are using. Im getting started with mine and plan to scale it to be a whole team running itself with an orchestrator.