Today, I built and shipped my first AI automation — a YouTube Daily Digest that runs entirely in the cloud. Every morning, it checks a YouTube channel (list that I have given) for new uploads, pulls the transcript, summarizes it with AI, and drops the digest straight into my inbox. No manual checking, no scrolling through YouTube — it just runs while I sleep. I built it with Trigger.dev for the scheduling and orchestration, OpenAI for the summarization, and Claude Code to write and debug the actual TypeScript. The build wasn't friction-free. My first live test run failed with a cryptic 429 error. Instead of guessing, Claude Code read the full stack trace, correctly diagnosed it as an OpenAI billing issue rather than a code bug, and pointed me to the exact setting to fix. One change later, the pipeline ran clean end to end — transcript in, summary out, email delivered. It's a small automation, but getting something live in the cloud, running on a schedule, with zero ongoing effort from me, feels like a real milestone. This is what "working while you sleep" actually looks like. #AIS Challenge

I spent a few hours today teaching Claude how to think like me. Not prompting it. Not chatting. Building a skill that encodes my writing voice so I never have to explain it again. Here's what I built: writing-style — encodes my personal voice so Claude never needs me to explain how I write again. Short sentences. No jargon. Metrics over vague claims. Trigger it with /writing-style LinkedIn post and it drafts in my style instantly. meta-ads-strategist — plan a full Meta campaign or audit existing ones. It pulls live data from my Meta Ads account, flags underperformers, and outputs a campaign structure with strategy doc, ad set specs, and a setup checklist. Trigger it with /meta-ads-strategist [product or goal]. One optimization I made: Added a style.md as a separate supporting file instead of cramming everything into SKILL.md. Keeps the logic clean. Update my voice rules without touching the skill itself.

Hello Everyone, Day 2 is completed Share Your Day 2 Build: Scraped Naukri.com job listings using Firecrawl MCP + Claude Code — and got a clean CSV with 20 performance marketing roles sorted by Remote / Hybrid / On-site in minutes. What I scraped: Live job search results from Naukri — job title, company, location type, experience range, date posted, and direct apply URLs. All structured, all ready to track. One thing that surprised me: Claude Code didn't just blindly scrape — it actually picked firecrawl_extract with a JSON schema over a basic scrape because it understood I needed structured data, not raw HTML. Then when the deprecated API endpoint returned zero results, it debugged itself and switched to the correct /v1/scrape format without me having to figure that out. That kind of autonomous problem-solving is what separates an AI tool from an AI agent. One use case idea: Job market intelligence for clients. If you're running LinkedIn or Google Ads for a B2B SaaS client, knowing which companies are actively hiring for specific roles tells you exactly who's in buying mode. Scrape weekly → plug into your targeting. No more guessing who to reach. If you just got the MCP server connected and ran your first scrape — that's already ahead of 90% of marketers. Share it. #AISChallenge #day2

Hello Everyone, I’ve successfully completed Day 1 of the 7-Day AIS Challenge! 🚀 Today, I built a complete Newsletter Automation using Claude Code from start to finish. It was a great learning experience and an exciting way to explore Agentic AI. Looking forward to building and sharing the next 6 projects over the coming days. Thanks to everyone in the community for the inspiration and support! 🙌

From first client agreements and first automations to AI-powered business systems and community-led breakthroughs, another strong week inside AIS+ proved that progress comes from doing. 🚀 Standout Wins of the Week inside AIS+ 👉 @Kacper Rutkiewicz crossed both 1,000 YouTube subscribers and $15K in automation revenue, sharing the journey from learning to building a real business. 👉 @Mario Chasco turned a client demo into a formal agreement, proving that consistent learning and showing up eventually creates opportunities. 👉 @Chase Coughlin shipped a complete Vendor Management System for his family farm, connecting multiple tools into a real-world automation solving an actual business problem. 👉 @Esther Adelodun , an auditor by profession, built her first working workflow and reminded everyone that technical backgrounds aren't required to start building. 👉 Michael Williamson completed his first automation just three days into the program, then immediately improved it with error notifications and monitoring. ⸻ 🎥 Super Win Spotlight | @Valli Challa Valli joined AIS+ as a first-time founder looking to better understand AI, automation, and how to build alongside other entrepreneurs. Since joining, she has: - Launched with beta users for her product - Built valuable relationships and partnerships through the community - Leveraged startup resources, credits, and training to accelerate growth - Gained confidence navigating the founder journey Her biggest takeaway? You don't have to figure everything out alone. Sometimes the most valuable resource isn't another tool, it's being surrounded by people solving similar problems and moving in the same direction. 🎥 Watch Valli's story 👇 ✨ Every successful founder starts somewhere. Inside AI Automation Society Plus, members are learning faster, building real solutions, and helping each other move forward every single week.