No virals. No hype. Just consistency. $2,924 earned in the last 28 days, with daily revenue climbing steadily $259 in a single day. This is what happens when you pick the right niche, optimize properly, and let the system work. YouTube automation isn’t magic… it’s strategy. Want to build this kind of income stream? 👇 Check under the comments 📲 Join our Telegram channel 💬 Or DM me directly on WhatsApp..... To get started

Started slow… then the system kicked in.$9,631 in estimated revenue in just 28 days up 9,003% from the previous period.This is what happens when you focus on the right niche, high RPM content, and consistency.No hype. Just strategy and execution. If you want results like this 👇 Check under the comments 📲 Join our Telegram channel 💬 Or DM me directly on WhatsApp..... To get started

2.4M views, 113.6K watch hours, +8,000 subscribers, and $5.4K estimated revenue in just 28 days. This is what happens when the right niche, strategy, and monetization system come together. No guessing just data-driven YouTube growth. If you want results like this 👉 Check under the comments 👉 Join our Telegram channel 📥 Or DM me directly to get started

So I got a bunch of Tavily API credits for completing their course AND I wanted to show how to use a Boilerplate template to start apps. Combined this with a system (Claude Code Plugin) I've been developing the past couple of months I'm calling 'Apex Spec System' and I made a pretty awesome and good looking app. Complete open-source here: https://github.com/moshehbenavraham/tavily-app How it works: - Phases → major feature groups - Sessions → focused implementation units - Specs → detailed requirements per session - Task checklists → 15-30 items to complete - Validation gates → quality checks before moving on The result: - 15 sessions across 3 phases - FastAPI backend + React frontend + PostgreSQL - Auth, CRUD, 4 Tavily operations, save results with metadata - ~15K lines of production-ready code - 2 afternoons The key insight: AI doesn't drift when it has clear scope, explicit constraints, and traceable progress. It's not magic—it's just structured prompting at the project level. Video below! Curious if anyone else is experimenting with structured AI dev workflows such as BMAD, Github Spec Kit, etc. What's working for you?

Most of my work focuses on AI automation for clients, but at the end of the year I also created an AI-powered New Year’s greeting video for one of them. I’d like to add that I’m not a video or movie expert and I don’t have a background in this field. Still, with the help of AI tools, I was able to create the final video without any major issues: - VEO 3.1 – video clips - Nono Banana Pro – images - ElevenLabs – audio background and voice-over - CapCut – final editing and assembly The point is simple: if I can do it, you can too.And if you like the video, feel free to give it a like 👍