Hello, I want to build an agent that scrapes trending jewellery from Google and Amazon, selects the most trending items, and after human approval creates listing sheets for Amazon and Etsy. Has anyone built something like this before? I'm not sure whether it would be easier with n8n or Python.

I emailed 600+ people I hadn't spoken to in 14 years 5 of them became my first paying customers — within 60 minutes. The product isn't even publicly launched yet. Here's what happened. I spent the last year building a desktop voice AI studio as a solo dev. The interesting technical challenge: running 3 different ML inference engines entirely on-device in the same process. Native Rust backend, no Python, no Docker. The fast engine does 6x real-time on Apple Silicon. The multilingual engine handles 23 languages. Voice cloning from a short audio sample. I'm partially dyslexic — been converting text to audio since high school. That personal workaround eventually became a real product. 3 days ago, I emailed 648 customers from a marketing tool I built back in 2012. Hadn't contacted them in over a decade. Plain text emails, no design, no branding — just personal messages. 10% open rate on a stone-cold list. Some of them actually bought. Revenue before the product even launched publicly. One guy found a PDF from my old product on his hard drive and wrote me a full page about it. 14-year-old business relationships converting into customers today. Tonight it goes live. For anyone here building with AI — has anyone else run ML inference natively on desktop? The symbol collision problem between multiple inference engines was genuinely hard. Curious if others have hit this.