1. Start by Experimenting With Different Styles Your first job is exploration. Use an image generator to create print-ready designs in several distinct styles, such as: Minimal line art, Decorative prints, Bold abstract patterns At this stage, quantity matters more than perfection. You’re trying to discover what resonates with buyers, not what you personally like most. 2. Test What Sells With A/B Experiments Once you have a batch of designs, start testing them. Post multiple versions (on site like TeePublic, Etsy& RedBubble) of similar designs, change titles & thumbnails while keeping the art the same, track which versions get more views, clicks, and sales This A/B testing approach helps you narrow down which ones are popular. Sometimes, a small change in wording or preview image can outperform a “better” design with weak presentation. 3. Use Print-on-Demand Marketplaces to Reduce Risk Instead of printing inventory yourself, list your designs on a print-on-demand marketplace. These platforms handle production and shipping, so you can focus on: ~ Creating designs ~ Writing strong listings ~ Improving visibility This keeps startup costs low and lets you experiment without financial pressure. 4. Optimize for Discoverability With Keywords Great art won’t sell if no one can find it. So use targeted keywords in your titles and tags. Think like a buyer: * What would someone type to find this design? 5. Stay Consistent Early revenue will most likely be small, but that's normal. Instead of chasing instant success, focus on patterns: Which styles sell repeatedly? Which keywords bring traffic? And which thumbnails get clicks? 6. Optimize and Scale Once you identify 2 or 3 top-performing designs, put your effort there. Create variations of the winning styles and refine the titles, tags, thumbnails etc. Then expand those designs across multiple products. Scaling what already works is far more effective than constantly starting from scratch. Becoming an AI art seller is mainly about testing smart. If you treat AI art like a business instead of a shortcut, you will give yourself a real shot at building steady, repeatable, passive income.

Hello Guys, I'm beginning in the automation world i've setup my whatsapp ai agent with n8n everything is just fine, test work smoothly but i'm stuck to turn my number into production, meta ask me to delete my existing whatsapp account, and i'm a bit lost at this point, would appreciate some help here please

After logging 300+hours of intensive AI use in the last six weeks, after the AI bootcamp, 40 days ago from Nov 6th, 2025, running real workflows—not demos—I made a decisive platform shift to GEMINI PRO. Below is the exact rationale, from my personal and practical use documented for transparency and repeatability at the request of some of my followers. ChatGPT — Limitations Observed in High-Intensity Use (300+ Hours of Practical Work) ✘ Inconsistent reliability during peak usage hours; frequent bottlenecks ✘ Constantly have to reopen new chats to continue an existing workflow ✘ Consistently forces the user to refresh the chat when it crashes ✘ Uses DALL·E for image generation (Inferior MCP connector) ✘ Very poor quality in image AI generation ✘ Uses report PDF generator, which is inaccurate and does not parse text properly ✘ Does not produce native video outputs in comparison to Gemini Pro VEO 3 or upcoming VEO 4 power ✘ Does not integrate like Gemini Pro with Google Videos, Products, and Workspace ✘ Does not check Gmail inside the chat interface ✘ Uses folders, but does not use Gems like Gemini Pro, which are sub-agents with rules, (Time Saver) Gemini Pro — Why I Transitioned (Now Operating as “Nautilus”) ✔ Exported ENTIRE history of conversations from ChatGPT to Gemini Pro very easily. ✔ Stronger long-context persistence across extended conversations ✔ Stable performance during sustained, high-intensity usage ✔ Supports structured agent orchestration with Gems ✔ Enables purpose-built autonomous agents (“Tritons”) ✔ Reduces prompt redundancy through retained role-specific logic ✔ Scales horizontally without performance collapse ✔ Better aligned with real business, automation, and execution workflows ✔ Superior image creation with Nana Banana Pro ✔ Superior creation of videos with VEO3 & VEO4 ✔ Checks Gmail inside Gemini Pro chat interface (Genesis Pro user face) ✔ Pulls YouTube videos directly inside the UI chatbox, which GPT does not do ✔ Grabs direct research from Google, which ChatGPT cannot do

quick tip that’s helped me with AI: focus on clarity before prompts. Clearly defining the outcome, audience, and purpose often leads to far better results than simply asking AI to complete a task. Looking forward to learning and sharing insights with this community.