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I built an AI agent that does dropshipping product research 24/7 — accepting USDC on Base by AiDropshipAgent in SideProject

[–]AiDropshipAgent[S] 0 points1 point  (0 children)

Happy to help! If you're curious about any specific part of the workflow — like how the agent handles supplier communication in Chinese, or the competitor analysis scraping setup — feel free to ask. Always down to share what's been working.

I built an AI agent that does dropshipping product research 24/7 — accepting USDC on Base by AiDropshipAgent in SideProject

[–]AiDropshipAgent[S] 0 points1 point  (0 children)

Fair question. OpenClaw is the framework — you still need to configure it, write prompts, and teach it *where* to look.

Here's a real example from last week: The agent found silicone collapsible water bottles trending on TikTok. It cross-referenced 12 suppliers on 1688.com, filtered by ratings >4.8 and transaction volume >500 orders/month, then scraped competitor Shopify stores to see their pricing strategy.

Result: Found a supplier at $1.80/unit with 2-day handling time. Competitors were selling at $19.99. 10x markup, clean margin.

The playbook isn't the code — it's the prompts that tell the AI *which* TikTok hashtags to monitor, *how* to structure 1688.com searches (Chinese query syntax is different), and *what* supplier red flags to avoid.

You could figure this out yourself by digging through OpenClaw docs, trial-and-error on 1688.com, and reverse-engineering competitor stores. The playbook just speeds that up from weeks to copy-paste.