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I built an AI that answers Instagram DMs for small businesses, here's what 5 completely different industries taught me
I build AI-powered DM automation for Instagram and Facebook. Over the past 2 months I've onboarded clients across 5 completely different industries and every single one surprised me with how they use the product. Sharing what I learned because I think it applies to anyone building tools for small businesses. **1.** **The** **fitness** **coach** **wanted** **to** **send** **memes.** He was the first to really stress-test the AI and his top feature request wasn't what I expected. He wanted the bot to send motivational memes and transformation photos during conversations to keep leads engaged. We built an AI media library where you upload images with descriptions of when to use them, and the AI decides the right moment. His other big ask was blocking friends and family from getting AI responses. Makes total sense once you think about it, but I never would have built it without him asking. **2.** **The** **travel** **company** **exposed** **our** **biggest** **flaw.** He set up a boating trips business and immediately found that the AI was ignoring his most critical instruction: "don't book for the customer, send the booking link." This turned out to be a system-level bug, not a prompt issue. He was hours from cancelling when I found and fixed it. Lesson: when a client says "the AI isn't listening to my instructions," believe them it might be your code, not their prompt. He also told me the AI was using too many semicolons and em dashes. Turns out our system prompt was literally using em dashes in the instruction that told the AI not to use em dashes. The AI learns by example. **3.** **The** **developer** **just** **wanted** **our** **API.** He doesn't care about the dashboard, the AI, or the pretty UI. He's building his own app and needs a Meta messaging API that handles all the authentication and webhook complexity. He asked for: webhook forwarding, a send-reply API, emoji reactions, typing indicators, and Instagram username extraction. He cancelled for a few d
The founder shows strong product-led growth instincts and rapid iteration based on diverse user feedback, which is a positive signal for early-stage PMF. However, the venture potential is capped by high platform dependency on Meta and a low technical moat in a crowded 'AI wrapper' market.