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My Dot built a streetwear brand: 6-prompt head-to-head vs Muse and Grok Bot

@TahaElHarti

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I gave OpenAI's dots, Grok Bot and Meta's Muse the exact same six prompts and asked each one to build me a streetwear brand from scratch. Round 1: name, logo and customer. Round 2: the first collection. Round 3: suppliers. Round 4: the online store. Round 5: launch ads. Round 6: the investor pitch. Which AI can actually help build a $10K/month business?

YouTube creator Taha El Harti (channel 'Taha El Harti | Making AI Useful', @Tahaelharti_ai) ran a first-hand head-to-head test of OpenAI's Dots against Meta's Muse and Grok Bot, feeding all three the exact same six prompts to build a $10K/month streetwear brand from scratch. His Dot produced concrete round-by-round results: brand name, logo and customer profile; the first collection; supplier sourcing; an online store; launch ads; and an investor pitch. The video shows the Dot's real output at each stage — a genuine first-hand build test of the Dots agent, with the creator's own verdict at the end.

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Tried Dot for 1 week and it won me

I know the cool thing has been dunking on it, and I was skeptical too. So I challenged myself to use it starting last Friday. TLDR: I had Dot help build a real, playable Digivice in my downtime. My son ran around the house playing it for two hours. Based on my usage, I have questions about efficiency, but the benefit of having an orchestrator I can just chat with is pretty hard to deny. I had it design and build a real Digivice to play with my son, entirely in my downtime. The idea was simple. Let’s make a Digivice that actually works. Something we can carry around, encounter Digimon, battle, capture, and evolve them. So I started issuing Dot tasks: \- Build a 3D model of a Digivice. \- Build a shopping list to turn that model into an electronic game. \- Build the firmware around my vision for how the game should work. \- ??? \- Profit. Son ran around the house for two hours playing it. Obviously, I still had to print the parts, assemble the electronics, and actually test the thing. And there’s been plenty of iteration. Screw holes needing adjustments, the screen facing the wrong direction, touch controls that sounded good but felt finicky on the device. Real hardware gives you feedback pretty quickly. A lot of my messages were basically: “This doesn’t feel right. Let’s change it.” Then I’d describe what I wanted and have it work through the changes. That’s the part that won me over. I could give it a high-level objective during some downtime, come back, review what it had done, and give it the next set of changes. We went from an idea to something my son and I can actually play with. Playable web preview: [https://goldsziggy.github.io/z-ark-digivice/play/](https://goldsziggy.github.io/z-ark-digivice/play/) Device renderings: https://goldsziggy.github.io/z-ark-digivice/ GitHub, if you want to take a look or build your own: [https://github.com/goldsziggy/z-ark-digivice](https://github.com/goldsziggy/z-ark-digivice) In addition to this, I’ve had it: \- Manage tracking for my son’s mattress order and draft emails asking for updates. \- Work on a Pokopia-like game with Digimon, Pokémon, Palworld, and Pikmin influences. \- Bounce around work ideas, including multi-agent frameworks and MCP proposals like skills over MCP. \- Work on the bedtime book app I use with my son. Based on my usage percentages, I can almost guarantee it isn’t very efficient with its agent use. But I can’t deny the benefit of having essentially an orchestrator in chat that I can delegate high-level objectives to. And in this case, that turned into a real game I can play with my son. No internet required; and can take to the park like it’s Digimon Go
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