We’ve been building OXB Studio, a two-sided platform designed to help service providers (AI devs, automation builders, technical freelancers) present their work clearly, and help business owners find the right builder without sorting through noise. It’s not a marketplace clone. The focus is on clarity, trust, and execution rather than volume. We just reached a milestone where the core system is working end-to-end, so I wanted to share a few practical build learnings that might be useful if you’re shipping AI or platform products: - Role clarity beats feature depth. The biggest early win was forcing a clear split at onboarding: provider vs client. Most confusion disappears once users immediately know “who they are” in the system. - Dataflow > AI magic. The product only feels intelligent when users can see what’s happening next. Clear states, ownership, and progress mattered more than advanced AI features early on. - Workrooms reduce chaos. A shared space with milestones and scope visibility prevents most breakdowns once real projects start. - Trust signals are everything. Profiles only work when proof (projects, structure, reviews) is surfaced cleanly and consistently. I’m attaching a short walkthrough clip of the current beta so you can see how these ideas were implemented in practice. If you’re building a two-sided platform or AI product, curious what part has been hardest for you: onboarding clarity, trust, or operational flow?

Open any AI tool. It doesn't matter which one! Type this prompt: “Ask me one question at a time to understand what I do, and when you have enough information, clearly explain how you can help me.”

We just had the privilege of letting our partners over at Feeding America know that we will have another 2,000,000 meals ready to send their way in November. We just donated 1,400,000 meals in October and they just informed us that in the last few years we are now at 14,173,890 MILLION MEALS DONATED! It wouldn't be possible without all of you! 😃

The biggest difference between emails that get ignored and emails that get replies isn’t the subject line… it’s research + relevance. I just put together a system using n8n that: - Research prospects automatically - Pulls real, meaningful context - Turns that research into truly personalized cold emails Not templates.Not generic “we help companies like yours” nonsense. When your email proves you actually understand the person you’re reaching out to, replies stop being random, they become predictable. Most people don’t need better copy. They need better inputs. And automation done right makes that easy.