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I have been doing many shadow AI assessments recently. If you are interested in one please let me know.
The network for creativity
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Connect with clients, get discovered, and run your business 100% commission-free
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Most AI projects do not fail because the model is weak.
They fail because the system around it is weak.
Poor context. No memory strategy. Unreliable integrations. No evaluation. No fallback logic.
When I build AI agents, I focus on the full system around the model, not just the prompt.
That usually means backend APIs, structured context, RAG, tool integrations, queues, databases, monitoring, and clear failure handling.
The goal is simple: make AI useful in production, not just impressive in a demo
Turning a data-heavy AI product into a light, friendly experience, brought to life with motion. We’d love to hear your thoughts!
Another project I wanted to share: PerceptionX.
It helps teams understand how AI represents their company to potential hires. My role covered the website design and Webflow development.
The interesting part was figuring out how to introduce an unfamiliar idea clearly, then carry that through the pages and interactions.
Sharing a little look at the finished site below. Curious to hear what you think!
Introducing an unfamiliar idea like how AI represents a company is tough, and PerceptionX handles it clearly. Nice to see the Webflow build carry that story through the page.
