This came up on my feed this morning, thought I’d share the laughter 😊

What brought you to Data Alchemy? Why do you want to work with Data? Share your story! What's mine? I'm working in the oil and gas industry, and I'm responsible for drilling data acquisition and some basic interpretation on the offshore drilling rigs. But now I want to go to the other side of the mirror 😉

https://www.youtube.com/shorts/uvHeI9f_ZYE

Everyone’s chasing the next breakthrough model…But here’s the truth: Most businesses don’t need GPT-4. They need someone who understands their data, their users, and their goals. What does that mean for us? • Knowing when not to use AI • Cleaning data like it matters (because it does) • Designing prompts that sound more like UX than code • Merging messy spreadsheets into smart pipelines • Building trust in the output—not just accuracy AI isn’t magic . It's a system of assumptions, data, and intention. And the real alchemy? That’s when you turn noise into knowledge—before the model even runs. What’s one overlooked AI skill you think every Data Alchemist should master?

Everyone’s talking about AI agents. But the truth? Most demos you see online are just that—demos. Even big players like Apple and Amazon struggle to make their AI features work in the real world due to issues like hallucinations and unreliable outputs. In this week’s video, I break down the differences between simple workflows and true AI agents and share practical strategies for building reliable AI systems, including: - How to use workflow patterns like prompt chaining and routing to solve real problems effectively - Why agent frameworks might not be the solution you think they are - The #1 thing you need to scale AI systems successfully (hint: it’s not a new tool) Learn how to move beyond the hype and build AI systems that actually work.