About

AI value, measured.

According To What is where I try to figure out how Microsoft AI creates value in real work.

My name is Lisandro, and I am an AI practitioner and consultant. I work with AI every day, mostly around Microsoft 365 Copilot, Copilot Studio, Microsoft Foundry, Power Platform, and Azure AI. So this is not me watching the AI wave from a distance. I am in it, building with it, helping people use it, and still asking better questions about what it actually changes.

I do not have all the answers. That is partly the point. I am convinced AI matters, and I am also convinced we are still learning how to measure it without fooling ourselves.

This platform focuses on Microsoft 365 Copilot, Copilot Studio, Microsoft Foundry, Power Platform, and Azure AI. The recurring question is simple: what happened after the pilot, rollout, or agent went live?

I love AI. I still want the measurement to survive an awkward meeting.

Some posts will be opinion. Some will be experiments. Some will probably age badly, because this field is moving fast. Fine. I would rather learn in public than pretend the method is finished.

Also, the boring basics count. Data quality, permissions, retention, sensitivity labels, governance, good prompts, process ownership, and clear policies all affect whether AI succeeds. Bad foundations can make a good AI idea look worse than it is. Or worse, make a risky idea look successful.

Expect practical experiments, templates, source links, and honest notes about boring tasks that might turn out to be surprisingly valuable. Agree or disagree with parts of it. I probably will too after a few more tests.