
What does your company own?
Maya catches a mistake. Can her company keep the lesson?
AI at work
I make films about AI at work, using everyday examples to make sense of the systems we rely on.
For people making technology decisions at work.

Maya catches a mistake. Can her company keep the lesson?
Keep following the questions
Turn a film over.
See where it takes you.



Essays & notes
The films and the writing follow the same questions: how AI becomes useful, how knowledge spreads and what people learn along the way.
Essay
“Your correction helped once. The tacit knowledge behind it can continue helping.”
From my essay
In an imagined refund request, Maya catches something the AI missed. I follow what her correction can leave behind: the right agreement, the reason it applies and a test for the next model. Keeping that lesson useful is still someone’s job.
The person behind the questions
Based in Toronto.
At Siemens, I help teams navigate complex IT environments and improve how services work together. I also build products and explore how AI can be useful in practice.
Running Digitally is where I turn those interests into films. I start with a question, work through the evidence and use everyday examples to make the systems easier to understand.
The questions that stay with me usually come after the demo. How do people check an answer and decide what to trust? If you’re working through an IT or AI question, I’d be glad to compare notes.
Narration is synthetic. Views are Satish's own.
I start with a question I want to understand. I read the sources, choose an everyday example and work through how the system behaves. I make the assumptions and limits visible, with chapters and references so you can check the reasoning.
The film notes include the sources and explain how the narration, illustrations and animation were made.