Imagine you’re sitting in a business meeting. Someone stands up and starts talking about “value streams,” “business capabilities,” and “business processes.” Everyone nods. You nod too. But inside, you’re not entirely sure what any of it actually means , and you suspect a few other people in that room feel exactly the same way.
Every time you’ve ordered food on your phone and waited for it to arrive at your door, every time you’ve walked into a restaurant and sat down for a meal , you’ve experienced “value streams,” “business capabilities,” and “business processes.
Early detection of lung cancer saves lives. When a pulmonary nodule, a small lump in the lung tissue, is caught early enough, treatment options are far better and survival rates improve significantly. The challenge is that spotting these nodules on a chest MRI scan requires a trained radiologist, a careful eye, and a lot of time. It is not something you can automate easily or rush.
We were exploring whether AI could help with exactly this as part of a proof of concept.
Gen AI Generative AI works by learning from large amounts of data, much like how humans learn from experience. Everything starts with data sources such as text, images, code, and audio. This data exposes the AI to how language is written, how visuals are structured, and how logic works in the real world. Importantly, the AI does not store this data like a library or database. Instead, it studies the data to understand patterns and relationships, which later help it generate new content.
Claude has two modes for handling complex tasks , Planning Mode and Thinking Mode.
Planning Mode = Breadth : looks wide across your whole project
Thinking Mode = Depth : thinks hard about one specific problem
Planning Mode Think of it like a contractor who walks through your entire house before starting any work. They check every room, understand what is connected to what, and make a list before picking up a single tool.
Why Context Matters More Than You Think Imagine you just joined a new team. It is your first day. A colleague walks up and says
“Can you fix the authentication bug in the user service?”
You have no idea where the user service lives, what language the project uses, whether there is a test suite, or what the team’s coding style looks like. You could ask a dozen follow-up questions or worse, you could guess and get it wrong.
