Humans don’t speak like forms. A person’s message is often vague, incomplete, and messy: β€œAbout that thing from last week, I think we should do something.” To a human familiar with the context, this sentence means something. To a system, it is a puzzle. We believe the hard job of an intelligent system is exactly this: extracting a correct, structured action from that mess β€” without asking the user to speak like a form.

Why this is hard

The difficulty comes from the gap between human language and a structured action. An action requires clear fields: what, for whom, at what priority. Human language does not state these fields explicitly; it hides them in context, allusion, and assumption. Bridging that gap β€” not by forcing the user into structure, but by the system understanding the mess β€” is what makes a good experience.

The path of conversion

This conversion happens in a few distinct steps. First, finding context: the system must work out what β€œthat thing from last week” refers to and retrieve it from shared memory. Second, organising: breaking what was said into meaningful parts β€” a new fact, a note, a state change. Third, the stage decision: should this matter advance to the next stage? Finally, action: turning all of this into a clear, structured proposal.

A human in the loop

Crucially, the output of this path is not an automatic, final action; it is a proposal. The system presents what it understood in structured form, and a human reviews and approves it. This loop catches errors and builds trust: the system performs the heavy lifting of extraction, and the human remains the final judge.

Domains are only examples

This pattern is not tied to one particular domain. It could be a sales note becoming a file update, a support message becoming a structured ticket, or a vague request leading to a specific action. These are only examples. What stays constant is the pattern itself: a vague message on one side, a clear action on the other, and an intelligent path in between.

Putting it together

We believe the mark of a truly intelligent system is not answering clear questions, but understanding vague messages. The user should not have to speak like a machine to be understood; it’s the system that should understand human language. And it’s right here that the gap between a rigid tool and a real colleague shows itself.