Cay works in the space between product strategy and implementation, where teams need to turn uncertain ideas into something concrete enough to evaluate. The work often begins with a question: what should this product do, what should be built first, and what would a real version look like?
Computer Agents gives Cay a workspace where those questions can become durable product work. Agents can explore context, create structured project plans, draft tasks, inspect files, create deliverables, and keep the reasoning attached to the same project instead of leaving it behind in a temporary chat.
From product ambiguity to structured work
Early product work is usually messy. There are notes, requirements, examples, constraints, and assumptions that need to be clarified before implementation starts. A useful AI system has to do more than produce a paragraph. It has to help organize the work.
Cay uses Computer Agents projects to capture that structure. A product question can become tasks, releases, comments, files, and follow-up work. Agents can inspect the surrounding context and decide what needs to be researched, drafted, prototyped, or reviewed next.
The result is a workflow where product thinking does not disappear after one prompt. It becomes part of the same system that can later support design, implementation, and review.
Why product context needs a workspace
Product decisions depend on context: what has already been tried, what the team agreed on, which constraints matter, and which tasks are still open. Cay uses Computer Agents to keep that context in one place, so every new run can build from the previous state of the project.
When an agent can see files, tasks, project plans, and prior runs, it can do more useful work. It can compare options, point out missing assumptions, draft a next version, and leave the output where the team can continue from it.
“For product teams, the value is not just faster ideation. It is having an agent that works inside the same project structure where decisions, files, and next steps live.”
Prototypes that stay connected to decisions
A prototype is most useful when it is connected to the reasoning that created it. Cay can use Computer Agents to keep the project brief, implementation notes, files, and generated artifacts together, making it easier to understand why the prototype looks the way it does.
That connection also makes iteration easier. When feedback arrives, the agent can inspect the current state, update the task plan, modify files, or create follow-up work without the team needing to reconstruct the whole context.
What this makes possible next
Cay shows how product teams can use agents as an operating layer for the messy middle of product development. Ideas can be explored, structured, prototyped, and refined without resetting context at every step.
As the workflow matures, the same project workspace can support deeper implementation, review, and delivery. The strongest product ideas can move from question to plan to prototype with more continuity and less manual coordination.