AI context
Give AI workflows structural context
Connect a task to the surrounding code so an agent can reason with relationships as well as retrieved text.
The problem
An agent can retrieve a relevant file and still miss a shared contract, a caller or a test that constrains the change. More text is not always better context.
A task is paired with relevant source, explicit constraints and tests into a reviewable context package before a person or agent reasons about a change. This is a conceptual example of useful context.
What Graphtia provides
Graphtia’s direction is to make code relationships and source context useful together. Explorer concepts such as dependencies, paths and related tests help define a focused context for an engineering question.
Keep context bounded and checkable
Start from the task and identify the relevant code. Include why each relationship matters, the source revision and any known limits of the result. Ask the agent to verify assumptions against source and tests before proposing a change.
Where it helps
Focused context is useful for an agent-assisted refactor, a review of a proposed change or an investigation that crosses multiple files. Explain the relevance of each source location before expanding the scope.
Relevant capabilities
Locate the interfaces involved in the task.
Connect callers, dependencies and relevant checks.
Keep assumptions and incomplete results visible during review.
Relevant product
Explorer addresses the code-understanding layer. Agent integrations and supported workflows will be described before public availability; this page does not promise an integration that is not yet announced.