Grasp draws a strict line between asking and changing. You can explore a graph freely without the fear that a query will mutate the world. The system treats queries as reflective operations: they reveal what would be true if a field were to exist, based on the existing structure and resolvers. Mutations, on the other hand, are explicit commitments that write new nodes or relationships.
Why This Boundary Matters
You want the graph to stay clean and reliable. If queries could write, then exploration would risk unintended side effects. The boundary creates a cognitive contract:- Queries inquire.
- Mutations declare.
- Resolvers fulfill.
- Structure holds.
This contract gives you a stable core that can be inspected, reasoned about, and trusted—even while layers of computation orbit around it.
What a Query Actually Does
When you query a field that is missing, the resolver may compute a value. But the graph itself does not change unless you explicitly commit the result. You can think of a query as “show me what this shape would resolve to, given the structure already present.” This makes a query a safe lens of intent, not a hammer of change.The System Stays Clean
This boundary prevents accidental writes. It also enables reversible exploration: you can probe ideas, simulate outcomes, and inspect missing data without polluting the graph. When you decide a computed value should become real, you perform a mutation that persists it.Why AI Needs This Boundary
AI is exploratory by nature. It tests possibilities, probes structures, and asks “what if” questions. Without a query/mutation boundary, an AI would risk corrupting the system simply by thinking. The boundary creates a safe playground: AI can explore without committing, and then explicitly mutate when the intent is clear.Practical Patterns
- Treat queries as shape checks and simulations.
- Persist resolved data only through explicit mutations.
- Maintain a clear log of when and why mutations occur.
- Use query outcomes to drive decision-making without side effects.