The use of new computing paradigms is intended to ease the design of complex systems. However, the non-functional aspects of a system, including performance, reliability and scalability, remain significant issues. It is hard to detect and correct many scalability problems through system testing alone - especially when the problems are rooted in the higher levels of the system design. Late corrections to the system can have serious implications for the clarity of the design and code.

We have analysed the design of a system of multiple near-identical, `reactive' agents for scalability. We believe that the approach taken is readily applicable to many object oriented systems, and may form the basis of a rigorous design methodology. It is a simple, yet scientific extension to current design techniques using message sequence charts, enabling design options to be compared quantitatively rather than qualitatively. Our experience suggests that such analysis should be used to consider the effect of artificial intelligence, to ensure that autonomous behaviour has an overall beneficial effect for system performance.