In this paper we describe the IAMwildCAT agent, designed for the TAC Market Design game which is part of the International Trading Agent Competition. The objective of an agent in this competition is to effectively manage and operate a market that attracts traders to compete for resources in it. This market, in turn, competes against markets operated by other competition entrants and the aim is to maximise the market and profit share of the agent, as well as its transaction success rate. To do this, the agent needs to continually monitor and adapt, in response to the competing marketplaces, the rules it uses to accept offers, clear the market, price the transactions and charge the traders. Given this context, this paper details IAMwildCAT's strategic behaviour and describes the wide techniques we developed to operationalise this. Finally, we empirically analyse our agent in different environments, including the 2007 competition where it ranked first.