In a beautifully written, cogently argued paper MacDonald (2013), presents the theoretical framework that guides one of the most creative and influential research programs in the language sciences. The PDC began with empirical demonstrations that readers are remarkably sensitive to distributional patterns in the input. These empirical demonstrations were accompanied by theoretical arguments that ambiguity resolution can be modeled by constraint-based (probabilistic) systems that learn these patterns from experience (also see Tanenhaus and Trueswell, 1995; Tabor et al., 1997). This research was part of a wave of research in the 1990's that answered long-standing questions in real-time language comprehension and early language acquisition, with variations of “It's the input, stupid” (e.g., Saffran, Aslin, and Newport's seminal work on statistical learning, Saffran et al., 1996). The probabilistic constraints that comprehenders learn and use must arise from the output created by speakers and writers. But why does that output exhibit systematic patterns both within and across language? One answer is that languages maximize learnability for the child. A second is that speaking and more generally the structure of language is shaped by considerations of communicative efficiency (see Jaeger's commentary). MacDonald proposes a production-based answer. Grounding her arguments in insights from the motor planning and control literature, MacDonald makes a convincing case that that constraints on planning processes in language production play an important role in shaping the form of utterances. She argues that the demands of memory retrieval, planning, and linearization for sequential behavior that requires a hierarchical control structure play the central role both in determining the forms that speakers use to convey their intentions and, as a consequence, the patterns of linguistic forms that are observed both within and across languages. These arguments are supported by a clear exposition of principles and a summary of some elegant experiments focusing on the production of relative clauses. Less convincing is MacDonald's argument that these production constraints comprise most of the story. Here is the cartoon view of the assumptions that underlie this claim. Speaking is extremely hard while understanding is comparatively easy. It is costly for speakers to take into account the listener, especially at the temporal grain required for influencing the planning process in production. Listeners, however, are really good at learning probabilistic constraints, making use of context, and adapting to speakers. Given these considerations it makes sense for speakers (and languages) to promote forms that make speaking easier. In this commentary, I raise question about some of the assumption that underlie the claim that production demands—in particular planning and linearization—are most of the story. I begin by noting some parallels with earlier arguments that were based on assumptions about the difficulty of comprehension. I note that much of what we know about how naturally listeners use context, emerged only when psycholinguists began to examine language comprehension in richer contexts and more natural interactive tasks. I suggest that we actually don't know much about how speakers might adapt to addressees in real-time language production. There is a paucity of research that examines production in those interactive environments where addressees provide feedback. When production is examined in interactive settings, there is tantalizing evidence that speakers do, in fact, monitor addressees, and might adapt on the fly.