"So, as a practising designer, are you ready for the next big evolutionary push forward?" asked the international creative evangelist, singling me out following a recent working lunch.
I could tell he planned to buttonhole me, because he'd noted my bemused smirks every time he repeated today's favourite buzzword: "innovation".
Clearly I'd provoked his personal confidence levels.
Faced with a loaded question, I tend to meekly reply, "I hope so." There's no point explaining to the highly-wired that when you reach my age, just waking up breathing is enough evolutionary push forward to satisfy my daily business ambitions.
"So, how do you plan to ideate in the future?" he continued.
"Ideate" is one of those hackneyed phrases served up as garnish on the same platter as "innovation" and is a term much loved by Palo Alto technology devotees.
Experience has taught me not to fence with wacky educational gurus seeking the upper hand.
Much better to answer by playing back some of the dross I'd listened to for the past hour.
"I'm going to focus on generating symbiotic concepts that hopefully might lead to unexpected serendipitous discoveries along the way," I murmured.
"Good answer ... I'm impressed," he replied, before adding quizzically: "so, what's your approach on LP?"
"Ah! The LP factor," I murmured, wondering what on earth Lemon and Paeroa had to do with creating a brave new world.
When faced with the unknown, I hurriedly retreat to the toilets to check Google on the mobile. "What's does LP mean?" I tapped out anxiously.
"Linear Programming" was the response, with the following complex explanation.
"This is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints.
"Its feasible region is a convex polyhedron, which is a set defined as the intersection of finitely many half spaces, each of which is defined by a linear inequality. Its objective function is a real-valued affine function defined on this polyhedron. An LP algorithm finds a point in the polyhedron where this function has the smallest (or largest) value if such a point exists."
Returning to the innovation mastermind, I smugly reintroduced the conversation where we'd left off. "That LP question ..." I blithely said, repeating parrot fashion the contents of Google's text. He appeared genuinely taken aback. "Wow! That's really interesting," He said, adding weakly, "I've never heard of 'Limited Production' being described that way before."