The rocky journey from maker to manager
GenAI reveals and amplifies a classic challenge in arts management
“If you cannot explain something in simple terms, you don’t understand it.”
—Richard Feynman
One of the bumpiest transitions in any career is the jump from maker to manager, or from functional/operational action to general management. As a maker or functional professional, you succeed through direct action, tacit (internal and habitual) knowledge, and coordination with functional peers (a production team, a development team, a marketing team). As a manager, you succeed through information and influence, explicit and explainable knowledge, and coordination across multiple specializations.
While that challenge used to be limited to newly promoted leaders, generative AI is forcing a similar struggle on anyone and everyone in the enterprise. AI is, essentially, a bright but clumsy team member you now have to manage. That drags you and everyone else, regardless of promotion, into the management challenges of indirect action, explicit knowledge, and cross-specialist coordination.
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Management scholar Linda Hill (2007) noticed and named the experiences of high-performing professionals as they moved into general management:
In their prior jobs, success depended primarily on their personal expertise and actions. As managers, they are responsible for setting and implementing an agenda for a whole group, something for which their careers as individual performers haven’t prepared them.
In other words, the ability to do direct work doesn’t necessarily translate to an ability to describe, delegate, and develop others toward that work. Individual, functional, operational expertise may be useful but it’s not sufficient.
Anyone working with generative AI faces a similar disconnect. Specifically, productive engagement with AI demands explicit and detailed answers to three questions:
What are the CONDITIONS of success in the task or project? What observable and reliable indicators distinguish a job well done?
What relevant, reliable, and accurate CONTEXT should inform the work? Of the vast array of possible reports, spreadsheets, memos, notes, emails, and resources available, which are the sources of truth?
What CONSTRAINTS must focus and narrow the full range of possible actions? Are there rules, regulations, expectations, limitations, or even conventions of practice that must be obeyed?
So often, these questions are embedded in the practice itself, and the lived experience and expertise of the operational team member. Which makes the transition to team leader, or AI wrangler, not only a change in difficulty but a change in kind.
From the ArtsManaged Field Guide
Function of the Week: People Operations
People Operations involves designing and driving systems and practices that attract, engage, retain, and develop people within the enterprise (also called human resources).
Framework of the Week: Finders, Minders, and Grinders
Consulting firms often organize their teams in three groups, each with different expectations and responsibilities (and hourly rates). Finders bring in the clients. Minders manage the projects. And Grinders execute on the analytical and technical tasks. It’s a callous but constructive way of understanding the division of effort in any organization.
Photo by 愚木混株 Yumu on Unsplash
Sources
Hill, Linda A. 2007. “Becoming the Boss.” Harvard Business Review 85 (1): 48–56. 23363457.