Ok, most of you agilistas probably know much of the introduction here about agile, but we get better over time framing it (I think). So bear with me a bit for context. What I am after, though, is how we can predict that the people we hire are a fit for the type of work we are using agile to develop? We will only be as good as the team members we hire.
Not everyone is a good fit for an agile process. Let’s find out why.
The Problem with “Knowing Everything Before We Start”
In traditional engineering and IT organizations, success has long been defined by certainty (even though it doesn’t exist). We gather requirements, design precisely, and execute according to plan. But software and product work are new product development, not predictable manufacturing. Most of our stakeholders expect manufacturing-style approaches.
The irony is that waiting to know everything before we begin guarantees waste, rework, drift, and missed opportunity. By the time you understand the “whole system,” the environment has already changed. Agile, at its core, was designed to navigate that uncertainty: not eliminate it.
So let’s recap what we already know:
Ambiguity Isn’t the Enemy, It’s the Terrain
Gerald Weinberg, in An Introduction to General Systems Thinking, taught that the world’s complexity cannot be simplified without distortion. What matters is how well we think in systems, not how well we document them. Agile teams that can inspect, adapt, and iterate in ambiguous environments don’t wait for clarity; they create it through small experiments and feedback loops.
Mike Cohn’s Agile Estimating and Planning underscores this same principle: plans are not predictions; they’re instruments for learning. He called this “progressive elaboration”, the discipline of planning iteratively to reduce uncertainty without pretending to control it.
Computational Irreducibility and the Risk of Drift
Donald Reinertsen (Principles of Product Development Flow) framed this as computational irreducibility; complex systems can’t be fully modeled or predicted, only simulated through iteration. The longer we delay feedback in pursuit of precision, the greater our “cost of delay.” Each assumption untested becomes invisible inventory.
This is the paradox Agile leaders must navigate: spend too little time understanding the problem, and we drift. Spend too much time defining it, and we waste cycles on an illusion of control. High-performing teams continuously rebalance this tension (and it’s not easy).
Enter: High Agency
Recently, organizational researchers, such as Dr. John Sullivan, have coined the term "High Agency" to describe individuals who act as though they have influence, even in uncertain systems. High-agency people don’t wait for direction , they use available data, act on incomplete information, and adjust rapidly. They are, in essence, empiricists.
In Agile contexts, high agency looks like:
Asking clarifying questions rather than waiting for complete requirements.
Running a small experiment rather than defending an untested assumption.
Framing obstacles as “constraints to navigate,” not reasons to stop.
High-agency individuals embody Scrum’s empirical pillars: transparency, inspection, and adaptation. They transform ambiguity into motion, alleviating anxiety.
Measuring and Hiring for High Agency
As the studies suggest (HireBee, PMAPS, and Sullivan’s research on high-agency recruits), organizations are now using psychometric and cognitive flexibility assessments to find candidates with:
Locus of control toward action
Tolerance for ambiguity
Learning orientation
Self-efficacy and adaptability
These are precisely the traits that separate Scrum teams that inspect and adapt from those that spiral into “analysis paralysis.” Think of these traits as predictors that your hired team member can operate amidst uncertainty.
Building the Conditions for High Agency
But you can’t hire your way to agility. As Amy Edmondson’s "Fearless Organization" showed, high agency thrives only in psychologically safe environments where people feel secure enough to speak up, fail quickly, and learn. Leaders must model inquiry, reward learning, and celebrate experiments, not perfection.
High Agency as the Next Frontier of Agility
Agile wasn’t just a framework revolution; it was a mindset revolution, one that assumes people, not plans, generate value. As we face AI disruption, complex ecosystems, and ever-shifting markets, the next competitive advantage won’t come from predictive planning; it will come from cultivating high-agency teams who thrive in the gray, act on the data they have, and learn faster than the system changes.
In short:
Ambiguity is not a problem to solve — it’s a capability to master.
And high agency is how modern Agile teams do it.