The challenge for interviewers is distinguishing between candidates who sound ready — and those who will become ready under pressure.
David J. Chamberlin is the managing director of the Strategic Communications Advisory Team at Orrick.
Early-career candidates have never sounded more prepared. That may be a hiring risk.
They arrive with structured answers, polished language and a level of fluency that, not long ago, took years to develop. AI has raised the baseline. Drafting is instant. Analysis is accessible. Thinking appears clean.
But that fluency can be misleading. Because what sounds like experience is often proximity to tools.
When I started interviewing people, no one taught you how to evaluate judgment. You hired for capability — writing, clarity, composure — and trusted that experience would do the rest.
That model no longer holds.
The job of the interview has changed
We are no longer hiring for output. We are hiring for trajectory. More specifically, we are hiring for the capacity to develop judgment that matters most when the stakes are real.
The challenge is that judgment rarely presents itself directly in interviews. You have to know how to look for it. This doesn’t require redesigning your entire hiring process. It requires changing how you use the interview itself — spending less time validating polished answers and more time creating conditions where thinking has to evolve.
Traditional interviews reward polished answers. Effective interviews surface how thinking changes under pressure.
Test for how candidates think — not how they sound
Strong interviews should introduce ambiguity early — not as a tactic, but as a reflection of reality.
Communications, marketing and corporate affairs don’t operate on perfect information. Priorities collide. Facts are incomplete. In communications, where timing, accuracy and stakeholder trust are constantly in tension, those tradeoffs define the work.
The question isn’t whether a candidate knows the answer. It’s what they do when there isn’t one.
What matters is posture under uncertainty. Do they get curious? Do they ask better questions about context, constraints and risk?
One simple way to surface this is to shift from retrospective questions to live problem-solving. For example: A regulator calls about an issue we don’t fully understand yet. Media inquiries are starting. What do you do in the next two hours?
Then add pressure. Now assume legal tells you we can’t disclose key facts yet. What changes? The content of the answer matters less than how the thinking evolves.
Candidates who move too quickly to closure often struggle when situations don’t resolve cleanly — which, in practice, is most of the time.
Do they become defensive, or more thoughtful? Do they double down, or adapt? The ability to revise thinking under pressure is one of the clearest early indicators of judgment.
Closely related is the ability to think beyond the first move. AI is exceptionally good at generating first-order responses, but what differentiates people is whether they can anticipate what happens next.
Look for ownership, ethics and awareness of consequence
Ownership is another critical signal, and it often shows up in how candidates describe past experiences.
Most people can explain what happened. Fewer take responsibility for outcomes, especially when those outcomes weren’t ideal.
But in practice, accountability is not optional. It’s structural.
Listen carefully to whether candidates default to explanation or ownership. Do they acknowledge what they would do differently next time? Stronger candidates tend to describe what they would change. Weaker candidates tend to explain why the outcome wasn’t their responsibility. Blame halts development. Ownership accelerates it.
Ethical instinct matters just as much.
Most failures didn’t begin with clear ethical breaches. They began with small rationalizations under pressure — because something was technically allowed, because speed felt necessary or because no one expected immediate consequences.
That’s why it’s not enough to test obvious right-versus-wrong scenarios. The better signal is whether ethical awareness shows up before it’s required.
One way to surface this is to introduce tension into an otherwise straightforward decision. For example: “We have incomplete information, leadership wants to move quickly and there’s no immediate legal constraint. What do you do?”
Do candidates recognize tradeoffs between speed, accuracy and transparency? Do they consider downstream impact on stakeholders?
Stronger candidates will often pause, qualify their answer, or surface risks before being asked. Weaker candidates tend to move directly to action without acknowledging the tradeoffs.
And underlying all of this is something we evaluate constantly: an understanding of power and context.
In real organizations, decisions are not made in neutral environments. Even without direct experience, the strongest candidates begin to see that decisions are shaped by authority and constraint — and they start to ask better questions because of it.
Those questions signal awareness that goes beyond task execution.
The signal is in how thinking evolves
At this stage, confidence is not a particularly useful indicator. It can be manufactured. It can be borrowed.
What matters more is judgment velocity — how quickly someone’s thinking improves as complexity increases.
You can see it happen in real time. Do their questions get better? Do they incorporate feedback? Do they refine how they frame the problem? Because early-career professionals, by definition, have not yet been close enough to sustained consequence to fully develop judgment.
The role of the interviewer is not to confirm what they already know. It is to determine how they will learn.
So, if you want to improve hiring outcomes, don’t spend the interview validating answers. Spend it creating conditions where thinking has to evolve, because in an environment where AI can replicate much of the visible work, that distinction is no longer philosophical. It is operational.
That’s the difference between hiring for polish and hiring for judgment.
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