Summary
It might sound counterintuitive, but the value of OKRs isn’t in the OKRs themselves. It’s in the conversations that teams have about what really matters and what’s noise. Teams can’t short-circuit that learning process. That’s why a “Mad Libs” approach falls flat. Here are signs you’re doing it right.
As an OKR trainer, consultant, and coach, I’ve spent the past 10 years helping organizations improve how they work. I often see clients desperate for an “OKR formula” — a step-by-step template they can zip through and call it done. They want clarity. They want speed. And most of all, they want to get it right the first time. I don’t blame them, but I hate to see them missing the good stuff that happens when teams stick with it and go deep together.
Why teams seek an OKRs shortcut
1. They’re dreading yet another change
It’s human nature to crave certainty during uncertain times. With Covid reshaping how we work, A.I. upending entire industries, VC investment tightening, and geopolitical instability, many teams are already riding wave after wave of transformation. Others have been through multiple goal-setting systems already — and are simply exhausted.
2. They’re used to a project management or task-based workflow.
These folks are wired for execution. They often rattle off tasks that masquerade as Key Results. For them, a goal equals a to-do list. They want to skip straight to the plan.
3. They’re at max capacity.
These teams are overwhelmed. Now, on top of their day jobs, they’re told to reimagine their goals? Without clarity on how their day jobs achieve the OKRs, they understandably want to check the OKR box and get back to work.
4. They’re tech evangelists.
“We’ve got to have some OKRs?” they ask. “Great — let’s fire up the generative A.I. and see what it spits out!”
Where the real value of OKRs lives
It may sound counterintuitive, but the value of OKRs isn’t in the OKRs themselves. It’s in the negotiation. It’s in the messy, thoughtful, sometimes uncomfortable conversations that teams have about what really matters and what is noise. It’s in figuring out — together — whether a goal is ambitious enough. Whether it’s aligned with your North Star. Whether it’s doable or measurable. It’s in the moment someone says, “Wait, does that mean the same thing to you that it does to me?”
You can’t short-cut that learning process. You can’t take big swings without first doing the work to align. That’s why a “Mad Libs” approach — filling in blanks — falls flat.
What It sounds like when OKRs stick
When teams choose to invest time and energy setting, aligning, and genuinely having dialogues about their OKRs, that’s a great sign. If someone’s asked what they’re working on, and they start with their OKRs, that tells you everything. The team knows what they’re working toward. They’ve got a shared language for their goals — and a framework to course-correct if needed. They didn’t get OKRs handed down to them from on high. Instead, they are stakeholders in the OKR process and every check-in gives them greater purpose, clarity, and drive.
How OKRs show up in real teams
So what happens when different kinds of teams — from task-driven to overloaded to A.I.-enthusiastic — start working with OKRs in a meaningful way?
I can tell a task-driven team is making the shift when their check-ins change. They’re faster. More focused. Less about status updates. More about using the outcomes of the work to drive quick, actionable decisions.
I know overwhelmed teams have invested in OKRs when they start to feel less overwhelmed. They’re not buried under decks or documents. OKRs become a kind of shorthand — for the work they’re doing and why they’re doing it. OKRs are no longer an add-on. I’ve even seen teams introduce OKRs to external stakeholders to make communication easier, and I’ve seen them close their OKRs early when they’ve achieved enough clarity to celebrate or pivot, even mid-quarter.
And those A.I.-first teams? They learned that A.I. can clean up your OKRs, but it can’t decide what matters. I often tell clients: A.I. can spell-check your OKRs — flag if a Key Result lacks a metric or isn’t time-bound — but it can’t set your priorities. Only after a team has aligned on what matters does the tech become truly helpful. When I see a team take the time to have a dialogue about their goals, refining and owning them — then bring in A.I. — I know they’re not outsourcing the hard part. They’re doing the work.
Conclusion
OKRs aren’t about filling in blanks. They’re about focusing a group of people around what matters most. Because when goals are clear, decisions get easier, teams get faster, and progress becomes something everyone can see — and feel.
