Five Things I Kept Thinking About This Year, and What They Mean for 2026
Building the Muscle to Sustain What You Already Know
tl;dr: Leaders already know what needs to happen, but building the muscle to choose and sustain the choice when pressure mounts—that’s the work now, and ahead.
1. The Choice Problem
You can’t have strategic clarity without deciding what you will not do—which means telling the advancement team their fundraising idea doesn’t align, explaining to the middle school head that their new program isn’t happening this year, or helping alumni understand that the thing they loved might not continue.
Strategic planning that avoids choice produces plans with 47 priorities across 8 themes: beautiful documents that don’t drive change.
Ask at your next leadership team: if enrollment dropped 10% tomorrow, which priorities would you cut?
If there’s silence in the room, it’s not because people don’t care, but because consensus feels safer and makes everyone feel included. However, clarity drives change, and change requires disappointing some stakeholders.
When you name three priorities, you’ve implicitly deprioritized everything else, which means most leaders carry the exhaustion of doing too much rather than face that conversation. A common refrain I hear: “We keep saying yes to good things and wondering why we’re still exhausted.”
Once you’ve chosen, however, you have to stay chosen—not just during the retreat when energy is high, but every week when new opportunities emerge, every month when stakeholders advocate for their initiatives, and every quarter when the temptation to add “just one more thing” becomes overwhelming. Slowly, almost imperceptibly, the plan can become a list of everything you’re doing rather than a filter for what you won’t do.
Then accountability: if you said this initiative would improve retention, did it? Most teams measure activity (”We launched the program”) instead of outcome (”Retention increased by X%”), and when results don’t materialize they explain away the gap rather than use it as data for the next decision.
Without clarity about what matters, discipline becomes impossible. Without discipline, accountability has nothing to measure. AI can draft something in minutes now—the differentiator is whether leaders build the muscle to sustain their decision when the easy path is to add rather than subtract, and smooth over rather than clarify.
2. The Softening Pattern
Someone writes an uncomfortable truth in a draft proposal—declining enrollment, shifting market position, mission drift—and the feedback comes immediately: “Can we soften this?”
The phrase gets revised, then revised again. “We’re losing ground to competitors who’ve solved problems we’re still debating” becomes “We have opportunities to strengthen our competitive positioning.” One sentence names what needs to happen, the other postpones the decision.
Notice the pattern in this example: three years of enrollment decline, accelerating, with families choosing competitors who built programs your school is still discussing. The data is clear, the trajectory obvious, but when someone drafts “enrollment erosion” the feedback comes back: “That language will make the board anxious.”
So it becomes “enrollment opportunity”—reframing losing students as gaining opportunity. The revised language doesn’t change the trend, but it makes everyone more comfortable with the status quo until the window for proactive response narrows.
We confuse clarity (which names what’s happening) with certainty (which promises outcomes we can’t control), and when strategic planning surfaces uncertainty we reach for softer language that feels less risky. The trap: certainty isn’t the opposite of anxiety, it’s the avoidance of anxiety.
Ask yourself: if this plan doesn’t create some discomfort when you read it, should you trust it?
3. When Speed Becomes Authority
AI can spin up bus routes and catchment maps in under half an hour, compressing what used to take a month into minutes. The model optimizes for time: eleven minutes saved per route looks efficient in the output until you map it to actual families and realize that eleven-minute savings adds a transfer a single parent working the dinner shift can’t manage. The efficiency is real, but the judgment is absent.
Speed quietly becomes authority when you’re not paying attention.
Numbers feel objective, models feel neutral, but every model embeds assumptions about what matters—and when you move fast, those assumptions don’t surface until they break something.
A pricing model can project revenue scenarios but misses the community backlash you’d see coming if you’d walked that parking lot a thousand times. Curricular analysis identifies efficiency gaps but won’t tell you which programs matter enough to protect even when the numbers don’t justify them.
The framework that works: human at the beginning (purpose and boundaries), AI in the middle (synthesis and speed), again human at the end (judgment and responsibility). You keep the “why” and the “so what” while letting AI accelerate the middle—and only the middle.
Most schools asked “Can AI do this faster?” in 2025, but few wondered “Who decides what AI isn’t allowed to decide?” The ones worth watching aren’t those with the best AI tools but the ones who decided explicitly what the model is not allowed to decide for them, and where human judgment remains non-negotiable even when the machine is faster, cheaper, and more confident.
Discuss at your next team retreat: Where is human judgment non-negotiable with your team—and does everyone know it?
4. The Boundary Problem
The distinction between “what” (board) and “how” (head) is intellectually simple—everyone nods at governance training. Then a major donor parent calls a trustee directly about the admission decision for their second child.
The trustee doesn’t use the script. Instead they take the call, express sympathy, promise to “look into it,” and show up at the next meeting asking in a sidebar why Emma wasn’t admitted when the family has given so generously.
The four-step framework we recommend (credit to Damian Kavanagh at MISBO) for trustees isn’t complicated: Empathize, Explain, Redirect, Inform. What’s hard is using it when their neighbor is calling, when it’s a donor who funded the new gym, or when it’s the friend from book club.
Governance training teaches the script, but practice is using it when the cost feels personal. Boards that navigate this well practice the discipline in low-stakes scenarios until it holds when stakes are high, building muscle memory for staying in the role even when key relationships are on the line. The ones that struggle treat each incident as unique—”this situation is different, this donor is special”—and never build that discipline.
Use this question with your board: when was the last time they all stayed in their lane even when it felt uncomfortable?
5. Optimization vs. Transformation
Hemingway on bankruptcy: “Two ways. Gradually, then suddenly.”
Organizations changing the model don’t announce it as innovation—they quietly rebuild the foundation while everyone else renovates the kitchen, and by the time it’s obvious they’ve changed something fundamental the window for others to follow has narrowed.
What gets called “transformation”: Centers for Innovation that innovate nothing, Institutes for Future Learning using pedagogy from the 20th century, micro-schools that keep the same instructional model in a smaller building, and auxiliary revenue experiments that never reach scale because they’re structurally incompatible with the core business model. None of these are “bad” ideas per se, they are just adjustments within the existing frame rather than changing the value proposition, relationship with families, or how education gets delivered.
Optimization makes your current model better, while real transformation builds a different model. The first extends your runway, and the second changes your destination.
Most find it hard sometimes to tell the difference because acknowledging you’re optimizing when the model needs transformation requires confronting uncomfortable truths about runway length and competitive positioning. Schools in the “gradually” phase keep optimizing—enrollment models built for a decade ago still govern decisions, tuition increases outpace family income growth by double digits, and what worked when information was scarce feels less and less compelling.
It’s easy to ignore gradual decline when you can still make budget. The “suddenly” arrives when it’s too late to build what you wish you’d started five years ago, and options have narrowed from “strategic transformation” to “crisis management.”
→ How will you know whether you are changing the model or adjusting within it?
What to Do With These Five Themes
Pick one good idea when you return from the holidays and don’t pursue it—just practice choosing first when the stakes are still manageable. Take your list of strategic initiatives and notice the euphemisms, every “opportunity” that’s actually a problem, every “strengthen” that avoids naming what needs to change, and then replace the soft language with clarity, even if it’s only for you and your team for now.
Write down three decisions AI is not allowed to make and make them explicit. Or, practice the governance script (Empathize, Explain, Redirect, Inform) with your trustees in a low-stakes moment in January so the muscle memory is there when a major donor calls this spring.
And, answer honestly: are you optimizing or transforming? Not what you wish you were doing, but what you’re actually doing.
The organizations that increasingly thrive will be led by teams and boards who build the muscle to sustain clarity when consensus feels safer, discipline when adding feels easier, and accountability when explaining the gap away feels more comfortable.
You already know what to do—the work is building the strategic muscle to do it.
Thanks for reading. See you in January.