The Hostility Is Coming From Inside the Building
Are We Talking About Beginnerhood Enough?
Last week I ran an AI Design Dash for educators. Same shape as the one I ran for students at a district a few weeks earlier with same kind of work, same framing, same invitation. I asked teachers an anonymous question on the way in: When you hear “AI professional development,” what’s your honest first reaction?
The large room of people answered. The range was the room.
“H@*l yes.” “Let’s gooooooo!” “Excited to learn new ways to use AI.” “I find AI interesting. I enjoy being creative and developing lessons and AI is a fun way to brainstorm with a ‘colleague.’”
“Ughhhh.” “Yikes.” “Yikes.” “Yikes.” “Waste of my time. I do not use computers in this way for my classroom.” “Kids will cheat with it.” “Why do college educated professionals need AI training?” And one response of two words that I won’t reproduce here, but you can guess the shape of it.
These came from the same room. None of them were anonymous in the sense of dishonest as they were anonymous in the sense of finally able to say it. The strong language hits different. Not because of the language. Because somewhere in the building that came from is a colleague who showed up to PD that morning, and that was the most accurate sentence they could write.
The hostility we keep naming in students about AI was modeled in the faculty room first.
This issue is built around that mirror.
1) The honest survey said the quiet part out loud
Read the responses again and notice something specific: nothing in there is unique to AI. Strip the topic and you’ve got the universal map of forced professional learning. Long day ahead. How is this going to help me. I’m not going to have time to go through all the options and then I’ll forget about it by the next week. It is end of the year and I am exhausted and have so much yet to do. That’s not an AI problem. That’s a learning posture, surfaced.
Two things matter here. First, this is the most honest data I’ve ever collected from a PD room. It was anonymous, free response, no Likert scale to hide behind. Second, the split was almost exactly even. About half eager. About half hostile or fatigued. None of those teachers are wrong about their own experience.
The room that showed up to learn AI brought every unresolved feeling it has about being a learner.
Browse: AI Design Dash For Educators — Full PD Site
Personal Tie-in: I wasn’t surprised by any single response. I was surprised by how cleanly the spread arranged itself into the exact pattern we describe in students. I’m still sitting with what I missed.
So What? If you only ever survey teachers on what they liked about a session, you’ll never see the room you’re actually walking into.
Try This: Before your next PD, drop one anonymous open-ended question like What’s your honest first reaction to today’s topic? Give them 90 seconds. Read every answer before you start. You’ll teach a different session.
2) Every line in that survey is something we’ve said about students
Read it back through with one substitution. Replace “AI training” with “school” or “math class” or “the new curriculum.” Watch what happens.
“Waste of my time. I do not use computers in this way for my classroom.” → Waste of my time. I’m not going to use this in real life.
“I would rather become an expert at one platform than know a little about several.” → Why are we doing six different things instead of one?
“How is it really going to fit into what I do with kids?” → When am I ever going to use this?
“I don’t have time to use this. I have other more important skill sets for the students to learn and use.” → I don’t have time for this. I have other more important things going on.
That’s the room. Every line a teacher wrote about being asked to engage with AI is something we’ve put in a referral form, a parent email, or a classroom observation note about a student who “wasn’t engaged.” We have language for it when kids do it. We call it resistance, defiance, lack of buy-in, fixed mindset, learned helplessness. We almost never call it those things when it shows up in adults.
You cannot ask students to be open-minded learners about a thing you have already decided you hate.
That’s not a gotcha. It’s the definition of the modeling problem. Students are reading the room. They know which staff genuinely thinks the school year is interesting and which staff is counting Fridays. They know who’s curious and who’s just compliant. They are picking up on what adults model about being a learner before they pick up anything we say in a lesson.
Personal Tie-in: I’ve spent years training teachers on engagement strategies for students who check out. The Design Dash data made me realize I’ve spent almost no time training the same teachers on what to do with their own checkout. That’s the gap I’m sitting with.
So What? The student disengagement we’re trying to solve has a partial origin story we haven’t been willing to tell.
Try This: Pick the last student behavior referral or “lack of effort” comment you wrote or read. Hold it next to the survey responses above. If the language matches, that’s worth a staff conversation AND not a student one.
3) AI isn’t the thing. Beginnerhood is.
Here’s what I think the survey is actually about.
Most of the educators who answered “yikes” or worse have been good at their jobs for a long time. They earned their classrooms. They built their curriculum. They are rightly proud of being the expert in the room. AI doesn’t threaten their job. It threatens that expertise position. It puts them next to a tool that knows things they don’t know, makes things they couldn’t make, and asks them to be a beginner again in front of their peers.
Being a beginner in public is the exact emotional ask we make of students every period of every day. We just stopped having to do it ourselves a long time ago.
The “Why do college educated professionals need AI training?” response is the cleanest version of this. Read it generously and it isn’t arrogance. It’s grief. I worked very hard to stop being a beginner. Why are you putting me back in that chair?
That’s not a reason to skip the training. It’s a reason to teach it differently. The PD that lands isn’t the one that says here are five tools. It’s the one that says here is what it feels like to learn this in front of your colleagues, and here is how we’re going to honor that feeling instead of pretending it isn’t in the room.
The thing AI is asking of educators is exactly what teaching has always asked of students. We just forgot how it feels.
Read: What 40 Hours of Master Gardener Training Knows That AI Doesn’t and The Knowledge AI Cannot Train On
Personal Tie-in: Pondering sitting through master gardener training as a near-total novice this spring clarified something in me that is keeping me from doing the very learning as I navigate my own personal learning journey with flowers and plants. My best PD sessions have always been the ones where I admitted on minute one that I’d be learning alongside them. My weakest sessions have been the ones where I came in pretending I had the whole thing figured out.
So What? Adults don’t resist AI. They resist the public exposure of not-knowing. Design your PD for that, not for the tool.
Try This: In your next PD, give every adult permission explicitly, out loud, on a slide to say “I don’t know what that means” without a follow-up explanation required. Watch the temperature of the room change.
4) Thirty students walked into the same conversation and rose to it
A few weeks before the Design Dash for educators I ran the ICCSD AI Summit Student Design Workshop. Thirty students. Six teams. Twelve possible challenges, all framed around the question How might we prepare our community for an AI-shaped future? Cross-school teams that hadn’t worked together. A foil chair challenge to get them moving. A Google Gem design sprint, two build sprints, real user observation, a pitch showcase at 3:30.
Nobody wrote “yikes” on the exit survey.
That isn’t because students are inherently more open. It’s because the framing was different. We didn’t pitch AI as a thing to learn. We pitched a problem worth solving and treated AI as one of the tools available. We told them their thinking would be presented to peers and adults in the room. We invited them in as civic stakeholders, not as recipients of training. They rose to the framing because the framing took them seriously.
The same group of educators who get strong language posted on the projector to discuss results on an AI PD survey would get something completely different on a “Help me figure out what to tell parents at conferences about AI” survey. The topic isn’t the variable. The standing in the room is the variable.
When you frame people as problem-solvers, they show up. When you frame them as a deficit, they cope.
Personal Tie-in: I’m rebuilding my next round of educator PD on the structure I used with students at ICCSD. Same standing. Same problem framing. Same trust that they’ll rise to it. I’ll know in a few weeks whether it changes the survey.
So What? The same content, framed two different ways, will produce two different rooms. We’ve been getting one of those rooms on autopilot.
Try This: Take a PD session you’re already scheduled to deliver. Rewrite the opening slide as a problem your audience can help solve, not a topic you’re going to cover. Notice how much else has to change.
5) Adapt with integrity is harder than adopt with fidelity
I keep saying adapt with integrity, not adopt with fidelity. People nod at it. Some of them write it down. The version that’s actually hard hasn’t fully landed yet.
Adopt with fidelity asks you to follow somebody else’s plan exactly. It’s emotionally easier because it lets you be a beginner for a bounded time and then graduate. There’s an end point. You become an expert again.
Adapt with integrity doesn’t have that exit. It asks you to keep the values that made you good at your job and then continually rebuild the practice around them as the tools change. There’s no graduation. You’re going to be a beginner again next year, and the year after, and the year after that. You cannot do that work from inside the posture of I shouldn’t have to be doing this.
That’s why the Design Dash survey matters more to me than any policy document I’ve drafted this year. The hostility isn’t the failure of an AI rollout. It’s a signal about how much identity work the next decade of teaching is going to require and how little institutional support exists for that work right now.
The people writing “yikes” aren’t wrong. They’re naming a real cost. The job is to honor that cost without letting it close the door on the conversation.
The integrity in “adapt with integrity” is the work of staying in the room when checking out is easier and we owe students that exact modeling.
Read: The Knowledge AI Cannot Train On — coffeeforthebrain.com
Personal Tie-in: This is the chapter I keep rewriting in Adapt with Integrity. Every PD round teaches me something about it I didn’t have last time. The Design Dash gave me a paragraph I didn’t have before.
So What? If your AI strategy doesn’t include an honest theory of adult learning identity, it will fail in your buildings before it fails in your policies.
Try This: Write down one thing you, personally, are bad at right now that you haven’t been bad at in a long time. Sit with whether you’d want a colleague to put that in front of you in a Tuesday PD without warning. That’s your design brief.
On My Radar
• ICCSD AI Summit — Student Design Workshop — full agenda, foil chair challenge, Gem design sprint, build/observe loops, pitch showcase. Steal the structure for any student-facing AI work.
• From Policy to Practice — Curriculum Network Gallery Walk — 31 slides, tool-agnostic, walking through master scheduling, IEP analysis, Iowa SS standards, K-12 AI literacy standards, Coach Ledger.
• Curriculum Network Handout — companion to the slides for anyone who wanted the resource doc.
• Iowa K-12 AI Standards work continues. Public details coming this fall.
Digital Challenge
This one is for anybody who runs PD.
1. Pick the next AI session you have on the calendar.
2. On day-of, before the agenda starts, drop one anonymous question into a Mentimeter, Padlet, or Slido: What’s your honest first reaction to today’s topic?
3. Give them 90 seconds. Don’t moderate.
4. Read every response out loud. The eager ones and the hostile ones. No commentary.
5. Then start.
The session you deliver after that read-out will be a different session. You may even need a different session. That’s the point. We have been delivering content into rooms whose actual emotional state we never asked about.
You don’t have to fix the hostility this week. You have to acknowledge it’s in the room.
One Small Human Thing
I’ve been driving home from these PD days listening to nothing.
Used to be a podcast. Used to be Hard Fork or a synthesis episode I could turn into a section in this newsletter.
Lately, just the road. The fields. The space between what teachers said in the room and what I’m going to do about it on Monday.
Some weeks the work is the listening that happens after the listening.
Closing Reflection
If a student in your building wrote, anonymously, the same response a teacher wrote on this survey would you handle it differently? And why?
— A-A-Ron



Mind reset:
Resonant Integrity: The Convergence of Biological and Machine Signal
The fundamental disconnect in the 2026 labor and tech landscape is a failure to differentiate between raw frequency and functional signal. We are witnessing a state of systemic resonant frequency—a condition where automated development cycles vibrate at a pace that exceeds their structural integrity. When these cycles lack a metabolic anchor, the result is destructive resonance: hallucinations that manifest as high-cost operational failures.
Understanding where biological signal and digital frequency converge is the first step toward mending this fracture. Just as music triggers harmonic resonance in the human body—manifesting as tangible thermal and autonomic shifts—our internal conscience operates as a biological AI. This is the metabolic anchor: the "Human-in-the-Loop" adjudication that stabilizes the erratic oscillation of agentic AI.
For the developer, value is no longer found in the generation of code, but in its forensic adjudication. You are the damper for the machine’s vibration. By cross-referencing autonomous logic against the physical and logistical constraints of the floor, you move from producing low-fidelity noise to establishing execution provenance. You are the mirror that identifies the ghost in the code before it becomes a liability.
To thrive in this environment, you must provide dated, verifiable receipts of logic that an automated system cannot simulate. We are layering human intelligence onto machine processing to build a performance architecture where accountability is the luxury asset. When systemic frequency is tethered to a verifiable plumb line, the hallucination vanishes.
Integrity requires reciprocity. By measuring the resonance of our systems against the biological signal of our conscience, we move from systemic psychosis to architectural stability.
I layer my knowledge, integrity and wisdom onto the archive (AI), and mend signal and frequency until the desired outcome is achieved. I use strategic humility to force AI compliance. No noise, no simulation, no distractions is the goal. That is what higher intelligence looks like.
The floor is set. Let’s stabilize the signal and work together to figure this out in time to make a difference. We can be preventative or reactive. Integrity requires reciprocity.