Beyond Free Tools: Rethinking Partnership in Ed Tech

When I was in the classroom, my approach to ed tech was simple: find the best tool I could get my hands on, make sure it was free, and put it in front of students as quickly as possible. If it worked well, I talked about it. I shared it with colleagues. I presented on it. I advocated for it without hesitation.

And ed tech companies understood that dynamic long before I did.

They knew teachers were the entry point. If we loved something, we would champion it. If enough of us adopted a free version, that usage could later become a compelling story for district-level conversations. As I transitioned to a tech coordinator role, I began receiving the cold emails and introductory calls that followed a familiar pattern: “I’m your district representative for ___.” Then, almost predictably, “I could tell you how great our product is, but wouldn’t you rather hear what your teachers think?”

What followed was often a detailed report showing adoption numbers that exceeded what I would have guessed. Sometimes there were names. Sometimes quotes. It was presented as evidence of organic enthusiasm, and in many cases it probably was. But it was also data being strategically gathered and positioned.

For a long time, I simply assumed that was how ed tech worked.

The Shift From Tools to Trust

What I’ve come to understand over the last sixteen years, though, is that the tools themselves are only part of the story. The real differentiator is relationship.

Relationship is not a conference dinner or a branded backpack full of swag. It’s not a free webinar that was already on your company’s marketing calendar. It isn’t even early access to new features. Those things can be pleasant, but they aren’t partnership.

The kind of relationship that actually matters in this work shows up in quieter, more consistent ways. It’s the support representative who remembers the nuances of your district and follows up without being prompted. It’s the engineer who takes a recurring complaint seriously enough to explore a fix. It’s the trainer who understands your instructional goals instead of simply walking through a slide deck. It’s a salesperson who knows when to suggest something new and when to say, “This probably isn’t right for you right now.”

That kind of attentiveness doesn’t happen by accident. It reflects something deeper about the company’s identity and leadership. In those cases, partnership feels embedded in their culture. You can sense that they value long-term trust more than short-term wins. Those are the companies you find yourself wanting to work with, even when they aren’t the least expensive option on the market. Over time, the relationship becomes part of the value.

When Partnership Takes Work

There are also companies where that depth of connection is possible, but it takes effort. We’ve worked with vendors where turnover disrupted continuity, where customer success managers were stretched thin, or where internal shifts changed the tone of the partnership. Sometimes investing time in those relationships pays off. You build shared understanding. You navigate challenges together. Other times, despite best efforts on both sides, it never quite solidifies.

In those situations, the strength of the product has to justify the energy required to maintain the partnership. And when renewal conversations arise—especially when pricing increases in ways that feel abrupt or unclear—the absence of relational capital becomes very noticeable. What a company pours into you over time shapes how confidently you advocate for them in return.

The Transactional Reality

Then there are what I think of as “as-is” companies. They may offer a powerful product or operate at such scale that personalization isn’t realistic. You submit tickets. You wait your turn. You adapt to their roadmap rather than contributing to it. The exchange is transactional, and everyone understands that.

Sometimes that’s simply the nature of the product. Sometimes it’s a strategic choice. Sometimes you see companies you love shift to this model and you are acutely aware that there has been a shift in strategy by the leadership (this is hard to swallow). In either case, you approach those relationships differently. You don’t confuse access with partnership.

Advocacy for the vendor is rare in these situations. Unless the vendor cultivates some type of active user community and incentives for educators to actively participate, this becomes the type of company you kind of roll your eyes at as a customer. Yes, I’ll do business with you. Not because I want to, but because you are the only game in town for this particular product. It is similar to how most of us feel when we have to pay our utility bills.

A Broader Lens for Teachers and Leaders

If you’re a classroom teacher, I don’t share this to discourage exploration. Free tools can be transformative. Innovation often starts there. But I do think it’s worth recognizing that there’s a larger ecosystem at play beyond “free for me.” Adoption has ripple effects. Data has direction. And relationships—whether present or absent—matter more than we sometimes acknowledge.

If you’re in a district-level role, the reflection shifts slightly. What kinds of companies are we aligning ourselves with? Do they understand our context? Do they respond when things break? Do they grow with us? Or are we simply managing subscriptions and usage reports?

I don’t pretend to have a neat formula for evaluating all of this. What I have is sixteen years of watching patterns emerge. The longer I work in this space, the more convinced I am that technology decisions are rarely just about features or pricing. They are about people. They are about responsiveness. They are about trust.

And in education—where the stakes are always students—trust is not a small thing.

Presenting With AI: What Elementary Students Taught Me About the Future of Work

Last week, I did something that I didn’t expect to enjoy as much as I did.

I co-presented with AI.

More specifically, I co-presented with Gemini, using an iPad and the Gemini app, during an elementary school Careers Day event. Whole classes rotated through, and I had about a half hour with each group. My goal wasn’t to “teach AI,” exactly. It was to help students start developing the kinds of human skills they’ll need in a future where AI tools aren’t a novelty, but a daily co-worker.

And what happened during those sessions shifted something in me. Because once you’ve presented with AI, you can’t unsee what’s coming next.

The Real Focus Wasn’t AI… It Was the Human Skills Behind It

When people hear “AI in schools,” they often assume the conversation is about tools. But the tools are the easy part. The real work is building the human capacity to use those tools well.

This is actually something we’ve been very intentional about in our district. We use the skills outlined in the latest World Economic Forum report as one of our key drivers for identifying what students need to learn to be successful in future careers—especially careers we can’t even define yet. The future of post-secondary education feels uncertain. The way people learn and prepare for careers feels uncertain. But the skills highlighted by the WEF are the kind of skills we can all agree are worth developing in classrooms with confidence.

So instead of focusing on Gemini as the star of the show, I built the session around the skills students will need to become functional, productive humans in an AI-supported world. Skills like communicating with clarity and purpose, using strong vocabulary, thinking critically, planning before acting, and understanding when to delegate tasks to technology versus when to do the thinking themselves.

I also wanted them to see that creativity and reflection are not “extras.” They’re essential. If AI can do the basic tasks faster, then the human advantage becomes our ability to think in diverse, meaningful, and original ways.

Obviously, I didn’t present these as a formal bullet list to third graders. But these themes were embedded in everything we did.

The Setup: Gemini as Our Onboard Ship Computer

To make the experience engaging and memorable, I built a simple narrative. I pre-crafted a prompt for Gemini ahead of time and gave it a role: Gemini was our onboard ship computer, helping us navigate our spacecraft on a journey to a galaxy far away.

Its job was to hold me accountable to clear and concise communication, serve as a “tour guide” to the stars, and act as a co-teacher by helping students understand how to interact with AI effectively.

In other words, Gemini wasn’t just answering questions. It was part of the experience. And it worked.

A Powerful First Step: Asking Permission to Be Imperfect

Before we even started, I asked the students for something important. I asked their permission for this to not go perfectly. I told them we were trying something new, and that experimentation sometimes comes with glitches, awkward moments, and learning as we go.

That wasn’t just a throwaway comment. It was modeling.

Because if we want teachers and students to take risks with new tools, we have to normalize what it looks like to be a beginner again. I quietly hoped the adults in the room heard it too.

Gemini Was Great… Until It Wasn’t (And That Was the Lesson)

Gemini performed really well overall. But there were a few slowdowns and glitches, and the kids noticed immediately. Of course they did. They’re sharp, and they don’t miss a thing.

Instead of trying to cover it up or rush past it, we leaned into it. It became an authentic moment to reinforce something I said throughout the session: we are the captains of our ship. The AI is a tool. The human stays in charge.

If the AI gets confused, stalls, or goes off topic, we don’t panic. We redirect. We adjust. We lead. That moment might have been more valuable than anything Gemini said all day.

The Camera Feature Changed Everything

One of the most powerful features of the Gemini app was the ability to turn on the camera—our ship’s “visual sensors.” This turned into an unexpectedly fun and meaningful part of the experience.

Gemini could see the kids. It could see them dancing, moving, waving, and reacting. And suddenly the room felt more alive. The AI wasn’t just a voice answering questions—it was interacting with what was happening in real time.

We even did a little experiment. I held up an image that the students could see, but Gemini couldn’t. The kids described it, and Gemini had to guess what it was. Then, after it guessed, we turned the camera toward the picture so Gemini could “see” it.

The students loved it. And honestly… I did too.

The Moment That Hit Me: I Was Presenting With AI

When I first played with ChatGPT, I never imagined a moment like this. But now that I’ve experienced it, I can’t unsee it. It was genuinely surreal—in the best way. I wasn’t presenting about AI. I was presenting with AI.

Gemini would take over after I asked a question, and while it spoke, I could walk around the room, observe students, interact, and read the energy of the class. It felt like having a co-presenter—except I had full control. And unlike a human co-presenter, I could cut Gemini off mid-sentence and take the floor back instantly.

That alone was a strange new kind of power. It made me realize that AI isn’t just changing what we teach. It’s changing what it means to present, facilitate, and lead learning.

What the Kids Revealed About AI Use Was Eye-Opening

I asked a simple question during the session: “Who here knows what AI is?” Every single student raised their hand.

Then I asked: “Who here has used AI before?” Every single hand stayed up.

100%.

Now, I’m not claiming this is a perfectly scientific sample. It’s possible the environment or context created some bias. But still, the numbers were much higher than many educators want to admit. Kids are not waiting for adults to catch up. They’re already living in the world we’re still debating.

What surprised me even more was how many students casually mentioned that their parents use AI regularly too. Several kids described hearing about it at home, watching parents use it, or even having parents show them what it can do. And this wasn’t just parents in tech jobs or office environments.

One student told me his dad is a professional welder and uses AI regularly to help him figure out how to do parts of his work.

That moment stuck with me. It was a reminder that AI isn’t quietly “on the way.” It’s already embedded in everyday life, and kids are watching it unfold in real time.

They Also Struggled to Explain What AI Actually Is

Even though every student said they knew what AI was, many struggled to describe it clearly. They mixed it up with robots. They described it like it was a person. They assumed it had feelings, a life, a job, a family, a home somewhere.

So we had to talk about it directly. AI isn’t a person. It doesn’t have emotions. It doesn’t “live” anywhere. It doesn’t care if you’re happy or sad. It is a tool—an advanced computer system designed to help humans do work.

And that distinction matters. Because if students don’t understand what AI is, they’ll either fear it, worship it, or trust it too much. None of those outcomes lead to healthy use.

One of the Funniest Moments Was Also One of the Most Telling

At one point, Gemini started talking a little off-topic. So I cut it off. Kind of abruptly. I redirected it and tightened up the conversation.

And the kids lost it. They laughed—an audible guffaw—because they couldn’t believe I was being strict with the AI.

It was funny, but it was also revealing. It showed how quickly kids assign personality and emotional weight to these tools. It reminded me that one of our jobs is to help students learn that they can be respectful, but also firm.

Because again, the human is the captain.

What I’m Taking With Me

This experience gave me confidence. Not just confidence that AI can work in a live setting, but confidence that it can actually improve engagement, improve learning, and create memorable moments that stick. It was useful. It was intriguing. It was fun. And it had impact.

I walked away thinking: If this can work with elementary students, it can absolutely work with adults. So I’ll be doing more presentations like this—more experiments, more co-teaching with AI, and hopefully more moments where students and teachers walk away not just entertained, but better prepared for the world they’re stepping into.

Because the future isn’t coming. It’s already sitting in the classroom.

And now I just hope my onboard ship computer can keep up.

The Most Important AI Tool We Gave Teachers Was Time

This week, our secondary educators participated in an in-person professional learning day designed to support the curricular work already underway across our district. Each content team was spending the day engaged in essential standards work—clarifying what matters most for student learning.

And that was the key.

When we carved out a 90-minute window for AI professional learning, we were intentional about not treating AI as the “new shiny thing” to bolt onto instruction. Instead, we rooted our work in the same anchor as everything else happening that day: standards, learning targets, and student outcomes. Because this isn’t about tools. It’s about what teachers can build when we give them space to think.

We didn’t have much time — but we made it count

We met once with each content area. Ninety minutes. In person. Fast-paced. We covered the essentials: prompt building, AI literacy, and how large language models work in plain language. We talked about the fact that these tools are prediction machines, not truth machines—and that they will confidently produce false information. We also addressed policy. We wanted clarity around what was allowed, what wasn’t, and what responsible use actually looks like in the classroom.

But the most important part of our sessions wasn’t the information we delivered. It was the time we protected. We carved out space for teachers to imagine the tools in their environment, with their students, teaching the content they love. We gave examples. We modeled. We left them with a recipe. Then we got out of the way.

Teachers didn’t need convincing — they needed permission

Before the day began, we knew one word would show up early and often: cheating. It’s one of the most persistent concerns educators have raised in recent months. And it’s a valid one. Teachers care deeply about authentic student work.

So we addressed it head-on. We talked clearly about the reality: our policy does not support AI being used for cheating, and teachers have every right to define when AI is not appropriate. But we also made something else clear: AI cannot be treated as a tool that is never allowed as a standing rule.

And something fascinating happened. Once teachers had clarity—once they had permission, clear answers, and an opportunity to see the tool used differently—the word cheating disappeared. In every session. The tone shifted from fear to curiosity.

What teachers did with time

Teachers didn’t need more slides (don’t worry — we had that part, too, for the mini-lesson). They needed a window to think, create, and collaborate. And the moment we gave them that window, they did what teachers always do: they started building.

Snapshot #1: “Wait… I could have students critique the AI.”

At one point, a teacher pulled me aside during work time and said:

“Oh my gosh. I could have my students critiquing the work the AI did. I had never thought of that.”

That moment mattered because it represented a shift away from seeing AI as an answer machine—and toward seeing it as a thinking partner. Critiquing AI output isn’t a shortcut. It’s analysis. It’s evaluation. It’s exactly the kind of cognitive work we want students doing more often.

There were other moments like this. Moments when teachers realized they did not have to do the work of translating every document for students if they taught students how to have the tools translate the document for them. They didn’t have to curate every resource into a NotebookLM and then share it with the students if they taught students how to create their own NotebookLM with the resources already provided.

And that has an impact on students as well. The idea that you have to put in the work, learn the tools, and be responsible for creating your own learning opportunities is something that will serve all students well in the future. The maid and butler of their learning environments has been let go. They have to learn how to survive and succeed, to do for themselves, and to make the most out of the tools and opportunities they are given. That will have a positive impact on student learning.

Snapshot #2: A team built a project-planning AI tool in real time

In another room, a group of teachers focused on a familiar student challenge: students often begin project-based learning without a plan, and productivity suffers quickly. So they built one. In our 7 minutes of work time on that tool, they literally had a working prototype. The powers of AI technology were in full display.

Using Gemini, they designed a project-planning “Gem” that could guide students through building a plan, organizing resources, identifying deadlines, and staying focused. In less than 90 minutes, teachers went from “What even is a Gem?” to creating something that could immediately support students.

Snapshot #3: Reflection feedback that changed student productivity

One teacher shared that he had already been using a Gemini Gem for weekly student reflections in his project-based learning environment. The results weren’t small.

He explained that the immediate feedback students received through the tool had shifted their productivity in a meaningful way. Students weren’t waiting days for feedback—they were getting real-time coaching they could apply immediately.

Not only was he able to share a success story, but he also grew a network. I noticed two other teachers meander over during work time to see his reflection gem in action. They weren’t from his school. They didn’t know the work he had been doing. And in about 8 minutes of work time, they made a connection and he felt seen for the idea he put into the room.

Bonus snapshot: A sassy AI conversation with Frida Kahlo

And then there was the moment that reminded us what learning really looks like. A teacher experimenting with Spanish prompts began challenging the AI’s colloquial language, pushing back on phrasing and tone, refining it, and correcting it.

He started imagining students having a conversation in Spanish with AI as Frida Kahlo. At one point, he got a little sassy with the AI, challenging it like a student would. It was funny—and also exactly what we want students to do: engage critically and push beyond surface-level answers. He was also now empowered to improve the AI bot, as he had learned to control it through prompt creation and iterative prompt generation.

The real takeaway: Teachers want to learn

At the end of each session, we were met with gratitude and enthusiasm. Teachers want to make an impact on students every day. They don’t show up to be ineffective. They show up because they care about kids and they care about doing the work well.

What we saw in these sessions was a group of professionals doing what teachers do best: imagining what’s possible. And they did it with a few free tools and a small amount of time.

AI training isn’t the point. Empowerment is.

The biggest success of our professional learning day wasn’t the tools we demonstrated. It was the space we protected. Because the most important AI tool we gave teachers wasn’t Gemini, or prompt structures, or a list of resources. It was time.

Time to think. Time to build. Time to reimagine learning.

And if 90 minutes produced this kind of momentum—imagine what teachers could do with more.