When I wrote “A Year in the Life of This Substack”, I described AI Edu Simplified as a space to make sense of a rapidly unfolding world: part notebook, part dialogue, part public thinking exercise. The work felt (and still feels) exploratory.
Two years in, this substack space feels different. The questions are no less urgent, but the frame has widened. My practice in this space has slowed (61 in the first year; and this marks the 20th for the second year) even as my conversations have multiplied. As a staging or home for my sense-making, I can see the shifts to make it more like an open room where I aspire to listen as much as I speak.
This past year as a whole was filled with lots of changes. It has brought new rhythms and new boundaries. I completed the dissertation; I stepped into a new position that focuses on AI in the teaching and learning space; I started doing more consulting work with leadership in higher ed with my partner.
A Side Note: On the topic of exploring, learning, and sharing, our work at Anchor Insights is leading to some fascinating conversations. One project we’re pursuing is thinking about different ways to support middle & lower-resourced institutions around how they operationalize AI. If you’ve got 20 seconds, would you consider completing this 4 question survey? We will be sharing the results back on the Substack.
The work of thinking publicly about AI is now intertwined with professional realities in which AI isn’t just a topic that connects to my full-time work but a daily responsibility. That means navigating two kinds of truth: what I learn through my broader collaborations across higher ed, and what emerges inside the collaborative circles of my current role.
That can be tricky (and that was anticipated). Writing here was simpler: observe, reflect, publish. Now I find myself pausing and asking what belongs to me to say and what is being co-created with others. The posts that make it through that filter are ones that still feel true in the broader sense, the kind of truth that’s grounded in pattern, conversation, and practice rather than in a single institution’s vantage point.
This recalibration hasn’t silenced the space, but it has changed its purpose. I post less often, but what I share tends to be more situated, such as interviews, workshop kits, and other artifacts that can be used directly by others. Instead of processing every idea that I’m chewing on, I’m sharing tools, templates, and voices. I like to think that the space has shifted from what I think to what we’re learning together.
Networked Reflection
The AI conversation can feel saturated for me; I can’t keep up with all the things, even of the authors and creators I absolutely love and look forward to learning from–never mind the ones that also come through their recommendations. There’s so much content, so much noise, that at times the most radical act feels like saying less.
That’s part of why I have leaned toward conversation. Interviews like the ones with Rob Nelson (Part 1; Part 2) and Lori Looney gave me a way to surface insight through dialogue rather than commentary (feel free to sign up for an interview). Each conversation reminds me of the message I routinely bring up in talks and workshops. This work isn’t solitary; it’s distributed, iterative, and often communal in ways that rarely show up in final publications.
I’m starting to wonder about how I can turn this in a space of networked reflection. That is, a space where meaning emerges through exchange. So much of my understanding of AI in education comes from other people: colleagues, faculty, students, and the many professionals working in or at the edges of policy, technology, and pedagogy. I’m finding meaning and value in amplifying that collective sensemaking and documenting what’s unfolding.
That’s also why I’ve been publishing workshop kits and useful frameworks here. It’s not only about accessibility but about extending the life of what happens in those workshops and talks. When I publish the materials here, the ideas are no longer bound behind the closed doors (or zoom links) of a single event or institution and further extend their usefulness as part of the commons.
Confidence, Uncertainty, and the Beginner’s Mind
In the last 3 years, I’ve spoken at close to a hundred events, from small faculty workshops to national convenings. That kind of repetition breeds confidence as there’s now a deep reservoir of examples, questions, and use cases that inform how I talk about AI. And yet, the more I do this work, the more I feel the need to hold onto and center the beginner’s mind, approaching each context as if I might have it wrong.
There’s a paradox at the heart of this moment. We need voices who can speak with clarity and guidance, and yet any claim to certainty risks becoming obsolete by the time it’s published. I hope to continue to navigate this by speaking with conviction but not finality. To remind myself and readers that all of this is still provisional, still unfolding.
Maybe that boils down to certainty about values, uncertainty about outcomes. I know that AI will continue to shape the conditions of teaching and learning. I know that educators need spaces to think aloud together. What remains unknown (and productively so) is how those two realities will continue to evolve in relation.
Growth and Focus
When I first began, I imagined the audience as faculty and educators navigating how to teach in an age of generative AI. That’s still true, but the audience has expanded. Since last year, this newsletter’s growth has nearly tripled to over 11,000 subscribers and followers. Increasingly, I’m hearing from department chairs, deans, provosts, librarians, instructional designers, industry leaders, and others who are shaping institutional responses.
The conversations here are now as also about strategy and big-picture exploration as it is about practice. It’s why I co-wrote and published this piece for EDUCAUSE about who gets to make policy and this one about the challenges of getting to an institutional policy. It meant thinking about what language invites participation rather than polarization, and about how to hold a mix of immediacy and longevity in what I’m creating here. I hope for this newsletter to remain grounded in the everyday realities of teaching while also offering something useful to those shaping policy and leadership decisions.
Over time, I’ve learned that not every idea belongs on AI Edu Simplified.
Roughly thirty drafts are sitting half-finished in my folder. I started these posts but grew too long, too tangled, or too reactive. Some were provocative for the sake of provocation, and that’s never quite felt right for this space.
Those abandoned drafts have taught me what the space isn’t: it isn’t a place for hot takes or dismissing large swathes of people grappling with AI, regardless of their position about it or positionality. It’s a space for discernment and finding language that helps others make sense of complexity. In year 3 of an AI discourse that seems to be dominated by extremes (evangelism on one end, existential fear and loathing on the other), I have tried to stay in the middle: skeptical, curious, open.
That stance echoes what I wrote in A Shill for AI…, where I unpacked a public exchange that pushed me to think about how we argue in good faith. The experience clarified something I still hold: that being critical of AI and being engaged with it are not opposites. The work is in keeping both lenses active at once and using critique as a form of care, not distance.
What the Substack (and y’all) Teaches Me
Maintaining this space alongside a more visible professional role has helped me to remind me what the act of writing does for me. There’s still a bit of brand maintenance that goes on (and has always been something I’ve done alongside my full-time work), but more important is that it has been a reflective discipline: a place to think in real time with a community that’s also learning.
That’s partly why I resonated so much with the exercise I described in AI Practice: Building My Quote Collection. That piece began as a technical workflow for digitizing my book annotations, but in hindsight, it was also a metaphor for this Substack itself: gathering fragments of insight, preserving them for reuse, and letting AI serve as a kind of intellectual amplifier.
There’s also something deeply pedagogical about this process. The transparency allows for others to learn and consider by proxy. It’s a practice I honed for nearly 15 years on my other blog. However, given the size and focus difference, it’s an opportunity to do that on a broader scale and one that comes with more critical eyes.
Appreciating the Readers
It’s been this past year that I’ve started to hear more from readers. Sometimes, it’s been in proxy through the “likes” or in the comments and the restacks. Othertimes, they tag me on other social media platforms to highlight a piece of mine. But increasingly, it’s in workshops, conferences, and the like where they take the time to tell me that they are readers or followers of my work. That’s always humbling because, inevitably, I’m also saying the same thing and fanboying over a variety of folks that I come into contact with in the same spaces. Those moments remind me that the newsletter’s reach extends far beyond its visible metrics.
I’m also grateful for the folks who subscribe and pay, despite every post being free and licensed with Creative Commons. That gesture of voluntary support in an open space feels like the clearest signal that the work has value. It’s an act of trust and solidarity, one that keeps me accountable to the ethos of making knowledge open, usable, and iterative–a through-line that has been present in my writing and speaking over the last 15 years..
Still, I don’t always know exactly what readers take from this space. That uncertainty is part of the ecology of online writing. What I can control is the invitation: the openness to conversation, the modeling of curiosity, and the occasional reminder that everyone reading is also a potential contributor to the larger project of understanding AI in education.
Collaboration as Next Chapter
As I’ve moved into doing more interviews (with a few more ready to go), I hope this space can be a platform for others’ voices. So many people are doing thoughtful, grounded work who may not have a home for it in traditional academic venues.
There’s so much interesting writing happening in hallway conversations, in Google Docs, in the margins of workshops. I’d love to surface those voices: faculty, instructional designers, administrators, librarians, students—anyone helping higher education make sense of AI from within.
As I look ahead to year three, I find myself returning to the same grounding principle that began this whole project: curiosity paired with care. The landscape of AI in higher education keeps changing, but the deeper work continues all the same. We’re trying to understand what it means to teach, learn, and lead in a world increasingly shaped by systems we can neither ignore nor fully control.
In that sense, this newsletter is still doing what it set out to do two years ago. The form has evolved; the purpose has deepened. It’s less about answers now and more about practices of writing, of sharing, and of thinking together in public.
If you’ve been part of that journey by reading, sharing, or simply reflecting alongside these posts, you have my gratitude. The next phase is about widening the circle. If you’ve got an idea, a project, or a question worth exploring here, reach out.
Final Note: This post was created with GenAI. I had it interview me about my thinking around what I wanted to say, I then provided it with past post examples to extract the style, and had it take a first go at a first draft to which I then edited. You can see the chatlog here if interested.
The Update Space
Upcoming Sightings & Shenanigans
AI and the Liberal Arts Symposium, Connecticut College. October 17-19, 2025
The AIs Go Marching On: Finding Our Way with AI in Education, NCFDD, October 24, 2025
EDUCAUSE Online Program: Teaching with AI. Virtual. Facilitating sessions: ongoing
Recently Recorded Panels, Talks, & Publications
The Opposite of Cheating Podcast with Dr. Tricia Bertram Gallant (October, 2025)
The Learning Stack Podcast with Thomas Thompson (August, 2025). “(i)nnovations, AI, Pirates, and Access”.Intentional Teaching Podcast with Derek Bruff (August 2025). Episode 73: Study Hall with Lance Eaton, Michelle D. Miller, and David Nelson.
Dissertation: Elbow Patches To Eye Patches: A Phenomenographic Study Of Scholarly Practices, Research Literature Access, And Academic Piracy
“In the Room Where It Happens: Generative AI Policy Creation in Higher Education” co-authored with Esther Brandon, Dana Gavin and Allison Papini. EDUCAUSE Review (May 2025)
“Does AI have a copyright problem?” in LSE Impact Blog (May 2025).
“Growing Orchids Amid Dandelions” in Inside Higher Ed, co-authored with JT Torres & Deborah Kronenberg (April 2025).
AI Policy Resources
AI Syllabi Policy Repository: 190+ policies (always looking for more- submit your AI syllabus policy here)
AI Institutional Policy Repository: 17 policies (always looking for more- submit your AI syllabus policy here)
Finally, if you are doing interesting things with AI in the teaching and learning space, particularly for higher education, consider being interviewed for this Substack or even contributing. Complete this form and I’ll get back to you soon!
AI+Edu=Simplified by Lance Eaton is licensed under Attribution-ShareAlike 4.0 International
Two years! Glad to see you going strong, Lance. I appreciate your reflections.
Thank you, Lance! Your intellectual generosity AND humility/beginner's mind, and unrelenting pursuit of growth have made this space a real gem! So fortunate you've been an early voice in AI in EDU and have helped center on humanity and shape it for the better!