The AI Teacher Lounge

Hey friends, Scott here.

What a busy but productive week it has been here at The AI Teacher Lounge and StackFord.

Last week, we officially launched our educator-focused AI newsletter and our first podcast. This week, our mailing list has doubled, and I am happy to announce that our new website is live: https://theaiteacherlounge.com/

I continue to leverage AI tools heavily, but they are just that: tools. They allow me to get tasks and projects done in a fraction of the time it would have taken me just a year ago. Planning, writing, organizing, building resources, creating podcast materials, updating websites, and keeping all the moving pieces moving. AI has not replaced the work. It has helped me get more of the work done.

That is why I created The AI Teacher Lounge. I want to share with you, my fellow educators, the latest AI tools, ideas, and workflows that can help you do the same. Not because every educator needs to become an AI expert, but because many of us could use practical ways to save time, build better materials, and keep up without feeling like we are drowning in another new thing.

The weekly podcast, which you can find on YouTube and SoundCloud, is my hands-on demonstration of the AI tools I am using in my own workflow.

• YouTube: https://youtube.com/playlist?list=PLBZXgcHY-otBoEEfnZYSz6SjOLqQo0uA2&si=aXnKqnLpKIMWW69o
• SoundCloud: https://soundcloud.com/the-ai-teacher-lounge

Thank you for your continued support, and be sure to share the love with your fellow educators by sending them information about our Lounge.

So now grab your coffee. Let’s look at a few things worth knowing this week, without pretending every tool announcement is a thunderclap from the future.

Source: eSchool News

Link: https://www.eschoolnews.com/innovative-teaching/2026/06/09/pbl-shifted-the-way-students-see-math/

What happened: An eSchool News article highlights a project-based learning activity where students designed backpacks as a way to apply math in a real-world context. Instead of treating math as a pile of separate skills, the project gave students a reason to measure, plan, revise, explain, and use math as part of making something.

Why educators should care: I’m cheating a little with this one because it is not really an AI story. But it belongs here because it reminds us what good AI use should support: better learning design. AI can help generate scenarios, constraints, examples, and reflection questions, but the real win is still the learning experience we build around it.

What to watch or try next: Think about one abstract skill you teach. Then ask: what could students design, build, plan, compare, or explain that would make this skill useful?

Source: Shake Up Learning
Link: https://shakeuplearning.com/blog/amping-up-literacy-instruction-magicschool/

What happened: Shake Up Learning shared a literacy-focused session on using MagicSchool to support early childhood and elementary reading instruction. The session looks at ways teachers can use the tool to generate higher-level questions, decodable texts, vocabulary-based content, and scaffolded supports.

Why educators should care: For literacy teachers, especially in the early grades, the prep work can get very specific very quickly. You may need a decodable passage, a vocabulary activity, a question set, and a differentiated version of the same idea before your coffee has even committed to helping you. AI can be useful here as a starting-point generator.

What to watch or try next: Do not treat the output as finished just because it came out clean. Read it like a teacher. Check the vocabulary. Check the reading level. Check whether the questions actually match the skill you are teaching. AI can draft. You still decide.

Source: Tech & Learning
Link: https://www.techlearning.com/technology/customer-service-matters-in-educational-it-support

What happened: Tech & Learning published a reminder that educational IT support is not just about uptime, ticket closures, cybersecurity rules, and system reliability. Those things matter, but the article argues that technology support is also a service profession. Communication, empathy, clear timelines, and plain language shape whether teachers see IT as a partner or a barrier.

Why educators should care: This one hits home for anybody who has ever lost access to a system five minutes before class. When tech support is responsive and respectful, teachers are more likely to ask for help early. When support feels cold, confusing, or dismissive, people start creating workarounds. And in schools, workarounds can become a whole circus.

What to watch or try next: If you are in a leadership or support role, look at your tech process from the teacher side. Is it clear? Is it respectful? Does it help people get back to teaching, or does it just close tickets?

MagicSchool is not new, but it keeps showing up because it is built around education workflows instead of making teachers start from a blank AI chat box every time.

This week, the literacy use case stood out. A teacher could use MagicSchool to draft comprehension questions, create vocabulary practice, generate a decodable passage, or create differentiated versions of a text. That does not mean the tool replaces reading instruction. Please do not hand the steering wheel to a chatbot and hope phonics works itself out.

The possible win is speed. If MagicSchool gives a teacher a usable first draft, that teacher can spend more time refining, adjusting, and teaching instead of staring at a blinking cursor.

The caution is the same one we should use with any AI tool: check the output. For literacy especially, small mistakes matter. A passage can look fine but miss the sound pattern you intended to practice. A question can sound smart but not actually measure comprehension. A vocabulary activity can be cute and still be useless.

My take: worth trying if your district allows it and you have a specific task in mind. Start with teacher-created content and avoid putting student information into any tool unless your school has clearly approved it.

I want to introduce you to one new feature of the newsletter: What I’m Reading & Watching.

Each week, I’ll share one resource I use to keep up with AI. In all my time working with computers, I have never seen anything evolve as quickly as AI is evolving right now. It is exciting, but it can also be a lot.

So, for those of you who want to learn more without trying to drink from the entire internet firehose, this section is for you. One resource per week. That’s it. I’ll only highlight resources I actually use and find valuable as I continue learning, teaching, building, and trying to keep up with this field myself.

For the first recommendation, I can think of no better place to start than The AI Daily Brief.

I can listen to an entire episode on the way to the office and get useful AI news, updates, and insights before I even get to my desk. It has become one of the regular ways I stay current.

Give it a listen. I don’t think you’ll regret it.

Try using AI as a “real-world project starter.”

Pick one skill you are already teaching. Not a brand-new unit. Not a massive redesign. Just one skill.

Then use this prompt: “I teach [grade/course], and my students are learning [skill or concept]. Give me three simple real-world mini-project ideas where students would need to use this skill. Each idea should be doable in one class period or less, require minimal supplies, and include one reflection question students can answer at the end.”

The key phrase here is “mini-project.” We are not building a six-week museum exhibit with district approval, grant funding, and twelve color-coded binders. We are looking for one small way to help students see where the skill lives outside the worksheet.

• For math, it might be designing a backpack, planning a garden, comparing phone plans, or estimating materials for a small build.
• For literacy, it might be writing product descriptions, creating a short public service announcement, comparing two versions of the same message, or revising instructions so another student can follow them.
• For CTE or technology classes, it might be designing a troubleshooting checklist, planning a simple network layout, or explaining a technical process to a non-technical audience.

Let AI give you the rough ideas. Then you do the teacher work: choose the one that fits your students, your time, your room, and your sanity.

Here is where I keep landing with AI in education: the tool is not the lesson.

The tool can help. It can absolutely save time. It can give you a cleaner starting point than “I guess I’ll make this from scratch at 10:47 p.m. while questioning my life choices.” But the lesson is still the lesson. The teacher is still the adult in the room. The learning still has to make sense.

That is why the backpack math story matters. Students were not just doing math because page 142 said it was time to do math. They were using math because the project required it. That is the part we should pay attention to.

AI can help us build more of those moments. It can generate scenarios, constraints, examples, non-examples, reflection questions, rubrics, reading passages, and extension ideas. That is useful. But if we only use AI to make faster worksheets, we are missing the bigger opportunity.

Same thing with MagicSchool. I like the idea of a literacy teacher using AI to generate a first draft of questions or a decodable passage. That could save real time. But I do not want teachers thinking the AI output is automatically instructionally sound because it looks polished. Polished and correct are cousins, not twins.

And the Tech & Learning article on IT support fits here too. Technology works best when it reduces friction. That is true for AI tools, help desks, learning platforms, and classroom devices. If the tool adds confusion, creates more checking, or makes teachers feel like they need a second job just to manage the first one, then it is not helping.

So my challenge this week is simple: do not start with the tool. Start with the learning problem.

What do students need to understand? Where do they usually get stuck? What would make the skill feel real? Then ask whether AI can help you build that moment faster or better.

If the answer is yes, great. Use it.

If the answer is no, close the tab and move on with your life. That is also good instructional design.

This week in StackFord, I’ve been thinking a lot about how to make abstract technology concepts feel more concrete for students.

That is one of the reasons I keep building labs, simulations, checklists, and classroom-ready activities into the Tech+ curriculum. A student can memorize a definition for networking, operating systems, databases, or security, but that does not mean the idea has landed. Sometimes they need to click through it, build it, break it, troubleshoot it, or explain it to someone else before it becomes real.

The bigger takeaway for teachers is this: abstract content needs a handle.

A project gives students a handle. A lab gives students a handle. A scenario gives students a handle.

Sometimes even a well-written AI prompt can give teachers a handle when they are trying to turn a dry objective into something students can actually use.

That is the kind of AI work I care about. Not flash. Not noise. Just better starting points for real teaching.

Gratitude and accountability can sit at the same table. Honestly, they probably should.

See you next time in The AI Teacher Lounge.