Uploaded September 2026 | Updated September 2026, 1 day ago
After 200-plus episodes and a long stretch of silence, I'm back and the format has changed.
I've spent the last few years standing in front of rooms in K-12, higher ed, business, and industry, saying more or less the same thing: co-pilot, not autopilot(at least to start). Humans in or on or out of the loop. And somewhere in the hundreds of sessions I started to wonder whether I'd gotten really good at saying the things without actually doing them. Whether I'd become the guy with the metaphor(I feel like I have plenty of proof but imposter syndrome is real y'all).
So this season I'm going to stop describing it and show it. Every episode, I sit down with the tool I actually use and treat it as the guest in audio and video. You'll hear where it helps and where it gets things wrong, and where it tells me something about my own work I'd rather not hear.
What's in this episode
The four quadrants. Before you can have a real conversation about AI, you need to be able to say which kind of AI you mean. I walk through the framework I've found most useful: two axes — how deeply the tool is integrated into where you already work, and how much it does without a human in each step. That gives you four types.
Assistant — "I need answers when I ask." You prompt, you decide, you own it. This is the chatting quadrant, and it's where this episode lives.
Copilot — "Help me in the tool I already use." Gemini in Docs, Copilot in Outlook. It comes to you.
Autopilot — "Do this automatically for me." One narrow job, no approval each time.
Agent — "Figure out how, and do it for me." Goals, tools, limits — it picks the steps. I have one that cleans and sorts my desktop at 5:00 every morning.
The left half is productivity AI: a human still produces the outcome. The right half is engineered AI: the system produces it, and somebody still has to own it, monitor it, and answer for it.
Four reasons for the season. The flattening of "AI" into one word that means everything. The gap between people nodding at metaphors and then using the tools at a surface level anyway. The distance between theory-land and the reality of jammed lockers and fire alarms and a kid having a rough day. And a commitment to real pushback and unedited disagreement including with the machine.
What this is not. Not an interview with a person. Not a demo reel as no vendor is paying for this and I'm leaving in the parts that don't work. Not a claim that Claude has earned its opinions. The distinction matters and I'm not blurring it for a better episode.
Five unrehearsed questions. Nothing was pre-tested. Claude confirmed on the record that it hadn't seen the questions and hadn't been coached on how to answer.
What are you, in your own words, and what do people get wrong about you?
Based on how I actually work with you, what's my pattern, where do I lean on you well, and where am I lazy about it?
What's a task educators bring you constantly that you're genuinely bad at, and they don't notice?
When I push back, do you actually disagree, or are you performing disagreement because I asked for it?
What should teachers be more worried about than they currently are?
Three moments worth the listen
"Partial evidence, not a verdict." After Claude named a pattern in how I work, it put a caveat on its own read: that's how I show up in these conversations, not a verdict on me as a person. Real evidence, but partial. Which is exactly what we're failing to do with students adn this is a detection flag that becomes the whole case, and nobody asks what the kid was stuck on.
The two tests for real disagreement. Ask what would have to be true for it to be wrong; if it can name a specific condition, there's something underneath the agreement. Then push back on something it got right. If it folds instantly and thanks you for the correction, you just watched it choose your approval over the truth. The tell in both cases is speed.
Year three. The worry isn't cheating or job loss. It's that the tasks that felt like busywork were where teacher judgment got built. Writing your own lesson plan is inefficient and the inefficiency is where you notice this won't work for third period. Grading the stack is slow, and somewhere in it you spot four kids sharing a misconception, and that becomes tomorrow. Automate the tedium and you don't just save time, you remove the practice reps. The veterans already have theirs. It's year three that's exposed.
After 200-plus episodes and a long stretch of silence, I'm back and the format has changed.
I've spent the last few years standing in front of rooms in K-12, higher ed, business, and industry, saying more or less the same thing: co-pilot, not autopilot(at least to start). Humans in or on or out of the loop. And somewhere in the hundreds of sessions I started to wonder whether I'd gotten really good at saying the things without actually doing them. Whether I'd become the guy with the metaphor(I feel like I have plenty of proof but imposter syndrome is real y'all).
So this season I'm going to stop describing it and show it. Every episode, I sit down with the tool I actually use and treat it as the guest in audio and video. You'll hear where it helps and where it gets things wrong, and where it tells me something about my own work I'd rather not hear.
What's in this episode
The four quadrants. Before you can have a real conversation about AI, you need to be able to say which kind of AI you mean. I walk through the framework I've found most useful: two axes — how deeply the tool is integrated into where you already work, and how much it does without a human in each step. That gives you four types.
Assistant — "I need answers when I ask." You prompt, you decide, you own it. This is the chatting quadrant, and it's where this episode lives.
Copilot — "Help me in the tool I already use." Gemini in Docs, Copilot in Outlook. It comes to you.
Autopilot — "Do this automatically for me." One narrow job, no approval each time.
Agent — "Figure out how, and do it for me." Goals, tools, limits — it picks the steps. I have one that cleans and sorts my desktop at 5:00 every morning.
The left half is productivity AI: a human still produces the outcome. The right half is engineered AI: the system produces it, and somebody still has to own it, monitor it, and answer for it.
Four reasons for the season. The flattening of "AI" into one word that means everything. The gap between people nodding at metaphors and then using the tools at a surface level anyway. The distance between theory-land and the reality of jammed lockers and fire alarms and a kid having a rough day. And a commitment to real pushback and unedited disagreement including with the machine.
What this is not. Not an interview with a person. Not a demo reel as no vendor is paying for this and I'm leaving in the parts that don't work. Not a claim that Claude has earned its opinions. The distinction matters and I'm not blurring it for a better episode.
Five unrehearsed questions. Nothing was pre-tested. Claude confirmed on the record that it hadn't seen the questions and hadn't been coached on how to answer.
What are you, in your own words, and what do people get wrong about you?
Based on how I actually work with you, what's my pattern, where do I lean on you well, and where am I lazy about it?
What's a task educators bring you constantly that you're genuinely bad at, and they don't notice?
When I push back, do you actually disagree, or are you performing disagreement because I asked for it?
What should teachers be more worried about than they currently are?
Three moments worth the listen
"Partial evidence, not a verdict." After Claude named a pattern in how I work, it put a caveat on its own read: that's how I show up in these conversations, not a verdict on me as a person. Real evidence, but partial. Which is exactly what we're failing to do with students adn this is a detection flag that becomes the whole case, and nobody asks what the kid was stuck on.
The two tests for real disagreement. Ask what would have to be true for it to be wrong; if it can name a specific condition, there's something underneath the agreement. Then push back on something it got right. If it folds instantly and thanks you for the correction, you just watched it choose your approval over the truth. The tell in both cases is speed.
Year three. The worry isn't cheating or job loss. It's that the tasks that felt like busywork were where teacher judgment got built. Writing your own lesson plan is inefficient and the inefficiency is where you notice this won't work for third period. Grading the stack is slow, and somewhere in it you spot four kids sharing a misconception, and that becomes tomorrow. Automate the tedium and you don't just save time, you remove the practice reps. The veterans already have theirs. It's year three that's exposed.
