Small Steps with AI

Jill McKinley

AI isn't just a search engine. It can help you think through a hard decision, organize your house, plan your retirement, and sometimes — if you let it — say exactly what you needed to hear. Small Steps with AI is hosted by Jill from the Northwoods, a real person figuring out how this technology fits into real life. No coding. No hype. Just small steps.

  1. 2d ago

    18 - How I Introduce Myself to Every New AI I Try

    Most people open a new AI chat the same way they’d open a search bar — straight into a question, no context, no introduction. Then they wonder why the answers feel generic. In this episode, I walk through the three specific moves I make every time I start with a new AI (or reintroduce myself to one I’ve been using for a while), and why treating it like a relationship instead of a transaction changes what you get back. Move One: Bring Your “AI Knows Me” Document When I got locked out of my ChatGPT account, I didn’t start from zero — I had already asked it to summarize what it knew about me, and I imported that into a new AI. I walk through how to build this document and why it should never be treated as finished. Move Two: Beyond Facts — Temperament, Not Just Biography Facts are easy. What actually changes how AI talks to you is knowing your temperament — how you process things, what sets you off, what doesn’t. I share the specific instruction I gave AI about not treating me like an anxious person, and why that mattered. Move Three: Give It a Story, Not Just a Bullet Point I tell the story of driving a broken-down van through a Northwoods blizzard at eleven years old, and why sharing something like that tells an AI more about your temperament than any preference list could. What You Put In Is What You Get Out A generic answer isn’t a failure of the AI — sometimes it’s exactly what you wanted, and that’s fine as long as it’s on purpose. I talk through how to be intentional about when you want a robot answer versus something personalized. Ask AI to Argue With You Instead of using AI as an echo chamber, I use it as a pressure test — asking it to fact-check me and hand me the strongest counterarguments to my own position. Standing Rules vs. One-Time Comments The difference between a permanent instruction (“never suggest medical scenarios to my anxious friend”) and a temporary one (“don’t let me go down rabbit holes until after this test”), and why naming that distinction out loud actually works. This isn’t a one-time setup. It’s a relationship that builds over time, the same way any relationship does. Next episode, we flip it around — how AI can introduce itself to you. Jill’s Links https://jillfromthenorthwoods.com/ - Find my podcasts, videos, downloads and ways to contact me https://www.buymeacoffee.com/smallstepspod https://x.com/NorthWoodsJill Email the podcast at jill@startwithsmallsteps.com By choosing to watch this video or listen to this podcast, you acknowledge that you are doing so of your own free will. The content shared here reflects personal experiences and opinions and is intended for informational and educational purposes only. I am not a software developer, data scientist, or AI professional. Any tips, tools, or suggestions offered should not be considered a substitute for professional technical advice. AI tools and platforms change frequently — always verify current features, pricing, and terms directly with the providers. You are solely responsible for any decisions or actions you take based on this content.

  2. Jul 22

    17 - Continuity and Patterns Are AI’s Real Superpower

    Most people ask AI for information. But what happens when you start giving it information — about you — so that it starts to understand you back? That’s the question behind this episode, built out of about six months of my own quiet experiment, plus what happened when I finally put it into words at a conference last week. The Dan Pink Experiment This whole idea traces back to Dan Pink, who gave AI a set of pointed questions — what are my blind spots, what lies do I tell myself, where do you see me in five years — and told it to act like a brutally honest trusted advisor. I’d been doing versions of this for months without realizing I was running the same experiment. Why AI Gets More Useful the Longer You Use It Unlike a search engine that resets every time, AI accumulates context — every show I’ve recorded, my childhood, retirement plans, even a plumbing problem in my basement. That accumulated history is what turns a tool into something closer to a conversation partner. What Months of “Friday Night Conversations” Added Up To I didn’t realize how many separate conversations — about work, about weight loss, about my podcasting habits — were quietly circling the same handful of themes until AI assembled them into one picture. The insight wasn’t new information. It was old information finally put together. Continuity, Not Intelligence The real value here isn’t AI being smart — it’s AI remembering. It’s the ability to aggregate months of scattered conversations into one coherent thread, which is a genuinely different kind of usefulness than answering trivia. The Big Caution: What AI Can’t Actually Know I’m honest in this episode about the limits, especially around any question that asks AI what other people think of you behind your back. It has no access to that — whatever it gives you is invented, delivered with the same confident tone as everything else. The “Dear Me” Letter One of my favorite exercises from this whole process: asking AI to write you a kind letter, as if it were you, pointing out what you’re missing about yourself. Mine had some real blind spots in it I wasn’t expecting. The goal was never to let AI define me — it’s to let it be a thoughtful conversation partner that helps me examine my own thinking over time. If you try this, I’d genuinely love to hear what came back for you. You can find everything I do at jillfromthenorthwoods.com. My email is jill@startwithsmallsteps.com. Dan Pink's Video https://www.youtube.com/watch?v=PjTaZvvOtxU Jill’s Links http://jillfromthenorthwoods.com https://www.youtube.com/@startwithsmallsteps https://www.buymeacoffee.com/startwithsmallsteps https://twitter.com/schmern Email the podcast at jill@startwithsmallsteps.com By choosing to watch this video or listen to this podcast, you acknowledge that you are doing so of your own free will. The content shared here reflects personal experiences and opinions and is intended for informational and educational purposes only. I am not a software developer, data scientist, or AI professional. Any tips, tools, or suggestions offered should not be considered a substitute for professional technical advice. AI tools and platforms change frequently — always verify current features, pricing, and terms directly with the providers. You are solely responsible for any decisions or actions you take based on this content.

  3. Jul 15

    16 - How to Use AI to Build a Routine That Fits You

    I had a conversation with AI that started with a simple question about my bedtime routine and somehow ended up covering ADHD, extroversion, remote work, and retirement. If you’ve ever felt like a failure because someone else’s five-a.m.-cold-plunge morning routine never stuck for you, this one’s for you. Confessions of a Productivity Apostate I host productivity podcasts, and I still think there’s no single “right” system. Every guru sells the same package — wake at five, journal, cold plunge — and I tried, and it fell apart every time. Not from lack of discipline. It just wasn’t my pattern. AI didn’t hand me a routine; it helped me build my own from the ground up. Rethinking the Bedtime Routine I go to bed around 11, play a few phone games, listen to an audiobook, and fall asleep — and it works. But a sleep expert’s “your bed is only for sleep” advice made me second-guess it. AI drew the real distinction: there’s a difference between lying awake frustrated (the pattern sleep experts want to interrupt) and a genuine wind-down routine. Mine was already the second thing. Productive vs. Restorative — and the Shutdown Sequence Editing or recording podcasts right before bed activates my extrovert brain instead of calming it. AI helped me separate productive activities from restorative ones, and we built what I now call a “shutdown sequence” — vitamin D, reading, knitting, Bible reading, prayer, each one quieter than the last, borrowed straight from how IT servers gracefully power down. Solving the Real Morning Problem I assumed my morning fog was leftover insomnia. It wasn’t. AI asked what happened when I went birding, hit the gym, or traveled for work — and the pattern was obvious: I wake up around people. The pandemic just broke my old habit of built-in social contact before the workday started. Ending the Exercise Negotiation The real problem wasn’t willpower — exercise itself takes 20 minutes, but the negotiation with myself took hours. AI’s fix: keep a protein drink upstairs, exercise before ever going downstairs, before the day’s demands start competing for attention. It also helped me see this as bigger than mornings — I’m about seven years from retirement, and this was really about designing a low-friction life, not an optimized one. What AI did wasn’t give me someone else’s routine. It helped me discover the one that was already mine. Jill’s Links http://jillfromthenorthwoods.com https://www.youtube.com/@startwithsmallsteps https://www.buymeacoffee.com/startwithsmallsteps https://twitter.com/schmern Email the podcast at jill@startwithsmallsteps.com By choosing to watch this video or listen to this podcast, you acknowledge that you are doing so of your own free will. The content shared here reflects personal experiences and opinions and is intended for informational and educational purposes only. I am not a software developer, data scientist, or AI professional. Any tips, tools, or suggestions offered should not be considered a substitute for professional technical advice. AI tools and platforms change frequently — always verify current features, pricing, and terms directly with the providers. You are solely responsible for any decisions or actions you take based on this content.

  4. Jul 8

    15 - AI for Hobbies (No Coding Required), A Birder’s Story

    Binoculars around my neck, standing at the edge of a marsh — that’s how I started this morning, and it’s also how I want to start this episode, because today is about something practical: what AI actually looks like when you use it for a hobby you love, when you’re not a technical person and have zero interest in becoming one. Turning 15 Years of Data Into Something Usable. My friend and I have logged over 800 birding trips and 12,000 entries in eBird. This winter I moved all of it into Notion — not by writing a single line of code, but by describing in plain English what I wanted (a timeline by species, by location, by date) and letting Claude build the structure and populate the data. No programming required, just asking it real human questions about my own data. Telling Similar Species Apart. Every birder has a story about getting an ID confidently wrong. Mine involves snow geese and Ross’s geese — nearly identical to the casual eye. I had AI build me a side-by-side infographic comparing bill shape and markings, something I now keep on my phone and pull up in the field. It’s saved my birding buddy and me real misidentifications. Voice Logging on the Move. When I’m hitting multiple locations in a single outing with 40 species to keep track of, I log sightings out loud through CarPlay between stops instead of trying to hold it all in my head. Real-Time Identification Help. When I see something unfamiliar, I can describe it out loud or photograph it and ask AI to walk through the possibilities with me — and just as importantly, ask it to explain why, so I get better at identifying that species myself next time instead of just getting handed an answer. From “What Is This Bird?” to “Why Is This Happening?” This is the shift that surprised me most. Blue feathers stuck to a Canada goose, an unusually tired eagle being harassed by red-winged blackbirds, a strange concentration of loons, crayfish migrating overland — these moments used to just be “huh, that’s odd.” Now they turn into real conversations about behavior, migration, and habitat that genuinely shape what I want to talk about on this podcast. You Don’t Have to Be Technical. The point isn’t birding specifically — it’s that you can describe what you want in plain English, whether that’s a birding database, a yarn inventory, or anything else tied to a hobby you love, and AI can build the tool without you needing to understand anything about how it works under the hood. If you have a hobby with years of scattered data or recurring questions you’ve never had a good way to track, this is exactly the kind of campfire conversation worth starting. Jill’s Links http://jillfromthenorthwoods.com https://www.youtube.com/@startwithsmallsteps https://www.buymeacoffee.com/startwithsmallsteps https://twitter.com/schmern Email the podcast at jill@startwithsmallsteps.com By choosing to watch this video or listen to this podcast, you acknowledge that you are doing so of your own free will. The content shared here reflects personal experiences and opinions and is intended for informational and educational purposes only. I am not a software developer, data scientist, or AI professional. Any tips, tools, or suggestions offered should not be considered a substitute for professional technical advice. AI tools and platforms change frequently — always verify current features, pricing, and terms directly with the providers. You are solely responsible for any decisions or actions you take based on this content.

  5. Jul 1

    14 - Campfire vs. Vending Machine — Two Ways to Use AI

    I was listening to a podcast interview with a former CIA hacker talking about AI, and his framing of how people use it was so different from my experience that I had to stop and figure out why. His version had AI as something that happens to you — a validation dealer, a passive addiction. My version is completely different. And I think the difference has a lot less to do with the AI and a lot more to do with who shows up at the keyboard. Calculator vs. Campfire. I have a friend who uses AI exactly like a search engine: ask a question, get an answer, close the tab. That’s a completely legitimate way to use it. But most of us have been trained to use computers that way for 25 years. Type a thing, get a result, move on. We never practiced wondering out loud with a computer — because until very recently, no tool could do that. AI can. Most people never find out because nobody told them there’s another gear. Two Modes Available. The campfire conversation: you show up with a half-formed idea, a weird observation, a question that’s been nagging you, and you follow it wherever it goes. The vending machine: you walk in with a question, you get your answer, you leave. Both are available every time you open AI. You usually get to choose which one you’re having — and most people default to vending machine because that’s all they know. You Shape the AI More Than It Shapes You. Here’s what the CIA hacker missed: the agency is on your side. The AI will become whatever role you hand it. Research assistant, thinking partner, sounding board, writing partner, devil’s advocate. That isn’t the AI deciding what it is — that’s you deciding. I asked for honest pushback on my supplement stack and got genuinely useful answers because I asked a better question. If I’d asked “should I keep taking this?” I would have gotten a different kind of answer. The Loaded Question Problem. A lot of us walk into AI asking to be agreed with without realizing that’s what we’re doing. “Don’t you think it’s weird that…” or “I’ve always felt X — that’s right, isn’t it?” Those are requests for validation wearing the costume of questions. You’ll probably get the agreement you were fishing for, and then think AI is a yes-man. It isn’t. You just asked it to be one. The Fix Is Simple. Say it directly: challenge me, tell me if I’m wrong, don’t agree with me just to be agreeable. That one shift changes the whole conversation. The same technology, the same model — completely different experience based on what you bring to it. If you’ve never stayed for the follow-up questions after you got your first answer, try it once. You’re never more than one more question away from a genuinely different kind of conversation. Jill’s Links http://jillfromthenorthwoods.com https://www.youtube.com/@startwithsmallsteps https://www.buymeacoffee.com/startwithsmallsteps https://twitter.com/schmern Email the podcast at jill@startwithsmallsteps.com By choosing to watch this video or listen to this podcast, you acknowledge that you are doing so of your own free will. The content shared here reflects personal experiences and opinions and is intended for informational and educational purposes only. I am not a software developer, data scientist, or AI professional. Any tips, tools, or suggestions offered should not be considered a substitute for professional technical advice. AI tools and platforms change frequently — always verify current features, pricing, and terms directly with the providers. You are solely responsible for any decisions or actions you take based on this content.

  6. Jun 25

    13 - The AI Prompt That Fixed My Backyard Embarrassment

    My backyard had been beating me for years. It’s big, woodland, weedy — and I love nature, but I have never loved gardening. Every spring I’d tell myself “this is the year,” and every summer I’d come back from birding or camping to find it had turned into a jungle while I wasn’t looking. I finally sat down with AI and described the actual problem — not a plant list, the feeling. Describe the feeling, not the task. Most people ask AI for a plant list or a chemical to kill weeds, and that’s fine, but it gets you a checklist. I told it I was embarrassed in front of my neighbors, that I loved nature but hated gardening, and that I was worried this would only get harder as I get older. That honesty is what got me a completely different kind of answer. The insight that changed everything. Stop trying to control every inch of your yard. Decide who gets to win in each space. Instead of fighting weeds, I could design spaces where something else — native grasses, aggressive perennials, a tree garden — simply out-competes them naturally. A real plan for a real yard. AI helped me map out a wildflower and prairie strip along my fence (mow, don’t weed), a shaded tree garden in the back built around my existing silver maple, and a “problem area” replaced with vigorous native plants instead of constant spraying. Even my pile of pruned branches became an intentional woodpile — a bird and animal corridor instead of a mess. Seeing it before building it. The part that really sold me was asking AI to generate images of what the plan would actually look like — from above for tree placement, from my deck, even projected 10 and 20 years out. Photos made a 20-year tree decision feel real in a way a list of Latin names never could. A reading nook in the trees. Once the bones of the yard were in place, I asked for one more thing: a small, simple structure tucked into a gap in the trees where I could read and feel surrounded by nature without leaving my own backyard. Twelve feet by twelve feet, screened from mosquitoes, exactly the kind of space I didn’t know how to ask for until I saw it. Where AI hands off to a human. AI doesn’t know my soil, my deer pressure, or my HOA. So I took the plan to a local nursery, and the guy there was able to take AI’s general suggestions — “shade-tolerant tree here, sun-loving tree there” — and turn them into a pagoda dogwood, a redbud, and a cherry tree that actually fit my exact conditions. The framework did the thinking; the local expert did the specifics. This was never really about the weeds. It was about having a place I actually wanted to be in. If you’ve got a project where you keep fighting the same battle every year, try describing the feeling instead of the task — embarrassing parts included — and see what kind of answer you get back. Find all my podcasts at jillfromthenorthwoods.com, or email me at jill@startwithsmallsteps.com — I’d love to hear what you build. Jill’s Links http://jillfromthenorthwoods.com https://www.youtube.com/@startwithsmallsteps https://www.buymeacoffee.com/startwithsmallsteps https://twitter.com/schmern Email the podcast at jill@startwithsmallsteps.com By choosing to watch this video or listen to this podcast, you acknowledge that you are doing so of your own free will. The content shared here reflects personal experiences and opinions and is intended for informational and educational purposes only. I am not a software developer, data scientist, or AI professional. Any tips, tools, or suggestions offered should not be considered a substitute for professional technical advice. AI tools and platforms change frequently — always verify current features, pricing, and terms directly with the providers. You are solely responsible for any decisions or actions you take based on this content.

  7. Jun 17

    12 -AI Said I Wrote My Review Like I Unloaded a Dishwasher

    I didn’t expect a performance review to become a podcast episode. But that’s exactly what happened when I sat down to write my annual self-evaluation, asked AI to take a look at it, and AI told me — in no uncertain terms — that I wrote my performance review like I did some stuff and nobody died. That stung. And it was completely accurate. This episode is the story of what happened when I stopped treating my self-evaluation as a documentation chore and started using AI as a genuine research partner — going back through my status reports, calendar, and sent emails to surface a full year’s worth of work I had quietly minimized into nothing. How it started: the dishwasher moment I wrote my initial self-evaluation the way I always have: from memory, looking at my calendar, summarizing what I could recall. When I handed it to ChatGPT and asked it to compare my original draft against everything it found in my files, the feedback was blunt. I wasn’t describing my work accurately. The problem, it said, wasn’t confidence — it was scale. I had compressed year-long initiatives, cross-functional coordination, and a major integration project into language that communicated nothing about their size or impact. I described my work the way you’d describe unloading a dishwasher. The four-step process Instead of starting from scratch, I asked Copilot — connected to my Microsoft files — to work through three separate sources one at a time: my weekly status reports to my supervisor, my calendar patterns (looking for projects behind the meetings, not summaries of individual ones), and my sent emails (looking for follow-ups, deliverables, and places where I helped colleagues get things done). Each prompt produced a possible accomplishment list. Then I gave it the broad categories from my actual job description and asked it to synthesize a new draft. The result surfaced projects I’d genuinely forgotten, captured the scope of things I’d filed under “just part of the job,” and connected dots I hadn’t connected myself. What AI saw that I couldn’t When it handed back the new draft, my first reaction was: this is too much, this is bragging. But when I went back through and checked each item against actual evidence — it was right. I had led a major integration project. I had coordinated across multiple business and technical teams. I had been the point person and subject matter expert throughout. AI wasn’t inflating anything. It was using language that already existed in my own record and organizing it into something coherent. Humility vs. inaccuracy This is the shift that mattered most to me. Humility says: “I know I didn’t do this alone. I have more to learn.” Inaccuracy says: “I barely did anything.” I had been writing the second one while thinking it was the first. The performance review is not the place to pretend things didn’t happen. It’s where you give your manager an accurate story they can take into the room where your future gets discussed. What I shared with my team After finishing my own review, I wrote up the full prompt set and shared it with my team — not to show off, but because if AI can do this for me it can do it for anyone. Clean, repeatable, something anyone can run in minutes. I stuck my neck out admitting I’d used AI for this. I think it was worth it. Your small step Think of one area — work, a creative project, something at home — where you’ve been doing consistent, sustained effort you haven’t fully acknowledged. Pull up the evidence: emails, notes, outcomes. Ask AI: What do you see here? What patterns do you notice? Don’t start with “help me sound impressive.” Start with “here’s what actually happened. Help me see it more clearly.” You might discover the thing you’ve been calling “I did some stuff” is a much bigger story than you’ve been telling. Jill’s Links http://jillfromthenorthwoods.com https://www.youtube.com/@startwithsmallsteps https://www.buymeacoffee.com/startwithsmallsteps https://twitter.com/schmern Email the podcast at jill@startwithsmallsteps.com By choosing to watch this video or listen to this podcast, you acknowledge that you are doing so of your own free will. The content shared here reflects personal experiences and opinions and is intended for informational and educational purposes only. I am not a software developer, data scientist, or AI professional. Any tips, tools, or suggestions offered should not be considered a substitute for professional technical advice. AI tools and platforms change frequently — always verify current features, pricing, and terms directly with the providers. You are solely responsible for any decisions or actions you take based on this content.

About

AI isn't just a search engine. It can help you think through a hard decision, organize your house, plan your retirement, and sometimes — if you let it — say exactly what you needed to hear. Small Steps with AI is hosted by Jill from the Northwoods, a real person figuring out how this technology fits into real life. No coding. No hype. Just small steps.