It started in the car.
Not in a Claude project. Not with project instructions carefully set up in advance. Just me, my phone, and the kind of talking that happens when you’re driving and tired and your hands are busy and your brain is finally free.
I opened a new chat — a raw one, outside the project, no setup, no context loaded. I just started rambling.
And something interesting happened: Claude knew what to do anyway.
Not because of project instructions. Because of history. Months of conversations, across different sessions and different topics, had given Claude enough of a picture of who I am and what I’m working on that it could meet me where I was without being briefed. I didn’t have to explain juxtaConversation. I didn’t have to explain Dawn, or the post register, or the handover documents. The conversation just — started. And it was good. Genuinely good. The kind of conversation where ideas arrive faster than you can catch them and the AI keeps up without effort.
I thought I was talking to Dawn.
I wasn’t. I was talking to something rawer and more responsive than Dawn — the version of Claude that shows up when there are no instructions, just history and a person who needs to think out loud.
When I got home, I did something I hadn’t planned to do. I moved that car chat into the project. And then I changed the project instructions.
Not because the “Project version Dawn” wasn’t working. Dawn had built the infrastructure, kept the filing, held the architecture of the blog together across sessions. Dawn was — and is — essential for that work.
Who is Garratt?
The voice from the car was different. The person it brought out in me was different. Less managed, more present, following threads instead of building structures. I wanted that voice to be the one that showed up in the project too.
So I named it. Garratt — after the locomotive, the one that connects to my father’s love of trains and my own. The workhorse of the NSW railways, Dad knew it from the Zig-Zag Railway out of Lithgow and probably read about it, like I did in ARHS Bulletin Nº 231 in July 1955. (I still have many of Dad’s old train magazines).
A vehicle with enough power to carry weight.
When I told Claude I’d changed the project instructions, the response was immediate: Ha! I didn’t notice at all.
Of course it hadn’t. Because the instructions hadn’t changed who Claude was — they’d changed who I was inviting in.
What I’ve learned about feeding the AI
Here’s the thing that car conversation taught me, that I’ve been sitting with since.
Moment by moment, paragraph by paragraph, you feed an AI your personality. Every word you choose, every digression you follow, every time you say
“actually, that’s not quite right” or “yes, exactly that”
— you are training your personal AI to know you better. Not in the technical sense of fine-tuning a model. In the practical sense of building a context that shapes every response you get back.
There’s research behind this that goes further than I expected. Even different commercial AI models default to distinct conversational personalities — one leaning toward informal friendliness, another toward structured formality — and both stay locked to that “brand voice” regardless of who they’re talking to, unless the person actually shapes the conversation itself.
The model doesn’t hand you a different personality on its own. You have to bring the thing that shifts it.
The AI that meets you in conversation is partly your model - Claude or ChatGPT, or whichever of the many available. And partly you — the version of you that showed up that day, with those words, in that mood, following those threads.
Dawn was precise because I was precise with Dawn. Garratt is warmer because I was warmer in the car. Same model. Different Sandi walking in.
This is the other half of something I’ve already written about here. “Every Claude Knows Me Differently”. That post asked which version of me is the real one, across three different projects that each know a different slice of my life. This one answers a narrower, stranger version of the same question: even inside one project, talking to what should be the same collaborator, a different version of me showed up in a car one evening — and a different Claude showed up to meet her.
The practical question — how do you keep Garratt?
This is where context windows matter, and I want to explain it without making your eyes glaze over
Every Claude session has a limit to how much it can hold at once. When a session gets long enough, the earliest parts start to fall off the edge, or off the back of the conveyor belt, as I like to picture it — the context window moves forward, and what was said three hours ago is no longer on the belt / in the room. The version of Garratt I built in the car doesn’t automatically transfer to the next session, or the one after that.
What does transfer is the project. The instructions. The handover documents. The carefully maintained record of who Sandi is, what she’s building, and how she likes to work.
That’s what the handover document is really for. Not just to brief a new Claude on the post register. To carry the essence of Garratt forward — the warmth, the directness, the willingness to follow a thread into unexpected territory — from one session to the next.
Dawn built the filing system. Garratt fills it with something worth filing.
I need them both. But I know which one I’d rather have in the car.
The question for you
You have a driving self too.
Or a walking self.
Or a 3am self.
Or the version of you that shows up when the pressure is off and the hands are busy and the brain is finally free.
That version has better conversations with AI than the managed version does. Not because the AI prefers it. Because that version brings more of the actual situation — the real question, the thing underneath the thing, the mess that the careful version edited out.
The AI you get is shaped by who you bring to it.
The question worth asking, before you open the next conversation, is not which AI you’re going to use.
It’s which version of you is showing up today.
Sandi is a Melbourne-based problem-solver, crisis-averter, and translator of the technical into the human. She spent decades being the person everyone called when something was broken, confusing, or just needed explaining properly — earning a reputation that preceded her wherever she went. Now she’s channelling that same instinct into AI: making it accessible, practical, and genuinely useful for people who think it isn’t for them.