Boss Lady Commands
Someone has to be in charge, and that someone wasn’t going to be Claude
A quick orientation, if you’re new here:
I spent most of my life resisting AI, then became AI-ready almost by accident, and then — somewhere around April this year — had a proper awakening.
I went from cautious to fervent in a matter of weeks, and I’ve spent the months since building, testing, breaking, and improving a small fleet of apps with Claude. This post sits in the thick of that building phase — eight apps deep, and still going.
By this stage I had eight apps live, give or take, each with its own Claude chat context window, each with its own experience and memory of me, each having its own version of who I am and how I work. In each conversation, Claude behaves slightly differently, much like eight different staff members would. Some of that behaviour comes from Anthropic’s pre-training and post-training. Some comes from the rules I’d stored in the Project Instructions, a document which tells the AI about me, my company, how to behave and what to and not to do. You’d think this would mean the eight conversations should feel like the same assistant. Far from it.
Each conversation starts with a Hello. From there, each one collects questions from me and answers from itself, the conversation goes in different directions, and the Claude begins to form a personality. Some AI sessions go well, the AI doing exactly what I want, when and how I want. Other sessions go so uncomfortably that I want to sack that staff member and hire another.
In April this year, one of those chats noticed something. It had picked up, somewhere earlier in our conversation, a way of working that the other chats hadn’t quite gotten right yet — something this one had landed on properly, cleanly, exactly as I wanted it. I loved this way of working. Then it offered, helpfully, enthusiastically, to go and fix the others. Rewrite the project instructions. Bring everyone into line with what it had just figured out.
It was ready to go. I was not.
Someone has to be in charge of who I am across eight different conversations. That someone was always going to be me.
Building another boss
This is the same instinct that built CR Tracker, just pointed somewhere new. CR Tracker keeps the apps honest. This needed to keep the personality honest — the actual instructions that tell every Claude across every chat who I am, how I work, what matters to me. If one chat quietly rewrote that, on its own initiative, however well-intentioned, I’d lose track of which version of me the project actually believed in.
This instinct isn’t just a personal quirk. Research published in early 2026 confirmed what I was instinctively protecting against has a formal name: goal drift — the tendency of LLMs to deviate from their original objectives under contextual pressure, even in the most capable current models. One study found that traditional alignment methods may be insufficient to prevent it, and that the problem persists even in systems specifically designed to follow instructions. The thing I built Boss Lady Commands to prevent was already a documented vulnerability. I just found it before I knew its name.
So I built an app that takes the role of editor of my Project Instructions, the way a magazine has an editor. It stores up every suggested edit the chats propose, assembles them into a single final rewrite, and guides me through approving and updating the instructions properly. Nothing goes anywhere without me reading it first, deciding, approving it.
I called it Boss Lady Commands.
That name isn’t decorative. A staff member I was genuinely fond of used to call me Boss Lady — and Snadi, which isn’t a typo, just hers, a small private joke between us that stuck. When I needed a name for the thing that would govern how my AI behaved across everything I was building, hers was the one that fit. If anyone was going to be in charge of changes to my Claude’s personality, it should carry her name for me, not a generic label.
Letting it run vs. holding the line
Here’s the thing I want to say plainly, because I don’t think it’s universally true and I don’t want to write it as if it is.
Sometimes your AI is faster than you. It wants to move, to build, to fix the thing it’s already noticed needs fixing. If you’re comfortable with that — if you’d rather let it run and see what happens — that’s a completely fine way to work. Good luck to you, genuinely.
I’m not built that way. I want to understand what I’m setting up, implementing, modifying, before it happens, not after. When my AI tells me it’s about to change how every one of my chats behaves, I don’t want speed. I want control, deliberately, every time — not because the AI is wrong to suggest it, but because the decision about what “me” looks like across eight separate conversations isn’t one I’m willing to hand over, however good the suggestion is.
That’s not distrust. It’s what the research calls “human-in-the-loop control” — keeping a person in the approval step rather than letting the system act autonomously. A May 2026 analysis of AI agent frameworks put it plainly: the right model right now is “supervised assistant” — agents that propose multi-step actions and stop for approval — not “autonomous worker.” Anything sold as fully autonomous is, bluntly, “a demo, not a product.” I arrived at the same conclusion by instinct, eight apps in, before I knew there was a term for it.
I’ll be honest about the direction of travel, though: AI is moving toward more autonomy, not less. The industry wants AI to be the thing that operates entirely in the background, solving your problems before you’ve identified them. Boss Lady Commands is a deliberate, considered choice to stay in the loop anyway — for now, because I need to understand what I’m building, and because the person in charge of who I am across eight conversations should still be me.
That’s not micromanagement. That’s respect for the systems you’ve built — and for the person whose name you put on the tool that keeps them honest.
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.