Thank you to everyone who tuned into my live video! Join me for my next live video in the app. Prompt With CARE What watching someone else prompt taught me about the skill we all think is basic—plus two prompt packs that set up your Claude Cowork in one afternoon Yesterday I asked a student to sit at my computer and prompt Claude Cowork to build a presentation. He typed a single sentence, hit enter, and waited. Watching him, I realized two things: the conversational interface with these tools is a genuine skill, and I’d been doing it so long I’d forgotten it had to be learned. I teach people AI tools constantly—I had never once sat down and watched someone else prompt. It was the most instructional thing I’ve done in months. So this piece is the session I ran afterward, in writing. One framework, one habit loop, and—because readers keep telling me prompt packs are the most useful thing I publish—two packs you can paste into Claude Cowork today: a Cold Start Interview that sets up your workspace from scratch, and five Workflow Interviews that teach it your voice, your week, and your standards. Nothing here is specific to medicine. If you have a job and a desk, this applies. Housekeeping: I don’t type my prompts—I speak them. You will never type as fast as you talk, and the more descriptive your language, the better your output. I use Wispr Flow (function + spacebar, then just talk—you can literally whisper). If you want to try it, downloading through my affiliate link supports this newsletter. The Frappuccino Problem A close friend of mine has a habit that drives me a little crazy. He’ll say, “I don’t like the way AI writes X.” or he’ll say “AI never makes my images or powerpoints right”. And every time, I think: it’s not that you don’t like what AI makes. It’s that you don’t like what AI makes for you…because you’re giving it poor instructions. Think of these tools as a very smart intern. Maybe a PhD-level Harvard graduate of an intern. If I tell that intern “go get me coffee,” and they come back with a Frappuccino when I wanted an Americano with oat milk, that’s on me. The intern did their best with what I gave them. A language model is the same: every detail you leave out, it fills in with the most average assumption available. Vague prompts don’t produce bad output. They produce median output, which for any real professional task is the same thing. The fix is a framework I call prompting with CARE: C — Context. Who you are and what situation this output lives in. A — Audience. Who actually reads, sees, or uses this. R — Role. Who the AI should be—”you are a patient educator,” “you are a skeptical CFO”—so it pulls the right body of knowledge into the task. E — End product. The exact artifact you want: format, length, tone, what it should be usable for the moment it’s done. In my live session I demonstrated this with two prompts about the same topic. “Tell me about hip fractures” got me a long, jargon-heavy wall of text. The CARE version: “I’m a trauma surgeon, fewer than a third of my patients ever start bone-protecting treatment after a fracture, you’re a patient educator, write for families at a sixth-grade reading level, one-page handout, warm and non-alarmist, end with three questions to ask your doctor” This prompt instead produced something I could physically hand to a patient that afternoon. Same model. Same topic. The difference was entirely in the briefing. Your First Output Is the Input The second principle, and the one that separates people who get compounding value from people who quit: the first output is not the final output. It’s the input for the next cycle. You will be very frustrated if you try to one-shot these tools. The entire power of a large language model is the compression of iteration cycles: you get unlimited at-bats, and each swing takes seconds. When my bone-health handout came back and I didn’t love it, I didn’t start over. I said what needed to change. Make it Duke-branded, add interactive components, also give me a PowerPoint I can click through. And the output became the raw material for something better. Later I dragged that same HTML into a fresh Cowork task and rebranded it for RevelAi in one prompt. Output becomes input. That’s the loop. Two force multipliers on that loop. First, speak instead of typing. Being verbose is usually a weakness of mine; it turns out it’s a superpower with these models, because descriptive, rambling, context-rich instruction is exactly what they reward. You’re not on a timer, and nobody’s grading your dictation. Second, meta-prompting: when the end product demands a better description than you can produce—a detailed image prompt, say—don’t write the prompt yourself. Ask the tool to write the best-practice prompt for you, then carry it wherever you need it. The model is better at describing what the model needs than you are. The Step Most People Never Take Everything above makes a single task go well. The better approach is making sure you never start from zero again. This is what I think of as building sustainable context systems. The low-hanging fruit is Projects: a folder where your chats, files, and outputs accumulate so the tool carries the thread across sessions. I run my academic promotion tracker, cap table, and investor touchpoints this way connected with Live Artifacts. Learn more about Scheduled Tasks and Live Artifacts Below: But the foundation underneath all of it—the thing I do with every person I onboard one-on-one—is to have Claude interview you. Instead of laboring to write the perfect context document about yourself, you flip it: make the model ask you questions, one at a time, until it understands your role, your projects, your people, and your standards. Answering questions is cognitively cheap. Composing instructions is expensive. And in Cowork, the answers don’t evaporate when the chat ends—they become standing infrastructure, so every future task starts with the CARE already half-written. The question is what the interview should cover. That’s the part most people improvise badly. Below the line are the exact packs I give people in one-on-ones—six prompts that stand up your workspace from nothing, and five that teach it your recurring workflows. The two prompt packs below are for paid subscribers. Pack One stands up a Claude Cowork workspace from scratch in about thirty minutes—it’s the same starter kit I use when I onboard people one-on-one. Pack Two teaches your Cowork your writing voice, your calendar, and your definition of done. Copy, paste, answer the questions out loud and you’re all set. As a bonus, in the paid section… It seems like many people are a fan of the one-shot video note that I wrote recently. I also included a video of me installing the Higgsfield MCP. Techy Surgeon is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Prompt Pack One: The Cold Start Interview Run these in order, in Claude Cowork, ideally in one sitting. Each prompt instructs Claude to interview you and then write what it learns to memory—so say “save this” when the summary looks right. Total time: about thirty minutes. Less if you dictate. 1 — The Role Brief You’re setting up as my long-term work assistant, and right now you know nothing about me. Interview me, one question at a time, until you understand: what my job actually is day to day (not the title—the verbs), who I’m accountable to, what I produce, and what a great week versus a bad week looks like. Don’t accept vague answers—push for specifics. When you’re confident, write a one-page working profile of me, show it to me for corrections, and save it to memory. 2 — The Project Map Interview me about everything I’m currently working on—projects, initiatives, recurring responsibilities, and the things that are stalled but still mine. One question at a time. For each, capture: what it is, current status, who else is involved, the next milestone, and what I’m most worried about. Then organize it into a project map ordered by what deserves my attention, show me, and save it to memory. 3 — The People Directory I’m going to mention names, nicknames, and abbreviations constantly, and I never want to explain them twice. Interview me about the people and organizations in my work orbit: who they are, their role relative to me, how I refer to them in shorthand, and anything you should know before drafting something they’ll read. One question at a time, and prompt me with categories I might forget—boss, reports, clients, vendors, collaborators, the person I always forward things to. Save the directory to memory. 4 — The Preference Card Interview me about my output preferences so you stop guessing. Cover: how long answers should be by default, bullet points versus prose, how formal my drafts should run, formatting pet peeves, words and phrases I’d never use, and how I want you to behave when you’re uncertain—guess, ask, or give options. Get concrete by showing me two short sample paragraphs in different styles and asking which is closer. Save the result as my standing preference card. 5 — The Definition of Done For each type of deliverable I produce regularly—you have the list from my project map—interview me about what “finished” means. What does a ready-to-send email have that a draft doesn’t? What makes a document ready for my boss versus ready for a client? Build me a short rubric per deliverable type, confirm it with me, and save it. From now on, check your own work against these rubrics before showing me anything. 6 — The Standing Orders Last one. Interview me about the rules of engagement: things you should always do without asking, things you should never do without asking, topics where I want pushback versus execution, an
