When o3 Plans Your Career Better Than You Do

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I’ve always hated the question, “Where do you see yourself in five years?” Answering it feels like an exercise in forced self-aggrandizement—vaulting myself to the top of the org chart just to prove I have the right measure of ambition and am not afraid to "think big." If someone could supply an answer that felt authentic rather than pandering to whatever hiring manager asked the question, I’d Venmo them a finder’s fee.

So the Friday after o3 dropped, filled with equal measures of curiosity and dread, I let OpenAI’s newest model take a crack at earning a co-writing credit.

Six seconds later, I was staring at a scrollable epic, complete with revenue mix, milestones mapped to the quarter, and a five‑bullet case for why this future is “plausible.” In o3’s 2030, I’m editor in chief of Every, running a product studio, and on sabbatical writing a romantasy novel.

This model dreams bigger for me than I do.

Six months ago, GPT‑4 helped me reorient after a layoff. Since then, my career has evolved—and ChatGPT has leveled up from reactive analyst to agenda‑setting aide‑de‑camp.

Most stories about AI’s rapidly progressing capabilities hinge on fear: Automation eats jobs, algorithms erode agency, everything human gets flattened into paste. o3 presents a subtler puzzle: instead of waiting for prompts, it drafts possibilities. It proposes versions of you that you might actually want to become, and charts a path to get you there.

This essay is my field report on co-authoring a future with a machine unburdened by human baggage around ambition. Come to watch AI turn an argument into an action plan; stay for instructions on how to build an o3 career coach of your own.

Identity, cached: I rewrote AI’s idea of my self-concept

The second “editor in chief” flashed on‑screen, my stomach did the freight‑elevator drop it saves for roller coasters and performance reviews. Back‑to‑back 1‑on‑1s, traffic dashboards, and invoice-wrangling? No thank you.

But o3 doesn’t know that shepherding a team fills my heart with icy dread. All it has to go off of is the gigabyte of data I’ve parked in its cloud.

For months, I’ve fed ChatGPT the raw footage of my working life: half‑finished essays, dozens of style guide iterations, mini AI avatars that I’m building of my co-workers. Each upload teaches the model a little more about who “Katie the content strategist” supposedly is—and that version of “Katie” is apparently way bolder than the carbon‑based original.

“What about editor at large instead?” I prompted. Seven seconds later the blueprint recompiled to show my editor‑at‑large era: a job description I could actually see myself in. I was negotiating a job title for 2030 with a chatbot.

What struck me about this, compared with past chats, was o3’s habit of preemptively offering a plan instead of waiting for prompts. GPT-4 answered questions; o3 l drafts a future, then waits for your redlines. Prompting is secondary; the real skill is slashing, annotating, and rewriting the version of you the AI proposes until the roadmap sounds like a life you’d want to live.

The system prompts back: o3 turns doubt into to‑dos

GPT‑4 handled doubt like a yoga instructor: long breath in, reassuring mantra out “(Growth is non-linear”; “Careers unfold in seasons”). o3 treats it like a bug report: Log it, triage it, ship a fix before you refresh the tab.

When I told it I wasn’t sure I had the chops (or desire) to run a product studio, it didn’t drop the goal; it said “let’s unpack that.” Then it laid out a four-step process for digging into the source of the self-doubt: Extract what it was about vibe coding that appealed to me; shape that energy into a role that could outlive the hype cycle; test before making career-level commitments; and run every new obsession through a “sustainability scan”—a quick gut‑check for how well each interest aligns with my energy and sustains my interest.