The conversation around AI and jobs tends to get stuck on one question: will AI take my job? It's a fair question, but it's the wrong one for most professionals to spend their energy on. The more useful question is quieter, and it's already playing out inside performance reviews and hiring decisions right now: what does "competent" mean anymore?
Across the professionals Joshua Terrell has trained — engineers, product managers, analysts, and team leads — the same pattern keeps showing up. The bar for baseline competence is moving, and it's moving faster than most job descriptions have caught up to.
The shift from "can you do it" to "can you do it with AI"
A few years ago, being a strong software engineer meant writing clean, working code efficiently. That's still true, but it's no longer sufficient on its own. Increasingly, being strong at the job means knowing how to use AI coding tools to move faster without introducing bugs, security issues, or unmaintainable code — a genuinely different skill from writing code unassisted.
The same pattern shows up outside engineering. A marketer who can direct AI tools to produce ten strong campaign concepts an hour is operating at a different level than one who can't, even if both understand marketing equally well. The underlying expertise hasn't changed — the expected output has.
Why this catches experienced professionals off guard
Ironically, it's often the most experienced professionals who feel this shift most acutely. They built deep expertise the traditional way, over years, and that expertise is still genuinely valuable — but it's being evaluated against a new, faster baseline that didn't exist when they built their reputation.
This creates a strange dynamic: someone can be excellent at their job by every previous standard and still feel like they're falling behind, simply because the standard itself moved. Recognizing that this is a systemic shift — not a personal failing — is the first step to responding to it productively instead of anxiously.
What actually helps
- Treat AI fluency as a core professional skill, not an optional add-on — the same way spreadsheet literacy became non-negotiable a generation ago.
- Focus on judgment over tool-specific tricks. Tools will keep changing; the ability to evaluate AI output critically will not go out of date.
- Look for small, low-stakes ways to practice using AI in your actual work this week, rather than waiting for a formal training opportunity.
- Talk openly with your team about how expectations are shifting, rather than assuming everyone else already has it figured out. Most people don't.
The upside nobody talks about enough
This shift is disruptive, but it's not purely a threat. Professionals who adapt early gain outsized leverage — the same amount of effort now produces meaningfully more output, which historically translates into more opportunity, not less. The goal isn't to fear the new baseline. It's to get comfortable operating above it.
AI expert with a software engineering background, based in Dublin, Ohio. Joshua teaches practical AI courses and mentors professionals through Joshua Terrell AI Courses.