Over the last few weeks, a few parents and even my Tíos and Tías (uncles and aunts) with children or grandchildren in college have asked me the same question: should their students drop out and "just learn AI instead?"
I get it. The headlines are relentless. Entry-level jobs are vanishing. Majors are becoming obsolete. And if you're a parent watching your student invest time and tuition into a degree, the anxiety is real.
But here's what those headlines miss.
Entry-level work is being transformed, not eliminated. The World Economic Forum's 2025 Future of Jobs Report confirms that while routine tasks are being automated, many leaders anticipate higher entry-level headcounts in the coming years, provided those roles incorporate AI-related skills. The real issue isn't the degree. It's the gap between what students are learning and how they can apply it with AI.
I think about my own story. Growing up in West Texas, the only version of success I saw was doctor, lawyer, or oil field engineer. So, I majored in biology and organic chemistry, convinced that medical school was my path. It took a mentor asking me one question in my senior year to crack everything open: "Why do you want to be a doctor?"
I had no answer. I had been following my exposure, not my passion. So I pivoted, pursued a master's degree in something that actually lit me up, and never looked back. But that's a story for another day.
The same thing is happening now with AI. Students hear "learn AI" and think they need to become engineers. They hear "entry-level jobs are gone" and assume there is nothing left for them.
Neither is true.
The students who thrive won't be the ones who panicked and pivoted away from everything they built. They'll be the ones who looked forward, layered AI onto their existing strengths, and moved with intention.
Como decía mi mamá: "El que adelante no mira, atrás se queda." (Like my mother always said, "He who doesn't look ahead stays behind.")
The formula is simple: AI fluency + human wisdom = the new entry-level advantage.
THIS WEEK’S INSIGHTS:
In an AI-driven world, the students and early-career professionals who thrive won't be the ones who abandon their education. They'll be the ones who layered AI literacy on top of it.
The "AI + Your Expertise" Equation.
The future isn't AI replacing your field. It's AI amplifying it.
AI + Law.
AI + Healthcare.
AI + Business Strategy.
AI + Communications.
Every discipline is being augmented, which means domain expertise is still the foundation. The students building the strongest edge are those pairing deep subject matter knowledge with the ability to guide, prompt, and evaluate AI output. According to a 2024 Microsoft and LinkedIn Work Trend Index, 66% of leaders say they wouldn't hire someone without AI skills, and yet AI fluency without domain expertise is still not enough. Both matter.
Prompt Engineering Is the New Excel. In the 1990s, knowing how to use a spreadsheet was a differentiator. Today, knowing how to ask AI the right questions, with context, constraints, and clarity, is becoming equally essential. Research from OpenAI and the University of Pennsylvania found that large language models have the highest exposure to occupations requiring higher levels of education, which means white-collar roles must evolve, not disappear. Learning to guide AI well is how early-career professionals future-proof their relevance.
Human Skills Are the Moat. What AI cannot replicate, including critical thinking, emotional intelligence, ethical reasoning, adaptability, and the ability to build trust, are the exact capabilities that will define long-term career success. A Harvard Business Review analysis by Accenture researchers found that the most durable professionals in the AI era are those who combine "intelligent interrogation" of AI tools with integration of human judgment, exactly the fusion of technical fluency and interpersonal capability that compounds over time. Students who develop both sides of that equation now are building a career moat that compounds over time.
TRENDS
"AI + Major" Is the New Power Move
The narrative is shifting from "learn to code" to "learn to collaborate with AI in your field." Pre-law students are using AI-powered legal research tools. Marketing students are running campaigns with generative AI. Healthcare students are exploring AI diagnostic tools. The students gaining real traction aren't abandoning their disciplines. They're becoming the most AI-fluent practitioners within them. The competitive edge belongs to the person who understands both the domain and the technology.
Entry-Level Is Being Redefined, Not Deleted
The entry-level jobs disappearing are largely the ones built around the execution of routine, templated work, exactly the tasks AI handles well. The entry-level jobs being created require AI oversight, prompt refinement, output evaluation, and human judgment layered on top. This is a meaningful distinction. Students who graduate understanding that they are the quality-control layer on top of AI will arrive job-ready in a way their peers do not.
Parents Are the Hidden Audience in the AI Conversation
The anxiety in households right now is real and largely going unaddressed. Parents are making high-stakes decisions, encouraging major changes, questioning tuition spend, and pushing students toward tech, based on headlines rather than nuance. The most impactful conversations happening around AI adoption right now aren't just in boardrooms. They're happening at dinner tables. Organizations, educators, and leaders who speak directly to families about the AI transition are filling a significant gap.
3 MYTHS TO REFRAME
Myth #1: "My student should drop their major and just learn AI engineering instead."
Why we believe it: The headlines scream that traditional jobs are being wiped out, and "learn AI" has become the reflexive advice for every career concern. It feels proactive and protective to steer students toward what seems like the safe, future-proof path.
Reframe: AI engineering is one path, and an important one, but it's not the only path to AI fluency. The most in-demand professionals of the next decade will be domain experts who also know how to work with AI, not just engineers who build it. A communications major who can write, think strategically, and leverage AI tools is extraordinarily valuable. A biology student who understands how to integrate AI into research or clinical workflows has a rare combination of skills. Abandoning expertise mid-stream often means losing the very foundation that makes AI literacy meaningful.
Try This: Have your student identify two or three AI tools actively used in their specific field right now and spend one week experimenting with them. Search "[their major] + AI tools 2025" and see what practitioners are using. This grounds the conversation in reality rather than headlines.
Myth #2: "Entry-level jobs are gone. There's nothing left for new graduates."
Why we believe it: Layoff announcements are loud and viral. Junior role eliminations make the news. It's easy to pattern-match those headlines into a conclusion that there's no room left for people just starting out.
Reframe: Entry-level roles are being restructured, and in many sectors, the WEF Future of Jobs Report anticipates growth in entry-level headcount where AI skills are embedded. The graduates who arrive knowing how to use AI tools, write effective prompts, evaluate AI output critically, and apply human judgment on top are not competing with AI. They're the ones qualified to oversee it. That is an entry-level advantage, not a liability.
Try This: Instead of searching "jobs being eliminated by AI," search "jobs being created by AI in [field]" and spend 20 minutes reviewing what skills those roles require. Use that as a roadmap for the next semester.
Myth #3: "AI fluency means learning to code."
Why we believe it: The early conversation around AI was dominated by engineers, data scientists, and developers. "Learn to code" became the shorthand for future-proofing your career, and that framing has stuck even as the tools have become dramatically more accessible to non-technical users.
Reframe: The most important AI skill for most professionals is not coding. It's prompting, evaluating, and applying. Knowing how to give AI clear instructions, how to assess whether its output is accurate and appropriate, and how to integrate it thoughtfully into real work are the skills that matter across nearly every field. You don't need to understand how the engine works to drive the car well.
Try This: Challenge yourself or your student to use one AI tool this week without any technical setup, just a free account and a real problem from class or work. Try Claude, ChatGPT, or Perplexity and bring a real question from your field. Notice how the quality of your input shapes the quality of the output. That instinct is the skill.
TOOLS
This week's recommendation: Perplexity AI
If there's one tool I'd put in the hands of every student and early-career professional right now, it's Perplexity. Think of it as a research engine that cites sources in real time, making it invaluable for academic research, industry exploration, and staying current without drowning in browser tabs.
How to use it: Bring a real question from your coursework or your job search. Ask Perplexity to synthesize the current landscape on any topic, like "What AI tools are being used in healthcare administration right now?" or "What skills are employers in marketing prioritizing in 2025?" and watch it surface credible, linked sources alongside a clear synthesis. For students, this is a game-changer for research papers, interview prep, and understanding how your field is evolving. For parents, it's a great way to get grounded, sourced context on the AI headlines before making big decisions.
Bonus tools by major:
- Pre-law: Casetext (CoCounsel) for AI-assisted legal research
- Marketing/Comms: Jasper for AI-powered content creation
- Data/Business: Julius AI for AI-driven data analysis and visualization
- Healthcare: Doximity GPT for clinical communication drafting
TRY IT THIS WEEK (Micro-Actions)
These are designed for you and for the students or young professionals in your life. Share this section freely.
1. The "AI + My Major" Search. Spend 15 minutes searching "[your field] + AI tools 2025." Find two tools being used by practitioners right now. You don't need to learn them this week. Just knowing they exist and what they do is the first step.
2. One Real Prompt, One Real Problem. Take an actual assignment, work challenge, or question you're sitting with right now and bring it to Claude or ChatGPT. Don't ask something generic. Bring the real thing. Notice how specificity changes the quality of what comes back. That's your first lesson in prompt fluency.
3. The Mentor Question. Identify one person in your field who is 5 to 10 years ahead of you. Ask them this question: "How has AI changed the way you work in the last 12 months, and what do you wish you had started learning sooner?" The answer to that question is your personalized roadmap.
4. Reframe the Dinner Table Conversation. If you're a parent, shift from "Is your major still worth it?" to "Are you building adaptability?" Ask your student what they're experimenting with. Curiosity and experimentation, not perfection, is the new competitive advantage.
What's one AI tool you or someone in your life is experimenting with right now, and what field is it being applied to?
Drop it in a reply. I read every response, and the best answers may become the subject of a future newsletter. The community is one of the richest resources we have. Let's use it.
Closing Thought
Dropping out to "learn AI" misses the entire point.
The students who will lead the next decade aren't abandoning their education. They're expanding it. They're the ones asking not just what AI can do, but how it applies to the work I am already called to do.
I didn't need to abandon biology to find my path. I needed someone to ask me the right question. That's still true today.
Your major isn't the problem. Your exposure to possibility is the variable.
AI fluency without human wisdom is just automation. Human wisdom without AI fluency is just potential waiting to be unlocked.
Together? That's your entry-level advantage. Use it.
El que adelante no mira, atrás se queda. Like my mom said, "Don't get left behind. Look ahead." Start now.
♻️ Share this post with a parent or student who needs to hear it.
Hasta la próxima, ¡Abrazos! 💃🏻
Monica Marquez
Before You Go...
The Proving Ground Has Changed
I found my path because one mentor asked me the right question at the right time. Not everyone gets that moment. And with entry-level roles disappearing faster than ever, fewer young people will have the chance to build their judgment through the traditional proving ground of early career work.
So we built a new one.
The FlipWork Apprenticeship
This is a 12-week hybrid program for college undergraduates and recent graduates who want to enter the workforce as AI-native professionals.
It runs on the same methodology FlipWork uses with Fortune 500 leadership teams, adapted for the people who will one day take their jobs.
The premise is simple: the fastest path to fluency is working alongside it. It's tackling real business problems and getting relentless, real-world feedback until collaborating with AI becomes pure instinct.
The Apprenticeship Blueprint
- Weeks 1–2 | The Diagnostic: Apprentices begin with a readiness assessment of their AI fluency, mindset, and skill gaps. They leave knowing exactly where they stand and where the highest-leverage work is.
- Weeks 3–8 | The Application: Apprentices are embedded in live AI workflow challenges modeled on real-world business problems across multiple functions. This combines live weekly cohort sessions with intensive applied work.
- Weeks 9–12 | The Capstone: Apprentices design and deploy a bespoke AI-assisted workflow for a real use case, setting direction, directing agents, evaluating outputs, and defending decisions before a panel of senior practitioners.
The next cohort launches in April. Seats are capped at 50 to preserve the quality of the live experience.
If you know a student, a recent graduate, or a rising professional who needs this, send me at [email protected] with "send apprenticeship details" in the subject, and I will get you everything you need.
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