Forget STEM, The Future Ready Skills Curriculum is ECPM

Bonus Points if you Can Name Why this School Looks Familiar

Articles and perspectives considering the end of STEM education, given the rise of AI, have been filling my inbox lately. And in fairness and to be clear, STEM professionals are pointing, “of course not, Math will always be a critical skill, and Science is clearly more than an LLM doing research,” no indeed, STEM isn’t dead. But the demise of likely hundreds of thousands of engineering jobs raises a question fun to consider, and it’s clear many are doing so; what is future ready skills curriculum?

Ossiana Tepfenhart wrote in Medium, a year ago, that Gen Z is turning away from STEM. The LA Times, with UC San Diego’s workforce researcher and education Professor, John Skrentny, wrote a year before that, why pushing STEM is turning out to be a terrible investment. Brick Labs’ John Neretlis, “STEM is Dead.”

We can argue about if it’s true but that’s not why I’m here. Reading a lot about education, EdTech, and curriculum this weekend, I couldn’t help but keep thinking that while it isn’t dead, it’s important to still ask “what’s next?” Or perhaps, what is increasingly important in this emerging future??

AI does not replace technology.
AI replaces pattern recognition and execution.

The future belongs to people who understand people.

STEM teaches you how systems function. ECPM teaches you how humans behave inside those systems. And markets are human systems.

Economists such as David Autor at MIT have demonstrated that automation displaces routine, rule-based tasks while increasing the value of non-routine analytical and interpersonal work. The data shows polarization: middle-skill routine jobs decline; roles requiring judgment, coordination, persuasion, and problem framing increase in relative value.

Notice what that isn’t: it isn’t coding.

It’s decision-making, interpretation, coordination, and influence.

So, drawing from my online marketing past where a CPM is a measure of value (in online advertising), I got giddy at the implication of realizing that there is an acronym for a future in education that orients people better to creating value: ECPM.

Economics: Allocation of Scarce Resources

AI can model markets, it does not allocate capital or talent, and it isn’t going to deal with these looming questions of needing UBI (Universal Basic Income) or a mythical Post-Scarcity Society.

Capital allocation remains a human governance problem. Even in algorithmic trading environments, humans define risk tolerance, regulatory boundaries, and strategic objectives; we might be able to automate away hedge funds or day trading but actual capital allocation in society requires far more than math.

The OECD has repeatedly emphasized that entrepreneurship and productivity growth depend on efficient resource reallocation toward high-growth firms. Understanding incentives, marginal tradeoffs, opportunity cost, crowding out effects, and capital formation is what determines long-term prosperity.

If you don’t understand economics, AI becomes a productivity amplifier for someone else’s strategy.

You become the labor input.

Communications: Coordination at Scale

Psychologist Daniel Goleman (look at that, can you guess what the P is going to be?) has published research on leadership effectiveness consistently linking communication clarity to performance outcomes.

I want to highlight communication clarity there because most of my work with startups and governments is oriented to clearer communication setting proper expectations. I’m astounded by how many founders push back on pitch (communication) feedback when we talk about investor expectations; I’m not trying to get you funding, I’m trying to help you fix that what you’re saying doesn’t add up!

Language organizes coordination.
Markets are coordination machines.

AI generates text; it does not bear reputational consequences.

The workforce advantage in an AI world will go to those who can synthesize complexity, persuade stakeholders, frame decisions, negotiate tradeoffs, and align distributed actors.

Communication is not presentation skill. It is institutional architecture.

Psychology: Understanding Incentives and Cognitive Bias

AI models process information; they do not experience motivation. Markets are not equations; they are networks of human bias.

Daniel Kahneman’s work in Thinking, Fast and Slow and decades of behavioral research demonstrate that humans systematically deviate from rational models. Framing effects, loss aversion, anchoring, and status quo bias, these distort decisions every day.

AI can identify patterns in that data.
It cannot live inside the bias.

The person who understands cognitive load, fear responses, emotional triggers, and decision fatigue will design products, policies, and businesses that AI executes or engineers build.

Psychology is not soft science, it’s leverage.

Marketing: Value Perception, Not Product Engineering

If you think technology wins markets, you have not read history.

The QWERTY keyboard survived because of adoption lock-in, not engineering superiority. VHS beat Betamax for distribution reasons. Apple captures profit margins because of brand positioning, not semiconductor design.

Marketing is the applied science of value perception.

This time, I read The Effects of a Market Orientation of Business Profitability, in the Journal of Marketing , thanks to UC Berkeley’s John C. Narver and Colorado State University’s Stanley F. Slater. Repeatedly shown, well beyond that work, is that that customer orientation and market intelligence correlate strongly with firm performance. Simply put, is one of my frequent rants: marketing is not advertising and if you think it is, you’re hopefully appreciating by poor marketing is the second leading cause of startup failure.

Companies that understand customer behavior outperform those that focus purely on product excellence.

AI will optimize messaging and segment audiences.
It cannot decide what humans should care about.

That is a psychological and economic judgment.

More than in startups, in startup ecosystems (which I study and explain extensively) regions that emphasize invention over meaningful narrative capably distributed repeatedly underperform.

Technology without market alignment is academic theater.

Hopefully Clear, ECPM Wasn’t Just About STEM, it Makes Us Consider, “Yeah, but AI?”

Large language models and generative AI systems excel at synthesis and execution of structured data. They predict next tokens.

• They do not originate goals.

• They do not carry moral accountability.

• They do not own risk.

Humans who understand economics, communications, psychology, and marketing already determine:

• What problems matter

• What tradeoffs are acceptable

• What narratives drive adoption

• What incentives shape behavior

STEM builds the machine.

ECPM decides why it exists.

The labor market data already reflect this. LinkedIn’s 2025 Global Skills Report shows rising demand for skills like strategic thinking, communication, and relationship management. Wait, let me actually parse this a bit – they have, Conflict Mitigation (psychology and communication), Adaptability (marketing), Process Optimization (economics and marketing), Public Speaking (hopefully I don’t need to point this one out), Solution Based Selling (are you following me yet? marketing and psychology), Customer Engagement & Support (marketing, psychology, and communication), Budget & Resource Management (economics and marketing), Go To Market Strategy (I’m not even), Growth Strategy (ffs, it’s like they wrote my article), and Risk Assessment (marketing and economics). McKinsey’s 2023 report on generative AI concludes that roles requiring social and emotional skills are less automatable.

Routine cognitive execution is compressing in value.
Judgment, coordination, persuasion, and capital allocation are not.

“Engineering is Dead? b.s.” I’m not saying that or you’re not paying attention

Engineers who understand ECPM will lead.
Engineers who do not will be managed.

Founders who study market psychology build scalable companies.
Founders who worship product complexity build demos.

Policy professionals who understand incentives design durable ecosystems.
Those who chase innovation theater subsidize activity without value.

If you want to remain distinct from AI, become the person who decides what is done with STEM, how it is governed, and what humans are incentivized to do around it all, that’s ECPM.

Economics, Communication, Psychology, and Marketing
Not as electives: as core curriculum.

STEM remains essential but STEM alone produces implementers (and again, not paying attention if that makes you angry as a STEM professional, I didn’t say STEM produces implementers, I said STEM alone). ECPM produces strategists.

The future of the workforce is not anti-technology; it is pro-human behavior. Are you training students to build tools or to allocate power?

AI will handle the former while the latter remains human.

For now, for a few years, advantages will go to those who can code fastest as we transition into AI. In time, as it always ultimately has, it will go to those who understand why anyone cares.

ECPM: Economics, Communications, Psychology, Marketing.

Here’s why THAT order: Future Ready Skills Curriculum

Economics comes first because everything begins with allocation: scarcity, incentives, and tradeoffs; if you don’t understand marginal cost, opportunity cost, capital formation, or incentive distortion, you’re just rearranging deck chairs. Economics is the structural layer.

Communications comes next because organizations fail not because they lack ideas but because they lack coordinated execution. Research on team performance consistently shows communication clarity predicts outcomes.

Psychology is still before even marketing (gasp! Yes, I said it) because incentives don’t operate on rational robots and while communication without psychology is in-and-of-itself a valuable still, adding psychology is everything. Keep in mind, incentives and decisions operate in biased humans. Behavioral economics exists precisely because psychology alters economic outcomes. Kahneman didn’t win a Nobel Prize for vibes, he won it because psychology changes markets. Speaking of which…

Marketing comes last because it’s applied behavioral economics at scale. Marketing is where economics and psychology meet persuasion in the real world. Narver & Slater’s market orientation research: firms that orient around customers outperform product-centric firms.

ECPM also has a strategic logic:

Structure > Alignment > Behavior > Adoption.

That’s the stack to teach. That’s what everyone should learn.

Know the school in the photo? Disagree with me? Want to put this in practice?