Today is June 1st — International Children’s Day, observed around the world as a reminder that children are the foundation of our future and deserve education, care, and every opportunity to grow.
It is a fitting day to write this article. Because the question I have been turning over since a conversation with a school last week is ultimately a question about children — specifically, about what we are teaching them, what we are telling them their education is worth, and whether we are preparing them honestly for the world they are about to inherit.
The question is this: is classical education dead?
The conversation was lively. And the answer, delivered with more evidence than I expected, was a resounding no. In fact, the argument could be made that the humanities have never been more relevant. And as someone who spends every day thinking about artificial intelligence — building it, deploying it, and watching how others interact with it — I left that conversation with a perspective I want to share.
Because it turns out that the skills forged in a classical education are not the opposite of AI fluency. They may be its foundation.
The degree everyone apologized for
For at least two decades, the narrative in higher education has been relentlessly one-directional. STEM is the future. Code or be left behind. The humanities are charming but impractical. Philosophy teaches you to think but not to earn. English majors write beautifully about their unemployment.
Between 2012 and 2020, the number of bachelor’s degrees conferred in humanities subjects fell drastically — driven in large part by the perception that technical skills are the only currency that matters in a digital economy. Parents steered their children toward computer science. Guidance counselors framed the liberal arts as a luxury. And a generation of students quietly apologized for studying what they loved.
Then AI arrived. And something unexpected happened.
What great prompt engineering actually requires
Here is a question worth sitting with: what does it actually take to be great at prompt engineering — at communicating with AI in ways that produce genuinely useful, accurate, and nuanced results?
The answer is not Python. It is not statistics. It is not a computer science degree.
The future belongs to those who can speak both languages fluently: human and AI. And speaking human fluently — with precision, nuance, context, and rhetorical awareness — is exactly what a classical education trains you to do.
Think about what the humanities actually teach:
- Literature trains you to read closely, to notice what is said and what is implied, to understand that words carry meaning beyond their literal content.
- History trains you to reason from evidence, to understand context, to resist the seductive simplicity of a single explanation.
- Philosophy trains you to construct and dismantle arguments with rigor — to identify the hidden assumption in a line of reasoning, to question what everyone else accepts as given.
- Rhetoric teaches you that how you say something shapes what it means.
- Linguistics reveals that language itself is a system with rules, exceptions, and ambiguities that matter enormously.
Now think about what prompt engineering actually demands. You must communicate intent clearly to a system that is extraordinarily sensitive to how questions are framed. You must anticipate how an ambiguous word will be interpreted and resolve the ambiguity before it causes an error. You must construct a logical chain of instruction that the AI can follow without gaps. You must know when an output is subtly wrong — not obviously, catastrophically wrong, but wrong in the quiet way that only someone who deeply understands the subject matter would catch.
Rather than humans having to learn to talk the language of technology, AI is learning to talk our language — and that makes the ability to use human language with depth and precision more valuable than ever.
The philosophy major does not have to apologize anymore. They were training for this their whole academic career. They just didn’t know it yet.
The critical thinker in the room
There is a deeper point here that goes beyond prompt engineering as a job title.
Humanities and social sciences majors — philosophy, history, literature, linguistics, psychology — train students to analyze complex problems, assess various viewpoints, construct logical arguments, evaluate ethical issues, and question assumptions. These interactions sharpen the ability to challenge what others accept as given.
This is precisely what AI deployment in a professional context requires at every level. Not just the person writing the prompt — but the person reviewing the output. The person deciding whether the AI’s answer is correct enough to act on. The person who notices that the response was fluent and confident and completely wrong. The person who asks the question nobody else thought to ask: how do we know the AI actually understands this, rather than just pattern-matching its way to a plausible-sounding answer?
AI has limits because of unanticipated nuances in a task and its human and emotional elements. AI needs capable humans to manage it and pull the best from it. Those capable humans are not necessarily the ones who built the AI. They are the ones who understand human complexity well enough to know where the AI falls short — and rigorous enough as thinkers to hold it accountable.
In our experience building MERCED™, some of the most valuable contributors to testing, quality assurance, and output evaluation have not been engineers. They have been people who read deeply, think critically, question confidently, and write with precision. People who were trained — formally or informally — in the habits of mind that a classical education develops.
What this means for the industry — and for how we hire
There is a practical implication here that I think the moving and logistics technology space has not fully absorbed yet.
As AI becomes central to how SaaS platforms operate — generating outputs that affect pricing, compliance, customer communication, and operational decisions — the human layer around the AI becomes critically important. You need people who can evaluate what the AI produces with genuine rigor. People who will not simply accept a fluent answer as a correct one. People who can articulate, precisely and clearly, why an output is wrong and what a better one would look like.
Those people are not always found in computer science programs. They are found wherever serious thinking is taught and practiced — in philosophy departments, in history seminars, in literature courses where students are expected to defend an interpretation under pressure, in debate teams where the quality of an argument is everything.
Demand for creative thinkers and graduates of liberal arts courses could broadly become higher than ever thanks to AI. We believe that.
Classical education is not dead. It’s overdue for a reframe.
The school I visited last week is doing something quietly radical: teaching students not just what to think, but how to think. How to question. How to reason from evidence. How to construct an argument and test it against opposition. How to hold complexity without collapsing it into a simple answer.
These are not soft skills. In the age of AI, they are the hard ones. The ones that are genuinely difficult to develop, genuinely difficult to automate, and genuinely impossible to replace with a toggle in a third-party API.
The students sitting in humanities classrooms today may find themselves, in five years, doing work that did not exist when they enrolled — evaluating AI outputs, designing prompts for high-stakes professional applications, catching errors that no benchmark would ever flag, and asking the questions that keep AI systems honest.
They were training for this. The world just needed AI to arrive before it could see it.
