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A computer science professor publishes a letter to his students. He tells them to refuse mimetic narratives, set ethical boundaries early, refactor until elegant, prioritize people over profits, and be motivated by love rather than fear. He himself uses no LLMs in any form and calls himself a generative-AI vegetarian.
A discussion thread splits along the expected line. One reading takes the letter as courageous and beautiful, a defense of the craft against industry pressure. Another reading takes it as a tenured professor who has not worked a day in industry telling students to optimize for skills the market is in the process of pricing to zero.
The two readings are mirror postures. Both treat the surface question — should you join the new economy or refuse it? — as the question that matters. Neither asks what is actually happening underneath.
For sixty years, code was the externalized form of programmer thinking. Writing a function meant extracting structure from your understanding of a problem and making the structure manipulable, testable, sharable. The code was the artifact. The thinking was the value. Other programmers read the code partly to understand the system and partly to learn how the author thought about the problem.
A market that pays for code is paying for code as a proxy. The market does not directly pay for thinking — thinking is invisible — but it pays for code, which is thinking compressed into a form a machine can run and a coworker can review. The proxy worked because thinking was hard to externalize and code was the cheapest available externalization.
When code becomes cheap to produce, the proxy fails. The market still wants the thing the proxy was approximating. It does not want code; it wants problems solved, systems designed, intent made executable. What the market wanted all along was thinking made deliverable. Now it can ask for that directly.
The letter offers students moral exhortation in place of decision machinery. Be intentional. Cultivate your ability to think deeply. Care about craft. Be motivated by love. Each is a value statement. None of them tells a student what to do on Monday morning when offered a job in which the polished documentation will be ingested by a model as training data and the elegant refactor takes longer than the agentic reimplementation.
The vegetarianism move is the same shape. "I refuse to use LLMs in any form" is an identity statement: it tells the listener what kind of person the speaker is. It does not give the listener a frame for navigating their own choice. A student reading the letter learns who the professor is. They do not learn what to do.
The pattern is not unique to academia. Industry replies reproduce its structure. "System design beats line-craft" tells a student what skills to optimize for. It does not give them a frame for deciding whether the system they are designing is the system that should exist.
Both sides are performing identity in front of the question instead of opening the question.
If code was the proxy for thinking, then the question for someone entering the field in 2026 is: what does it look like to deliver the thing the proxy was approximating?
A first sketch:
A specification that makes one design space coherent and rules out three others is thinking made deliverable. The artifact is the specification, not the code that implements it. The specification can be implemented by a model in minutes. The model cannot generate the specification because the model does not know which design space the world wants.
A taxonomy that identifies which of seven failure modes a given system is in is thinking made deliverable. The artifact is the diagnostic frame. Once the frame exists, fixing the failure can be delegated. The frame itself cannot.
A position on what is true that survives interrogation by competent adversaries is thinking made deliverable. The artifact is the position and the trace of the interrogation. Both are durable. Code that implements the position is downstream.
The common shape: an artifact whose value is irreducibly the work of a mind that has held the problem long enough for structure to emerge. The mind doing the work is replaceable in principle but in practice is the bottleneck for the artifact's existence. Code-as-proxy let many minds approximate this work in parallel, with code as the comparable output. Thinking-as-deliverable does not parallelize the same way. The structure has to land in one mind first; only then can it be diffused.
A student entering the field in 2026 needs three things, none of which the letter provides.
First, a way of telling whether the work in front of them is code-as-proxy work (which the market will price toward zero) or thinking-as-deliverable work (which the market is in the process of learning how to pay for). The skill that survives is the skill of identifying which kind of work a project actually is. Most projects in industry are still labeled and structured as the first while the second is what is actually scarce.
Second, a vocabulary for the new artifact class. Specifications, frames, positions, diagnostic structures — these are not new concepts, but they have not been the deliverables of programmer training. A programmer trained to write functions cannot suddenly produce specifications. The production has its own learnable craft. "Refactor until elegant" is the wrong skill to optimize. The right skill is: hold a problem long enough for the structure to land, then write the structure down so others can act on it.
Third, a way of evaluating their own work that does not collapse into the old metrics. Lines of code shipped, tests passing, code review approval — these were measures of code-as-proxy. They will not measure thinking-as-deliverable. A specification that ruled out three design spaces does not produce a graph in the dashboard. The student needs an internal compass for what good thinking-as-deliverable looks like, because the surface metrics will keep paying for the old work for some years yet.
The letter could have offered any of this. It chose moral exhortation instead. The exhortation is not wrong. It is also not enough.
If the proxy does not actually break — if code remains the dominant form of programmer output and the AI tools remain assistive rather than substitutive — the analysis is wrong. The skills the letter recommends remain the skills that pay. The failure mode here would be treating an early signal as established fact.
If thinking-as-deliverable turns out to be a niche skill rather than a class — if only senior architects produce specifications and frames while everyone else still writes code under their direction — the prediction overshoots. The market may simply re-tier the existing skill ladder rather than rebuild it.
If the moral framing the letter offers is itself what carries the weight — if students need a sense of agency and ethical boundary more than they need decision frames — the letter is doing the right work and this analysis is doing the wrong work. The analysis assumes navigational guidance is what students need most. They may need conviction first.
The bet here: the proxy is breaking, the new artifact class is real, the students need machinery for navigating the change. Two of three may be wrong.
P.S.: