TL;DR
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In a February 27, 2026 essay on htmx.org, Montana State University computer science instructor Carson Gross advises aspiring programmers to continue learning and use AI as a teaching assistant rather than a substitute for writing code. He argues that code-reading, communication and understanding organizations’ needs may become more important as AI changes programming work.
Montana State University computer science instructor Carson Gross advises people considering programming careers to continue learning to code as AI tools spread. In a February 27 essay published on htmx.org, Gross recommends using those tools as tutors rather than code generators. He argues that hands-on coding experience helps students understand and evaluate programs produced with AI.
Gross answers the question of whether people should still become programmers with “Yes, and…” He describes programming as solving problems with computers and managing the complexity of those solutions. He argues that these abilities are likely to remain valuable as AI changes how software is written.
Gross directs his main warning at junior programmers and students. He argues that learners who rely on AI to produce code instead of writing it themselves may miss experience needed to understand how code works. That, he says, could make them less able to read, check and control software generated with AI.
Gross rejects the comparison between prompting an AI model and moving from assembly language to higher-level programming languages. He says traditional compilers behave predictably enough for programmers to reason about how source code maps to machine instructions. AI-generated solutions, by contrast, can vary and may add complexity or use unsuitable approaches, he argues.
Gross also describes using AI as a teaching assistant that explains concepts, suggests techniques or helps students address problems with tools and development environments. He says he has shared an AGENTS.md file intended to guide coding agents toward that role. The essay does not report results from a formal study of the approach.
The Skills AI May Not Replace
Gross’s advice addresses how students, families and educators might approach programming education when AI can generate working code. He argues that AI may change programming work, while understanding software, explaining problems clearly and identifying an organization’s needs could remain important skills.
Gross says students who use AI to bypass parts of learning may be less prepared to identify errors or assess whether a generated solution is appropriate. He suggests that using AI to clarify concepts and address technical obstacles can leave more time for learning. The essay presents his perspective as an instructor and does not establish whether this approach works equally well for every student or workplace.
Gross predicts that raw code-writing skill could lose relative importance, while communication and knowledge of the organization a programmer serves could matter more. These are forecasts, not established outcomes; the pace and scale of any change remain uncertain.
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Gross’s Case for Writing Code
Gross says he teaches computer science at Montana State University and wrote the essay in response to questions from relatives, friends and students about whether AI makes a programming career a poor choice. He distinguishes between generating code and developing the judgment to understand it.
Gross warns that students who cannot read code may create systems they do not understand or control, a risk he calls the “Sorcerer’s Apprentice Trap.” He says writing code is one way to build the familiarity needed to read it later, and advises students not to let AI complete assignments in their place.
Gross also describes technical obstacles as a barrier to learning. He recalls struggling to learn Unix while studying at Berkeley and says that difficulty contributed to his leaving the computer science program there. In the essay, he presents AI tutoring as a way to help learners address obstacles that consume time without teaching the programming concept at hand.
“You have to write the code.”
— Carson Gross, describing his advice to students
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How Programming Work Will Change
The essay does not quantify how many programming tasks AI can perform, how quickly demand for programmers may change, or which roles could be most affected. Gross’s expectations about the future value of communication, business knowledge and code-reading are his analysis and predictions, not measured labor-market findings.
It is also unclear how reliably AI tools can act as tutors across different subjects, students and coding environments. Gross says he has published guidance for configuring coding agents, but the essay provides no controlled comparison of students using that approach with students using other methods. It does not establish whether his advice will produce better learning or employment outcomes.
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How Students Can Apply the Advice
Gross’s essay does not announce a new program or specify a future milestone. It recommends that learners write code themselves, then use AI to ask questions, clarify concepts and work through technical roadblocks. He also encourages students to develop clear writing and communication skills and to learn about the organizations whose problems they hope to solve.
Whether those skills become more important as AI tools develop will depend on how employers adopt the technology and how programming work changes. The essay provides no timeline for that shift. Gross’s teaching recommendations are distinct from broader claims about future jobs, which remain unsettled.
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Key Questions
What is Carson Gross’s advice to people considering programming?
Gross says yes, they should still consider it, while recognizing that AI will change programming. He advises learners to write code themselves and use AI to support their understanding.
Why does Gross say students should write code instead of generating it with AI?
He argues that writing code helps learners develop the familiarity needed to read, assess and control code later, including code produced by AI.
How does Gross recommend using AI as a teaching assistant?
He recommends asking AI to explain concepts, discuss techniques and help with technical obstacles, rather than using it simply to generate assignment solutions.
Does the essay show that AI will reduce programming jobs?
No. Gross discusses possible changes in the skills programming work rewards, but the essay provides no employment data or job-loss forecast.
Source: hn
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