TL;DR
A programmer and informal educator argues that large language models are not necessary to learn programming. The essay stresses learning by doing, using open resources, and interacting with other people to build lasting understanding.
What happened
In a personal essay published January 14, 2026, an experienced programmer—who also helps teach people with learning disabilities and neurodivergence—contends that LLMs are not required to learn programming. The author credits open-source projects, freely available books, tutorials, forums, meetups and conversations with colleagues as the primary mechanisms that built their skills. They argue that genuine mastery comes from curiosity-driven experimentation: reading source code, forming hypotheses, designing and running experiments, and iterating on failures. The piece contrasts this hands-on process with relying on LLMs for quick summaries or answers, suggesting that passive consumption delivered by an AI does not produce the same durable retention. The essay also highlights the social dimension of learning—practicing explanations and answering peers—which the author says strengthens understanding. It closes with practical encouragement to tackle projects, share work, and keep exploring foundational systems and tools.
Why it matters
- Highlights that active practice and experimentation are central to building deep, transferable programming knowledge.
- Reminds educators and learners that community resources and open-source materials remain powerful training grounds.
- Raises questions about whether convenience tools (like LLMs) can substitute for long-term retention and skill development.
- Emphasizes social learning—asking questions, teaching others, and getting feedback—as part of becoming proficient.
Key facts
- The author says they do not believe LLMs are necessary to learn programming.
- They describe themselves as responsible for teaching people with learning disabilities and neurodivergence but not as a formally trained teacher.
- The essay credits open-source code, free books, tutorials, forums, meetups and personal conversations as primary learning resources.
- The author argues that durable understanding requires doing the work: reading code, forming hypotheses, running experiments and iterating.
- They caution that relying on LLMs for summaries or solutions can encourage passive consumption rather than active practice.
- The piece notes that LLMs’ convenience and nonjudgmental interaction are appealing, especially for shy learners.
- Examples of concrete learning projects mentioned include Programming Language Foundations in Agda, NAND2Tetris, studying Postgres source code, refurbishing a Commodore 64, and implementing a hash table in C.
- The author uses the Linux kernel as an example of a large codebase people learn to contribute to without reading every line.
What to watch next
- Whether more learners favor LLM-driven shortcuts over hands-on experimentation — not confirmed in the source.
- How communities and meetups evolve if more people rely on AI assistants rather than direct human interaction — not confirmed in the source.
- Long-term effects of LLM use on retention and the ability to solve novel problems without external prompts — not confirmed in the source.
Quick glossary
- LLM (Large Language Model): A class of AI models trained on large text datasets that can generate human-like responses to text prompts.
- Open source: Software whose source code is made available for anyone to inspect, modify, and distribute.
- Linux kernel: The core component of the Linux operating system that manages hardware, processes, and system resources.
- NAND2Tetris: An educational project and course that builds a computer from basic logic gates up through a working system and compiler.
Reader FAQ
Does the author say LLMs are useless for learning?
The author says LLMs are not necessary and warns they can encourage passive learning, but also acknowledges their convenience and nonjudgmental availability.
How did the author learn programming?
From freely shared materials, open-source projects, tutorials, meetups, conversations, and hands-on experimentation.
Is interacting with other people important for learning?
Yes—the author argues practicing explanations, asking questions, and teaching others are key to solidifying knowledge.
Will LLMs replace traditional learning methods?
not confirmed in the source
Posted on January 14, 2026 I don’t think you need LLMs to learn programming. I recognize that people need different strategies and tools to learn new skills and information. I…
Sources
- I Learned Everything I Know About Programming
- How to Teach Effective Use of LLMs in Software Development
- learn to code with LLMs? i read a bunch of learning science …
- The art of programming and why I won't use LLM
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