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According to Boris Churney, the specific programming language a developer uses is becoming less important because the AI model doesn't care. While features like type-checking currently help guide the model, future AIs will be sophisticated enough to write perfect code directly in low-level languages like assembly, abstracting away language choice entirely.
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For 50 years, software development operated at one level of abstraction: humans writing software. AI agents introduced a new level: humans telling models to write software. Now, advanced routines introduce a third level: models telling other models what to do, representing an unprecedented acceleration in programming abstraction.
Andreessen speculates that as AIs become the primary creators of software, human-readable programming languages could disappear. AIs might directly emit optimized binaries or even new model weights, shifting the human role from writing code to interpretability—asking the AI to explain its own systems.
AI coding has advanced so rapidly that tools like Claude Code are now responsible for their own development. This signals a fundamental shift in the software engineering profession, requiring programmers to master a new, higher level of abstraction to remain effective.
Marc Andreessen predicts that as AIs become the primary creators of software, the need for human-readable programming languages will vanish. These abstractions exist for human limitations. Future systems will likely generate optimized binaries or even model weights directly, making language debates obsolete.
The core task of writing code is no longer a significant challenge for AI. The focus is shifting to adjacent tasks and higher-level problem-solving, as demonstrated by Boris Cherny, who hasn't manually written code since November 2024.
Generative AI is making the task of writing syntactically correct code obsolete. The core value of a software engineer is shifting away from implementation details and towards the higher-level "thinking" tasks: understanding user needs and designing robust systems.
The craft of software engineering is evolving away from precise code editing. Much like compilers abstracted away assembly language, modern AI coding tools are a new abstraction layer, turning engineers into directors who guide AI to write and edit code on their behalf.
In the near future, developers may no longer write code in languages like Python or Javascript. AI, with its deep understanding of hardware, could translate human intent directly into binary, making infrastructure decisions like database selection entirely obsolete.
The paradigm for creating software has shifted from writing code to writing natural language. Founders report a new workflow: speaking English to an AI, which then writes English prompts for other programs to generate the final code. This fundamentally changes the nature of software engineering and productivity.
Programming languages like Python were designed for human readability. As AI models become the primary producers and verifiers of code, the dominant languages will likely shift to ones optimized for machine generation and formal verification. The focus will move from human convenience to provable correctness and efficiency for AI agents.
