Beyond Human-Readable: Rethinking Software Engineering Conventions for the Agentic Development Era

This project is currently a theoretical proposal (paper-based) with no community traction (0 stars) and no practical implementation. While the premise—that the 60-year-old paradigm of 'code for humans' is suboptimal for agents—is insightful, it faces extreme frontier-lab risk. Companies like Microsoft (GitHub), OpenAI, and Anthropic are already the primary drivers of agentic coding interfaces. If a 'non-human-readable' intermediate representation for code becomes necessary, these platforms will likely implement it as an internal optimization layer (e.g., within Copilot or Canvas) or a specialized tokenizer, rather than adopting an external academic standard. The project lacks a 'moat' because it provides a conceptual framework rather than a tool or a dataset. Its primary value is in identifying the 'semantic density' bottleneck, but the solution will likely be absorbed by the platforms that control the IDE and the LLM context window. Displacement is likely within 1-2 years as agentic tools move from 'chatting about code' to 'operating on code' via more efficient internal representations.