๐Ÿ’ฅ Human-readable code just isnโ€™t that important anymore

Originally published on LinkedIn

๐Ÿ’ฅ ๐‡๐˜‚๐—บ๐—ฎ๐—ป-๐—ฟ๐—ฒ๐—ฎ๐—ฑ๐—ฎ๐—ฏ๐—น๐—ฒ ๐—ฐ๐—ผ๐—ฑ๐—ฒ ๐—ท๐˜‚๐˜€๐˜ ๐—ถ๐˜€๐—ปโ€™๐˜ ๐˜๐—ต๐—ฎ๐˜ ๐—ถ๐—บ๐—ฝ๐—ผ๐—ฟ๐˜๐—ฎ๐—ป๐˜ ๐—ฎ๐—ป๐˜†๐—บ๐—ผ๐—ฟ๐—ฒ Weโ€™re moving away from human hands on keyboards writing code โ€” toward AI-first engineering, where AI generates 100%, replacing handcrafted traditional coding.

That shift forces us to rethink what engineering standards even mean anymore. ๐Ÿ’ญ

Traditionally, coding standards exist for two main reasons: 1๏ธโƒฃ ๐—ฅ๐—ฒ๐—ฎ๐—ฑ๐—ฎ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐˜†: So humans can maintain and evolve the code. 2๏ธโƒฃ ๐—ฆ๐˜๐—ฟ๐˜‚๐—ฐ๐˜๐˜‚๐—ฟ๐—ฒ ๐—ฎ๐—ป๐—ฑ ๐—พ๐˜‚๐—ฎ๐—น๐—ถ๐˜๐˜†: Ensuring sound architecture, separation of concerns, scalability, resilience, and other non-functionals.

Ultimately, both feed into maintainability โ€” the first from an understanding perspective, and the second from an extensibility perspective.

But in an AI-first world, it's a question whether the first even matters anymore.

Iโ€™m not saying we should have junk code โ€” AI, like humans, still benefits from clear structure. If itโ€™s unreadable, itโ€™ll struggle just like you or me. But the difference is in the minutiae โ€” the little things we used to obsess over: tabs vs spaces, newlines, bracket positions, variable naming conventions.

If those things matter, linting tools and auto-formatters can enforce them.

Or better yet, have Copilot or your codegen AI apply your teamโ€™s standards automatically. If your AI context includes your style rules (Cursor config, rule files, etc.), it should already be generating compliant code.

So why spend time in PRs nitpicking style? Why manually rewrite what an AI could auto-correct in seconds โ€” or even change it at all if itโ€™s already readable and understandable to both the AI and any human who might need to look at it? ๐Ÿค” Whatโ€™s the real value in that?

๐—ง๐—ต๐—ฎ๐˜โ€™๐˜€ ๐—ป๐—ผ๐˜ ๐˜„๐—ต๐—ฒ๐—ฟ๐—ฒ ๐—ฎ๐—ป ๐—ฒ๐—ป๐—ด๐—ถ๐—ป๐—ฒ๐—ฒ๐—ฟโ€™๐˜€ ๐˜ƒ๐—ฎ๐—น๐˜‚๐—ฒ ๐—น๐—ถ๐—ฒ๐˜€ ๐—ฎ๐—ป๐˜†๐—บ๐—ผ๐—ฟ๐—ฒ. ๐Ÿšซ

๐—”๐—ป ๐—ฒ๐—ป๐—ด๐—ถ๐—ป๐—ฒ๐—ฒ๐—ฟโ€™๐˜€ ๐˜ƒ๐—ฎ๐—น๐˜‚๐—ฒ ๐—ถ๐˜€ ๐—ถ๐—ป defining how the system should work โ€” its patterns, its non-functionals, its scalability, its resilience. Not in writing code, but in architecting and shaping it. Not in fixing syntax, but in defining acceptance criteria that ensure the code meets intent.

There are a hundred valid ways to write a solution. If two versions meet the requirements, are maintainable, and perform well โ€” does your stylistic preference really matter?

So to engineers: ๐Ÿ‘‰ ๐—”๐—ฟ๐—ฒ ๐˜†๐—ผ๐˜‚ ๐—ฟ๐—ฒ๐—ฎ๐—ฑ๐˜† ๐˜๐—ผ ๐—น๐—ฒ๐˜ ๐—ด๐—ผ ๐—ผ๐—ณ ๐—ฐ๐—ฎ๐—ฟ๐—ถ๐—ป๐—ด ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐˜€๐˜๐˜†๐—น๐—ฒ ๐—บ๐—ถ๐—ป๐˜‚๐˜๐—ถ๐—ฎ๐—ฒ โ€” ๐—ฎ๐—ป๐—ฑ ๐˜‚๐˜€๐—ฒ ๐Ÿญ๐Ÿฌ๐Ÿฌ% ๐—ผ๐—ณ ๐˜†๐—ผ๐˜‚๐—ฟ ๐˜๐—ถ๐—บ๐—ฒ ๐—ผ๐—ป ๐˜„๐—ต๐—ฎ๐˜ ๐—ฟ๐—ฒ๐—ฎ๐—น๐—น๐˜† ๐—บ๐—ฎ๐˜๐˜๐—ฒ๐—ฟ๐˜€?

To tech leadership: ๐Ÿ’ก ๐—ช๐—ต๐—ฎ๐˜ ๐—ฑ๐—ผ ๐˜†๐—ผ๐˜‚ ๐˜„๐—ฎ๐—ป๐˜ ๐˜†๐—ผ๐˜‚๐—ฟ ๐˜๐—ฒ๐—ฎ๐—บ๐˜€ ๐˜๐—ผ ๐—ณ๐—ผ๐—ฐ๐˜‚๐˜€ ๐—ผ๐—ป โ€” perfect-looking code, or scalable, well-structured systems delivered faster?

Iโ€™ve had countless discussions on LinkedIn debating whether AI can code. Thatโ€™s not the question โ€” we know it can.

โœ… Many engineers are already using it to generate 100% of their code today.

The real question now is how we adapt our engineering practices.๐ŸŒ