@interjc: Now it's all natural language programming, and to be fair, this has raised the bar. In the past, many people wrote good…
Summary
The tweet discusses how natural language programming has raised the bar for coding, criticizing that without clear thinking, output remains poor regardless of token usage.
View Cached Full Text
Cached at: 09/15/26, 11:54 PM
Now it’s all natural language programming, and to be fair, this has raised the bar. In the past, many people wrote good code by standing on the shoulders of framework authors. Now, people with unclear thinking and logic, who can’t even express themselves clearly, or don’t even know what they want, even if they burn through the world’s entire supply of tokens all by themselves, what they produce is still just a steaming pile of crap.
Vincent (@Vincent_AINotes): 今年好像已经没人争论Vue和React谁更好了。去年网上动不动就能刷到前后端吵架互撕,今年基本看不到了,清静不少😂
Similar Articles
@karpathy: The hottest new programming language is English
A commentary on how large language models and AI have made English an effective programming language, reflecting the shift toward natural language interfaces for coding tasks.
@lateinteraction: whatever you think of the labs' under-investment in clear and delightful writing, in favor of skills like math and codi…
The post highlights that AI labs' under-investment in clear writing skills compared to math and coding has significantly harmed their public perception.
@dzhng: https://x.com/dzhng/status/2090252351533973768
The article discusses the challenge of AI-generated code 'slop' due to human review bottlenecks and argues that software engineering must evolve to focus on system design rather than code readability.
Programming is dead. Engineering is thriving (4 minute read)
G5 Labs raises $14M seed funding to launch a platform that uses natural language as source code, aiming to transform software development into an AI-native process with a new abstraction layer.
@saranormous: https://x.com/saranormous/status/2064510215056400652
Despite rapid advances in AI coding agents like Devin, which have dramatically increased code writing and shipping, the article argues that the most valuable aspects of software engineering remain illegible to benchmarks and require human judgement and organizational coordination that cannot be easily automated.