Why AI Hasn't Replaced Software Engineers, and Won't
Hacker News (AI keywords)3 days agoOpinionBased only on the title, this appears to be a commentary on the limits of AI in software engineering. It likely argues that coding is only one part of the engineering role, while judgment, system design, debugging, product context, and accountability remain human-centered. The piece is relevant to developers and technical leaders evaluating AI coding tools without assuming full automation is imminent.
Hot take: "Vibecoding" is being used for two different things and it causes unnecessary friction
r/LocalLLaMA top day4 days agoCommentaryA Reddit user argues "vibecoding" carries two distinct meanings: throwing code at AI carelessly with no engineering judgment, versus using heavy AI assistance while still maintaining quality standards. Andrej Karpathy's own practice almost certainly fits the second definition, not the first. This semantic ambiguity fuels unnecessary arguments whenever the community debates AI-assisted development quality.
Anthropic Releases Claude Fable 5, Its First Mythos-Class Model★ 78
The Verge AI5 days agoReleaseAnthropic has released Claude Fable 5, the company's most powerful model ever made widely available and its first under the new 'Mythos' model class. The model shows exceptional performance across software engineering, knowledge work, and vision tasks. Its advantage over competing models reportedly grows wider as tasks increase in length and complexity, making it particularly suited for demanding, multi-step workloads.
Tokenomics: Quantifying Where Tokens Are Used in Agentic Software Engineering
Hacker News (AI keywords)7 days agoPaperThis arXiv paper studies token consumption in LLM-based multi-agent software engineering. Using 30 ChatDev tasks with a GPT-5 reasoning model, the authors map internal phases to SDLC stages such as design, coding, review, testing, and documentation. Preliminary results suggest code review dominates token usage, averaging 59.4%, while input tokens form the largest share, pointing to inefficiencies in agent collaboration.
AlphaEvolve：Google DeepMind 基於 Gemini 的程式碼 Agent 如何在各領域擴大影響力★ 80
Google DeepMind Blog39 days agoReleaseGoogle DeepMind has recently shared the latest progress and real-world impact of its new coding agent "AlphaEvolve." AlphaEvolve is an algorithmic system…
評估驅動開發（Eval-driven development）：更快打造更好的 AI 應用★ 80
Vercel Changelog605 days agoOpinionAs generative AI applications become more widespread, one of the biggest challenges developers face is the "non-deterministic" output of large language models…
Hugging Face 的設計哲學：為什麼我們反其道而行，選擇「重複程式碼」？★ 85
Hugging Face Blog1,531 days agoOpinionThis classic blog post from Hugging Face examines the tension between software engineering principles and the demands of machine learning (ML) research…
機器學習即程式碼（ML as Code）的時代已經到來：Hugging Face 談開發者導向的 AI 新典範
Hugging Face Blog1,698 days agoOpinionThis classic 2021 article from Hugging Face declared the official arrival of the "Machine Learning as Code" (ML as Code) era. The central argument is that…