A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls.
GitHub introduces Rubber Duck, an experimental feature for the GitHub Copilot CLI designed to provide a second opinion during coding tasks. By leveraging a different AI model family than the primary orchestrator—such as using GPT-5.4 to review Claude models—Rubber Duck acts as an independent reviewer to catch architectural errors, logical bugs, and cross-file conflicts that a single model might miss due to inherent training biases.
Django co-creator Simon Willison predicts the emergence of a "dark factory" era in software development, where AI-driven automation handles the entire coding process without human intervention. Drawing an analogy from automated manufacturing, Willison suggests that if machines can operate reliably without human oversight, there is no need for "lights on" monitoring. As AI tools increasingly take over complex programming tasks, the role of human developers may shift from writing code to merely providing creative direction. This evolution raises significant questions about the future of the global workforce and the potential for widespread displacement in the tech industry.
Simon Willison details creating a custom macOS presentation app, "Present," in just 45 minutes using Swift and SwiftUI. Frustrated with the risk of browser crashes when presenting a series of web pages, he built an app that displays URLs as slides, offering features like full-screen mode, keyboard navigation, and automatic URL saving. He even added remote control functionality via a web server and Tailscale.
The project highlights the power of AI-assisted coding and expands his skillset, demonstrating how experienced software engineers can quickly learn new languages and tools to solve personal problems. The resulting app is a simple, effective solution tailored to his specific needs.
The project highlights the power of AI-assisted coding and expands his skillset, demonstrating how experienced software engineers can quickly learn new languages and tools to solve personal problems. The resulting app is a simple, effective solution tailored to his specific needs.
This handbook provides a comprehensive introduction to Claude Code, Anthropic's AI-powered software development agent. It details how Claude Code differs from traditional autocomplete tools, functioning as an agent that reads, reasons about, and modifies codebases with user direction. The guide covers installation, initial setup, advanced workflows, integrations, and autonomous loops. It's aimed at developers, founders, and anyone seeking to leverage AI in software creation, emphasizing building real applications, accelerating feature development, and maintaining codebases efficiently. The handbook also highlights the importance of prompt discipline, planning, and understanding the underlying model to maximize Claude Code's capabilities.
Goose is a free, open‑source AI agent that runs locally and can autonomously plan, code, test, debug, and execute full development workflows—making it especially useful for data scientists who need to automate repetitive, multi‑step tasks. It supports any LLM, interfaces with file systems and APIs, and can extend its capabilities via the Model Context Protocol (MCP) to connect with databases, Git, Slack, and more.
- Autonomous task execution from high‑level instructions.
- Local execution preserves data privacy and control.
- LLM‑agnostic: works with GPT‑4, Claude, or local models.
- Two interfaces: desktop GUI and CLI.
- Extensible through MCP for external tools and services.
- Ideal for rapid prototyping, data pipeline automation, MLOps, and environment setup.
- Autonomous task execution from high‑level instructions.
- Local execution preserves data privacy and control.
- LLM‑agnostic: works with GPT‑4, Claude, or local models.
- Two interfaces: desktop GUI and CLI.
- Extensible through MCP for external tools and services.
- Ideal for rapid prototyping, data pipeline automation, MLOps, and environment setup.
>from the exit-statements dept.
Long-time tech journalist Clive Thompson interviewed over 70 software developers at Google, Amazon, Microsoft and start-ups for a new article on AI-assisted programming. It's title?
"Coding After Coders: The End of Computer Programming as We Know It."
Published in the prestigious New York Times Magazine, the article even cites long-time programming guru Kent Beck saying LLMs got him going again and he's now finishing more projects than ever, calling AI's unpredictability "addictive, in a slot-machine way."
In fact, the article concludes "many Silicon Valley programmers are now barely programming. Instead, what they're doing is deeply, deeply weird..."
Long-time tech journalist Clive Thompson interviewed over 70 software developers at Google, Amazon, Microsoft and start-ups for a new article on AI-assisted programming. It's title?
"Coding After Coders: The End of Computer Programming as We Know It."
Published in the prestigious New York Times Magazine, the article even cites long-time programming guru Kent Beck saying LLMs got him going again and he's now finishing more projects than ever, calling AI's unpredictability "addictive, in a slot-machine way."
In fact, the article concludes "many Silicon Valley programmers are now barely programming. Instead, what they're doing is deeply, deeply weird..."
Grindr's Chief Product Officer, AJ Balance, discusses the company's significant investment in AI, with 70% of its code now being checked via AI tools like Claude Code, OpenAI, and GitHub Copilot. This shift is changing the role of software engineers, moving them towards more code review and agent coordination. The company is also testing a premium "Edge" subscription tier at high price points, justifying the cost based on the value it delivers to users seeking enhanced connections. Balance also addressed concerns about ad density and subscription fatigue, outlining plans for ad format improvements and a focus on maintaining a positive free user experience.
This article advocates for wider adoption of Claude Code, an AI tool from Anthropic designed to write, edit, and fix code. Initially an internal tool for Anthropic developers, it's now publicly available as a command-line tool that operates within your terminal. It can understand natural language instructions to modify codebases, and even assists with non-programming tasks like file organization and research. While the terminal interface can be intimidating, the author suggests using it within an IDE or utilizing the Claude Desktop app's integrated Cowork interface, highlighting its potential for both developers and non-developers.
A new ETH Zurich study challenges the common practice of using `AGENTS.md` files with AI coding agents. LLM-generated context files decrease performance (3% lower success rate, +20% steps/costs).Human-written files offer small gains (4% success rate) but also increase costs. Researchers recommend omitting context files unless manually written with non-inferable details (tooling, build commands).They tested this using a new dataset, AGENTbench, with four agents.
