Repomix

Repomix: Tool to convert codebases into AI-friendly formats. Features include AI-optimized formatting, Git awareness, security checks, token counting, and a customizable CLI. Quick start with npx repomix, allows packing entire repositories, specific directories, or files. Supports Docker and offers various output formats (XML, Markdown, Plain text). Create a repomix.config.json for persistent settings. Comprehensive documentation available on GitHub.

https://repomix.com/

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Aider is an AI pair programming tool for terminal, supporting code editing in local git repositories, compatible with various LLMs. It simplifies project setup, allows requests for code changes, automatically commits edits, and integrates with popular IDEs, enhancing productivity across multiple programming languages.

https://aider.chat/

The Xonsh Shell — Python-powered Shell.

Xonsh is a modern, cross-platform shell that combines Python 3.6+ with shell commands, allowing seamless integration of both. It offers features like shell command combining, extensions (xontribs), customizable prompts, and extensive installation methods (PyPi, Conda, AppImage, Docker). It’s suitable for users of all skill levels and supports major operating systems like Linux, OSX, and Windows.

https://xon.sh/

Rork

Rork enables fast development of cross-platform mobile apps using AI and React Native, allowing users to create various applications like games, trackers, and dashboards.

https://rork.app/

Claude 3.7 Sonnet and Claude Code Anthropic

Claude 3.7 Sonnet, Anthropic's latest AI model, introduces integrated reasoning capabilities for improved coding and web development. It features instant or extended thinking modes, allowing user control over response time. Claude Code, a new tool for coding tasks, enhances collaboration and efficiency. Available across all pricing tiers, it retains previous models' pricing structure. Testing shows it excels in real-world coding tasks and reduces development time. The model prioritizes responsible use, with improved safety measures and user feedback integration to refine capabilities.

https://www.anthropic.com/news/claude-3-7-sonnet

Atuin

Atuin v18: a magical shell tool for syncing, searching, and backing up shell history. Features include end-to-end encryption, data import, and extra context storage. Open source, supports multiple shells, fast and reliable, easy setup, and optional cloud sync. 20K GitHub stars, growing community.

https://atuin.sh/

AI Coding: New Research Shows Even the Best Models Struggle With Real-World Software Engineering

AI coding research reveals top models struggle with real-world software tasks, as highlighted by OpenAI’s SWE-Lancer benchmark. The study shows even leading AI, Claude 3.5 Sonnet, only solves 26.2% of coding tasks and 44.9% of management tasks, translating to about $400,000 in potential earnings from $1 million, indicating they lag behind human capabilities in practical scenarios.

https://devops.com/ai-coding-new-research-shows-even-the-best-models-struggle-with-real-world-software-engineering/

How Core Git Developers Configure Git

Core Git developers use various git config settings to enhance their workflows. The article outlines crucial configuration options that should likely be defaults, categorizing them into three groups:
1. Clearly Makes Git Better – settings like branch.sort and diff.algorithm improve usability and clarity.
2. Why the Hell Not? – harmless options that may enhance the experience, like help.autocorrect and commit.verbose.
3. A Matter of Taste – preferences, such as managing merge conflicts with merge.conflictstyle.

Key recommendations include setting a default branch name, improving diff outputs, and auto-configuring remote tracking for pushes. The author emphasizes the practicality of these settings, backed by insights from Git core developers.

https://blog.gitbutler.com/how-git-core-devs-configure-git/

Why Clojure?

Clojure, a niche programming language, is valued for enhancing developer productivity, long-term maintainability, and fostering a culture of idea exploration. Its unique interactive development process allows for rapid testing and feedback, while a strong commitment to stability reduces maintenance costs. Clojure embraces immutable data and pure functions, aiding concurrency handling and simplifying testing. Despite its smaller developer pool, applicants tend to be high-quality thinkers. Clojure's interoperability with Java expands its usefulness, making it suitable for dynamic systems. Engaging with Clojure's community enhances problem-solving capabilities and promotes better software design practices.

https://gaiwan.co/blog/why-clojure/

aposd-vs-clean-code/README.md at Main · Johnousterhout/aposd-vs-clean-code

Discussion between Robert “Uncle Bob” Martin and John Ousterhout on software design principles in “aposd-vs-clean-code.” Key disagreements focus on method length, comments, and test-driven development. John emphasizes reducing complexity for easier understanding, while Bob champions small functions. They debate the risks of over-decomposition, balancing function size with clarity. They analyze the PrimeGenerator class for its design flaws, particularly method entanglement. Both find the other's approach lacking but agree on the challenge of maintaining code clarity amidst complexity. Ultimately, they encourage a careful balance between decomposition and comprehension in software design.

https://github.com/johnousterhout/aposd-vs-clean-code/blob/main/README.md

Why Are QR Codes With Capital Letters Smaller Than QR Codes With Lower-case Letters?

QR codes with capital letters are smaller than those with lowercase letters because uppercase codes use Alphanumeric mode, which is more efficient, requiring fewer bits per character (11 bits for two characters) compared to Byte mode used by lowercase (8 bits per character). For the same URL, this results in less data, hence a smaller QR code.

https://shkspr.mobi/blog/2025/02/why-are-qr-codes-with-capital-letters-smaller-than-qr-codes-with-lower-case-letters/

Get Coding Help From Gemini Code Assist — Now for Free

Gemini Code Assist offers free AI-powered coding help, enabling developers to access up to 180,000 code completions monthly without restrictive limits. It supports all programming languages and enhances coding efficiency by providing insights for code generation, debugging, and reviews directly within IDEs like Visual Studio Code and JetBrains. The GitHub extension facilitates automated code reviews, suggesting improvements and adhering to custom styles. Sign up requires only a Gmail account, with no credit card needed.

https://blog.google/technology/developers/gemini-code-assist-free/

Bookmarklets (and Custom URL Schemes) Are Criminally Underrated

Bookmarklets allow users to add custom JavaScript actions to their browsers, enabling personalized functionality like sending page URLs to external applications. They can interact dynamically with the current DOM and even launch local apps via custom URL schemes. While bookmarklets are powerful and versatile, they remain underutilized. Although setting them up can be cumbersome, the potential for seamless data flow between web browsers and local applications is significant. However, caution is advised against using untrusted sources for bookmarklets due to security risks.

https://silly.business/blog/bookmarklets-and-custom-url-schemes-are-criminally-underrated/

AArch64/ARM64 Assembly Tutorial

Vega's ARMv8 AArch64 Assembly Tutorial: Aimed at beginners, this comprehensive guide teaches ARMv8 AArch64 Assembly language, assuming no prior experience with older ARM versions. Key chapters cover installation, basic instructions, memory navigation, and advanced topics. Requires Linux and basic terminal knowledge. Discord contact for errors.

https://mariokartwii.com/armv8/

Can AI Coding Systems Earn $1 Million As Freelancers?

OpenAI researchers tested AI coding systems against real freelance software engineering tasks that humans earned $1 million to solve. They created the SWE-Lancer benchmark, sourcing 1,488 tasks from Expensify and Upwork. AI models like Claude 3.5 Sonnet and GPT-4o were evaluated on their performance. Results showed AI could earn over $400,000 but struggled with complex coding tasks, highlighting limitations in understanding and refining solutions. While AI can't replace human engineers yet, it may automate routine coding, allowing developers to focus on higher-level problems.

https://www.discovermagazine.com/technology/can-ai-coding-systems-earn-usd1-million-as-freelancers

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