klotz: coding*

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  1. Amazon has released Kiro, an AI-powered IDE designed for "vibe coding" that focuses on bringing prototypes into production with features like specs and hooks. It's powered by Claude 4 Sonnet and aims to apply software engineering best practices to the vibe-coding workflow.
  2. AI coding tools are increasingly interacting directly with the system shell (terminal) rather than traditional code editors, driven by the rise of agentic AI and tools like Claude Code, Gemini CLI, and CLI Codex. This shift, highlighted by benchmarks like Terminal-Bench, is occurring as some code-based tools face challenges and offers a versatile interface for developers.
  3. This article explores how AI agents are reshaping software development and the impact they have on a developer’s workflow. It introduces a practical approach to staying in control while working with these tools by adopting key best practices from the discipline of software architecture, including defining an implementation plan, splitting tasks, and so on.
  4. The article details the author's use of Claude Code to add a feature to a GitHub repository: an automatically updated README index. It's accompanied by a 7-minute video demonstrating the process.
  5. GitHub Copilot now has an Agents page to help developers kick off tasks and track progress. Users can assign tasks to Copilot (tech debt, bug fixes, new features) and Copilot will create a draft pull request for review. The feature is available to Copilot Pro/Pro+, Business, and Enterprise users with the coding agent enabled.
  6. This article discusses the impact of Large Language Models (LLMs) on the field of software engineering, arguing that while LLMs can increase efficiency, it's crucial to maintain a pipeline of junior engineers who learn through practical experience and problem-solving, rather than solely relying on AI-generated code.
  7. An overview of the top AI-powered coding tools available in 2025, including Cursor, Claude Code, Windsurf, VSCode, and others, highlighting their features and popularity among developers.

    | **Tool** | **Developer** | **Key Features** | **Notes** |
    |-------------------|----------------------------|---------------------------------------------------------------------------------|---------------------------------------------------------------------------|
    | **Cursor** | Anysphere | AI-powered autocomplete, code rewriting, agent mode, integrates with Web resources | Most popular AI-focused IDE, fork of VSCode |
    | **Claude Code** | Anthropic | Works in MacOS/Linux terminal, command-line interface, high control over workflow | Preferred by developers who like command-line tools |
    | **Windsurf** | Codeium (acquired by OpenAI)| AI autocorrect, agentic AI, Cascade interface, works in other IDEs (e.g., Jetbrains) | Rebranded from Codeium, acquired by OpenAI for $3 billion |
    | **VSCode** | Microsoft | Extensions support, GitHub Copilot (agent mode in preview), slow AI integration | Popular IDE, but slower to adopt AI features compared to startups |
    | **Vibe Coding Tools** | Various (e.g., Lovable, Replit, Bolt, Firebase) | Chat interface, no software installation, browser-based, minimal coding required | Designed for "vibe coding," where users describe what they want to build |
    | **Other Tools** | OpenAI, Mistral, Apple, etc. | Codex (OpenAI), Mistral Code, Apple’s AI tools, Zed, Devin (AI software engineer) | Rapidly evolving, many new tools emerging frequently |
  8. Atlassian announces Rovo Dev CLI, an agentic AI coding experience for developers in the command line, offering code understanding, development acceleration, Atlassian ecosystem integration, security features, and extensibility. It achieves state-of-the-art results on the SWE-bench benchmark.
  9. Guidance on choosing the best AI model for GitHub Copilot projects, considering speed, depth, cost, and task complexity. Models discussed include GPT-4.1, GPT-4o, Claude 3.5 Sonnet, o4-mini, o3, Gemini 2.0 Flash, and GPT-4.5.
    2025-04-25 Tags: , , , , by klotz
  10. This article explores a framework for evaluating AI models for use with GitHub Copilot, considering factors like recentness, speed, accuracy, and how to test them within your workflow. It highlights the benefits of using different models for chat versus code completion, and reasoning models for complex tasks.

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