Reading up on ide
14 deep · digging since nov 19, 25
- Tree-sitter vs. Language Servers
The Hacker News discussion explores the trade-offs between Tree-sitter's incremental parsing for syntax highlighting and Language Server Protocol's semantic features, concluding that combining both yields the best editor experience.
- Cursor agent best practices
Cursor's official guide details best practices for coding agents, emphasizing planning, context management, rules, and iterative review to maximize productivity.
- Diffs, from Pierre
@pierre/diffs is an open-source diff and code rendering library built on Shiki, offering customizable layouts, theming, and annotation support.
- Claude Code Sees Like A Software Architect
Claude Code's native LSP support lets it understand code structurally like an IDE, eating the business model of startups that built semantic code understanding as middleware.
- Just a moment...
Microsoft is deprecating its free, local IntelliCode AI code completion extensions in VS Code and pushing developers toward subscription-based GitHub Copilot with usage caps.
- Compound Engineering: How Every Codes With Agents
The piece outlines a four-step 'compound engineering' loop—plan, work, review, compound—to make each coding unit simplify future work, enabling small teams to run multiple products via AI agents.
- Introducing Debug Mode: Agents with runtime logs
Cursor introduces Debug Mode, an agent loop that generates hypotheses, instruments code with runtime logs, and requests human verification to reliably fix bugs that stump standard AI models.
- First make it fast, then make it smart
Faster AI coding models, even if less intelligent, are more productive for quick mechanical code edits than slower, smarter models, especially for users with short attention spans.
- Building an AI-Native Engineering Team
Coding agents like Codex can now sustain multi-hour reasoning tasks, transforming the entire software development lifecycle by delegating mechanical work across planning, design, build, test, review, and deployment.
- How to write a great agents.md: Lessons from over 2,500 repositories - The GitHub Blog
Analyzing 2,500+ agents.md files reveals that effective agent definitions require specific personas, executable commands, code examples, and clear boundaries.
- Google Antigravity
Google announced Antigravity, an agentic development platform that extends its AI IDE with multi-agent workspace management, CLI, and SDK.
- Google Antigravity
Google released Antigravity, an agentic IDE and VS Code fork with three surfaces—agent dashboard, editor, and browser extension—for building apps with Gemini models.
Takes
Stop using bulky GUIs. If you build software, live in the terminal.neovim + AI auto-assist + grok-code-fast. Lock in. 🔒The Setup:Shell: zsh + oh-my-zsh + starship Multiplexer: tmuxMonitor: btop + proc + duf + dustNav: yazi + zoxide + fzf + eza mag Search: ripgrep + fd… pic.twitter.com/0OKUWGhRjD
@tetsuoai
Excited to launch Google Antigravity, our next generation agentic IDE, now powered by Gemini 3! pic.twitter.com/Ya2sMHnnLw
@_mohansolo