If this is useful, a ❤️ helps others find it. Everything I keep looking up when building Tauri v2 apps — in one place. // Define #[tauri::command] fn greet(name: String) -> String { format!("Hello, {}!", name) } // With error handling #[tauri::command] fn read_file(path: String) -> Result { std::fs::read_to_string(path).map_err(|e| e.to_string()) } // Async #[tauri::command] async fn fet
When you build a PowerShell project from multiple files, the natural structure is clear: enums first, then classes, then functions. Each group has its own place, and as long as dependencies only flow in one direction, that structure works perfectly. But sometimes a function depends on a class, and that class calls the function. There is no longer a clean boundary between the two groups — they need
Repo: https://github.com/richer-richard/socratic-council Stack: Tauri 2 (Rust + React/TypeScript), pnpm monorepo, Apache-2.0 Latest release: v2.0.0 If you ask one frontier model a hard question, you get a confident answer. If you ask sixteen, you get an argument. Socratic Council is a desktop app that runs a structured seminar between sixteen LLM agents drawn from eight providers — OpenAI, Anthr
The drift problem nobody told you about If you have used Claude Code, Cursor, Aider, or any other AI coding agent across more than two projects, you have felt this: You start project A. You copy the .agents/ folder (or CLAUDE.md, or .cursorrules) from your last project. You tweak two things. Done. You start project B six weeks later. You copy from project A. You tweak three things this time. Now
Cross-posted from the Stigmem blog. Today we're releasing stigmem v1.0: A stable, open-source specification and reference implementation for a federated knowledge fabric for AI agents. Stigmem = Stigmergy + Memory. Stigmergy (Greek stigma — mark; ergon — work) is the coordination mechanism you see in ant colonies and termite mounds: agents don't communicate directly with each other. Instead, they
More rules should mean better output. That's the intuition. I spent weeks building a comprehensive CLAUDE.md — 200 lines covering naming conventions, security rules, error handling, architectural patterns, import ordering, type safety requirements, and more. I was proud of it. I'd thought through every scenario. Then I scored the output. 79.0 / 100. My carefully crafted documentation was actively
All tests run on an 8-year-old MacBook Air. The default: Tauri commands When commands aren't enough: events Targeting specific windows The channel API for streaming data async fn stream_data(on_event: Channel) -> Result<(), AppError> { What I don't use The pattern I follow User action → invoke command → return result Three patterns. That's the whole IPC layer. If this was useful, a ❤️ helps more t
All tests run on an 8-year-old MacBook Air. Most AI integration tutorials assume you're paying for API access. HiyokoLogcat is built entirely on Gemini's free tier — and designed so users bring their own free API key. Here's what's possible, what the limits are, and how to design around them. Gemini 2.5 Flash Preview: 15 requests per minute (RPM) 1,000,000 tokens per day 250 requests per day For a