For me, queued messages are the biggest DevEx unlock for @cursor_ai.
Now I can enter a flow state where I'm three feature requests/bug fixes ahead of Cursor.
I rapidly verify functionality and put new tasks on the queue while it's working through my requests ❤️
Interest in, and adoption of, MCP is exploding.
Think: one spec → any tool, any workflow, securely. Big shift for AI infra.
Top Ruby Auth Gems:
• Devise: Full-featured - from resets to 2FA.
• OmniAuth: Integrations galore. Good for social login.
• Clearance / Authlogic: Lightweight
• Rodauth: Rack-first with advanced modules (2FA, lockouts).
• Sorcery: Minimalistic but unmaintained.
1️⃣ The era of software agents is here—and three new protocols are shaping how they work:
2️⃣
MCP, ACP, and A2A.
Think of them as ports, walkie‑talkies, and trade routes for AI. Dive in 👇🧵
It’s all run sequentially with a Crew:
1. Code generation by the Senior Engineer agent
2. QA checks by the QA Engineer
3. Final sign-off from the Chief QA Engineer
Core Concepts
Crews: Groups of specialized agents (e.g., a “Senior Engineer” generating code, QA agent reviewing).
Flows: Event-driven workflows, giving you fine-grained control over who does what, when.
AI Agents That Code Your Game—Meet CrewAI
What is it?
CrewAI is a Python framework for orchestrating multiple AI agents (like a mini dev team) to generate, review, and validate code. Perfect for building something fun—like a Pac-Man or Pong clone—in Python.
Dev Superpower: Instant model swaps.
Start with GPT-4, switch to Claude or another model—your prompt and code stay almost the same.