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🧠💻 Say Hello to Google's Agent Development Kit (ADK)! 🚀 Unveiled at Google Cloud Next '25, the Agent Development Kit (ADK) is an open-source framework designed to simplify the creation of intelligent, modular, and production-ready AI agents. 🔹

The AI world just hit peak “premium”. Elon’s SuperGrok Heavy is now $300/month and that’s $3,000 a year for an AI chatbot. This officially makes it the most expensive subscription in the game. Here’s the current leaderboard of luxury LLMs: • Open

Cursor IDE vs TRAE IDE > Cursor - Free : Only on Auto Mode & GPT 4.1 Paid : Usage based pricing | $20/month > TRAE - Free : All models with Waiting on Que Requests. Paid : $3/month only for first month with 600 Requests on Premium Models like

Grok 4 is still #1 at LiveCodeBench Most developers use Grok to fix bugs left behind by other AI generators because nothing else understands code as deeply as Grok

🔮 No-Code AI Revolution: Multi-Agent Systems for Everyone! Multimodal LLM-based multi-agent systems are now accessible through no-code platforms. Game-changer alert! 🚀 Why it matters: - Non-technical teams can implement complex AI - Handle text,

🤖 Just discovered AI Fiesta - game changer for AI workflows! What is it? A unified platform that gives you access to 6 premium AI models (ChatGPT-5, Gemini 2.5 Pro, Claude Sonnet 4, Perplexity Sonar Pro, DeepSeek & Grok 4) under one roof. Key benefi

The Future of Intelligence is Unfolding Forget traditional AI—Universal Intelligent System is built on: 🔹 Self-Creating Codebase – AI that writes and restructures itself 🔹 Multi-Dimensional Learning Field – Learns across realities, beyond hu

🚀Exciting News! We’re thrilled to announce that we will be launching our AI application next month, August 2025! We truly believe this app has the potential to assist millions of users in their daily lives, making tasks easier, faster, and smarter

If you're building AI agents, you should get familiar with these 3 common agent/workflow patterns. Let's break it down. 🔹 Reflection You give the agent an input. The agent then "reflects" on its output, and based on feedback, improves and refines.