🧭 Goal-Oriented AI: Building Agents That Plan AheadSo far in our journey, we’ve built agents that:Sep 23Sep 23
⚙️ Orchestrating AI Teams: Building a Multi-Agent Workflow EngineIn the last post, we explored how multi-agent systems let AI agents talk to each other. But just like in real life, having multiple people…Sep 22Sep 22
🤝 Multi-Agent Systems: How AI Agents Can Talk to Each OtherSo far, we’ve built single AI agents — assistants that can:Sep 21Sep 21
🚀 AI-Powered Features Every Modern Web App Should Include in 2025AI is no longer a “nice-to-have” — it’s now a must-have for modern web applications. Whether you’re building with MERN, MEAN, or any other…Sep 20Sep 20
🤖 Integrating AI into Your MERN App: Best Practices & PitfallsThe MERN stack (MongoDB, Express.js, React, Node.js) is a favorite for building full-stack web apps. But when you try to add AI features…Sep 19Sep 19
⚙️ How to Build an AI Workflow Engine for Your ProjectsSo far, we’ve built agents that reply, remember, and learn. But real-world AI apps (like Zapier, LangChain, or OpenAI workflows) are not…Sep 18A response icon1Sep 18A response icon1
🚀 Deploying Your AI Bot with Express.js and MongoDBIn the last blog, we built a goal-based agent in Python. That was great for learning, but if we want people to actually useour AI agent, we…Sep 17Sep 17
🎯 From Rule-Based to Goal-Based: Next-Level Agentic AI in PythonSo far, we’ve built rule-based AI agents — they follow fixed instructions like “if user says this, reply with that.”Sep 16Sep 16
🧠 Agent Memory & Feedback Loop: Making Your AI Smarter Over TimeHow to Build an Evolving AI Agent That Learns from YouAug 4Aug 4
💬 Make a Chat-Based AI Agent with State and Feedback in ReactBuild a Smart Frontend Agent That Learns from User FeedbackAug 4Aug 4
