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Stop reading AI papers. I built a free interactive playgr...
Rohan Ghosh · 2026-04-24 · via DEV Community
Cover image for Stop reading AI papers. I built a free interactive playground to learn Agentic AI by building it. 🛠️

Rohan Ghosh

Hey DEV community! 👋

Over the last few months, I noticed a massive gap in how developers are learning about Agentic AI. We are currently drowning in theoretical blog posts, hype, and dense whitepapers on RAG, tool calling, and swarms.

But when it comes to actually building them? There’s almost nowhere to just sit down, run an agent, break things, and see how the prompt and tools interact under the hood—at least, not without spending hours configuring your local python environment and dealing with dependency hell first.

So, I built a solution: AgentSwarms (https://agentswarms.fyi).

It’s a free, interactive curriculum for Agentic AI. Instead of just reading about agents, you run live agents right alongside the lessons.

🧠 What you'll get hands-on with:

  • Prompt Engineering & System Messages: See exactly how tweaking temperature and persona instructions directly changes the execution behavior.
  • RAG (Retrieval-Augmented Generation) vs. Fine-tuning: Learn how to ground an agent in actual documents to stop hallucinations.
  • Tool / Function Calling: Get comfortable writing OpenAI schemas and connecting to MCP (Model Context Protocol) servers.
  • Guardrails & HITL (Human-in-the-Loop): Build approval workflows and safety constraints so your agents don't go rogue in production.
  • Multi-Agent Swarms: Compare orchestrator/router patterns versus peer-to-peer handoffs.

⚙️ The Setup (Zero friction)
I wanted to completely eliminate the barrier to entry for learners:

  • Learn Mode: You don't need to npm install, pip install, or even provide API keys to start. It's completely free, sandboxed, and runs right in your browser.
  • Build Mode: Once you're ready to experiment with your own stack, you can plug in your own API keys (OpenAI, Anthropic, Gemini, local models, etc.) and start pushing the limits.

💬 I need your feedback!
I built this for developers who learn best by doing. I’d love for the DEV community to take it for a spin and tear it apart.

  1. What agent patterns or architectures am I missing from the curriculum?
  2. Is the observability dashboard actually useful for debugging your traces?

Try it out and drop your thoughts in the comments. Happy building! 🚀