惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

J
Java Code Geeks
G
Google Developers Blog
人人都是产品经理
人人都是产品经理
U
Unit 42
爱范儿
爱范儿
Hugging Face - Blog
Hugging Face - Blog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
WordPress大学
WordPress大学
B
Blog RSS Feed
The Cloudflare Blog
D
Docker
A
About on SuperTechFans
IT之家
IT之家
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Y
Y Combinator Blog
月光博客
月光博客
云风的 BLOG
云风的 BLOG
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
MongoDB | Blog
MongoDB | Blog
Google DeepMind News
Google DeepMind News
The GitHub Blog
The GitHub Blog
博客园_首页
Stack Overflow Blog
Stack Overflow Blog

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
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! 🚀