Feb 16
Loading video player...
Access to FREE resources: https://www.skool.com/ai-learn-3541/about In this video, I break down the AI agent frameworks that actually ship in 2026, framework by framework — based on real production criteria. 🔥 Key Takeaways: • Why LangGraph became the production standard for complex multi-agent systems • How CrewAI went from experimental to S-tier through adoption • Why N8N crossed 100K GitHub stars — and where it actually fits • When visual agent builders like Flowise make sense in production • Why state management is still the biggest differentiator • Which frameworks to avoid unless you have a very specific reason ⏱️ Timestamps: 0:00 – Intro 0:24 – Ranking Criteria 0:47 – Flowise 1:55 – PydanticAI 3:41 – OpenAI Agents 5:44 – Google ADK 6:52 – N8N 9:32 – CrewAI 12:36 – LanGraph 13:33 – Final Recommendations 📚 Resources: • LangGraph: https://github.com/langchain-ai/langgraph • CrewAI: https://github.com/crewAIInc/crewAI • N8N: https://github.com/n8n-io/n8n • Flowise: https://github.com/FlowiseAI/Flowise • PydanticAI: https://github.com/pydantic/pydantic-ai • OpenAI Agents SDK: https://github.com/openai/openai-agents-python If you’re building AI agents that need to survive production — not just look good in demos — this breakdown will save you months of wrong decisions. 💡 Building real AI agents? Subscribe for no-fluff breakdowns of what actually works. #aiagents #langgraph #crewai #n8n #flowise #ai