Limitations of Agentic Frameworks: When to Use a Custom Framework

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Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
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Published on ● Video Link: https://www.youtube.com/watch?v=NoipTzs6_B8


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As LangChain and other agentic frameworks continue to evolve rapidly, with shifting philosophies and layers of abstraction, it’s becoming harder for developers to find stability and clarity. Watch as we explore the thought process behind rejecting complex frameworks in favor of simplicity, code readability, and production-readiness. This candid take highlights the real pain points many developers face when working with emerging LLM agent ecosystems, from chaotic documentation to framework instability.

If you’re working with LLMs, LangChain, AI agents, or building multi-agent systems, this is a must-watch. Learn what it takes to build your own agent architecture, and why sometimes starting from scratch gives you the clearest path forward.

#LangChain #AIagents #LangFlow #MultiAgentSystems #LLMDevelopment #OpenAI #GenerativeAI #AutoGen #AIengineering #DevTools #AIDev #TechTalk #GPT4 #AIbootcamp #StartupAI #AgenticWorkflow #LangGraph #LLMops



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