Head of Engineering | Principal Architect | Leadership in IoT & GenAI | Transforming Ideas into Reality
🚀 Workflows vs Agents: How to Choose for Your LLM Solutions When building AI systems with large language models, one of the biggest decisions is: 👉 Should you use a workflow or an agent? Here’s a simple way to think about it (inspired by Anthropic’s excellent guide) 🔹 Workflows → Best for predictable, repetitive, structured tasks. Example: Auto-replying to customer emails with a standard message. ✅ Consistent, low-latency, cost-efficient. 🔹 Agents → Best for open-ended, dynamic, exploratory tasks. Example: Researching and summarizing the latest market trends. ✅ Adaptive, flexible, capable of multi-step reasoning. ⚠️ But higher latency and cost. 💡 Rule of thumb: If you know the exact path → Workflow. If the path is uncertain → Agent. Start simple. Often, a single LLM call + retrieval works better than overengineering an agent. Frameworks (LangGraph, Rivet, etc.) are helpful—but only after you understand the basics. ✨ Credit: Anthropic’s blog “Building Effective Agents” for the insights that inspired this post. #AI #LLM #Workflows #Agents #Anthropic #ArtificialIntelligence
