Post by @high_tech02

Everyone talks about AI Agents but do you know what powers them under the hood? The visible part? The agent chatting with you. The real complexity? Buried deep below the surface. What looks like “an intelligent agent” on the surface is actually a deep, multi-layered tech stack carefully stitched together for real-world performance. Here’s the Full Stack of an AI Agent, iceberg-style: - Frontend: React, Next.js, Streamlit, Gradio, Retool - Memory: Vector DBs like Pinecone, Weaviate, Redis, Chroma - Auth: Okta, Firebase, Clerk who gets access matters - Tools: Google, Serper, Exa, Puppeteer for real-world interaction - Observability: LangSmith, Helicone, Arize, W&B track everything - Agent Orchestration: LangGraph, CrewAI, AutoGen - Model Routing: OpenRouter, Martian, PromptLayer - Foundation Models: GPT-4o, Claude, Gemini, Mistral, LLaMa 3 - Database: PostgreSQL, MongoDB, Neo4j - Infrastructure: Docker, Kubernetes, Terraform - Compute: AWS, GCP, Azure, Modal If you’re building serious AI apps in 2025, this stack isn’t optional it’s essential. What layers are you using in your agent stack? Anything you'd swap out or add? Let’s compare notes. #AI #AIStack #AgenticAI