Build AI Agents WITHOUT CLI (Full Control with FastAPI + AWS)

Description

🚀 Want to build AI agents with full control — without relying on SDKs or CLI tools? In this video, we walk through how to create and deploy a **custom AI agent on Amazon Bedrock AgentCore Runtime using FastAPI and Docker**. --- 💡 What you’ll learn: • How to build a custom agent without AgentCore CLI :contentReference[oaicite:0]{index=0} • Required AgentCore Runtime contract (/invocations and /ping endpoints) • Creating an agent using FastAPI • Handling requests and responses for AI interactions • Containerizing your agent (ARM64 Docker requirement) • Building and testing locally • Deploying to AWS using ECR • Creating an AgentCore Runtime manually • Invoking your agent using AWS SDK • Managing runtime sessions and lifecycle --- 🧠 Key Insight: Most tutorials hide complexity using CLI or SDKs. This approach: • Gives you full control over implementation • Works with any framework • Lets you customize every layer (API, infra, runtime) 👉 This is how real production systems are built. --- 📌 Core Requirements: • /invocations → Handles agent requests • /ping → Health check endpoint • Docker container (ARM64) • ECR deployment • AgentCore Runtime configuration --- ⚡ Why this matters: Using only CLI/SDK: → Limited flexibility ❌ Custom agent approach: → Full control + production-ready architecture ✅ --- 🏗️ Real-world use cases: • Custom enterprise AI agents • API-first AI platforms • Microservice-based AI systems • Secure and controlled AI deployments • Multi-agent backends --- 🔗 Topics covered: FastAPI AI agents, AgentCore Runtime, AWS Bedrock, Docker AI agents, GenAI backend, custom AI systems --- #AWS #AmazonBedrock #AgentCore #FastAPI #GenAI #LLM #AIEngineering #AgenticAI #CloudArchitecture