From Idea to Production: How I Built an AI Security Agent with AWS Bedrock AgentCore That Automatica

AI agents are the next big step after chatbots — but the path from a local prototype to a scalable cloud solution is full of pitfalls. In this talk, I’ll walk through my project ai-secure.dev, where I built a fully automated security compliance agent using AWS Bedrock AgentCore that audits websites against frameworks such as ISO 27001, NIST, and SOC 2. AgentCore is essentially “Fargate for AI agents”: you provide the container, and AWS takes care of scaling, networking, and infrastructure. Particularly exciting is the AgentCore Browser — a managed Chromium environment that enables web automation without maintaining your own Playwright infrastructure.

I’ll share practical learnings from development:

Why you shouldn’t build an agent from scratch — and how to validate use cases first using existing tools

Model routing for cost optimization — Haiku for simple tasks, Sonnet for complex audits, up to 90% cost savings through message caching

Local-to-cloud workflow — the same Docker container runs locally and in AgentCore

Production gotchas — from browser error handling to CloudWatch logging

This talk is aimed at developers who want to take AI agents beyond the prototype stage and into production — with real code, concrete architectural decisions, and honest lessons learned from operating it in the real world.