AWS GenAI Builder Series — AWS AgentCore Services
Format: 2 hours (presentation → live demo)
Focus: Build and operate AI agents on AWS using Amazon Bedrock AgentCore. We’ll work directly from the official AgentCore Samples repo to take an agent from local run to a production-ready deployment pattern.
What you’ll learn
Where AgentCore fits in an AWS stack: Runtime, Gateway (tooling), Memory, Identity, and Observability
How to run an agent locally, then deploy it on AWS
How to register and call tools (Lambda/HTTP) through the Gateway
How to add state with Memory and secure access with Identity
Practical ops: tracing, debugging, guardrails, and cost awareness
Live demo (using the GitHub samples)
Runtime quickstart: run a minimal agent locally → deploy → invoke
Gateway tool call: expose a simple Lambda/HTTP tool and call it from the agent
Add Memory + Observability: persist context and trace steps end-to-end
(If time) wire up Identity for a third-party call
Who should attend
Engineers and architects building agentic applications on AWS (SWE, MLE, SRE, platform).
Prerequisites (bring your laptop)
AWS account with access to Bedrock and AgentCore
AWS CLI configured (aws configure)
Python 3.10+ and Docker/Finch for local dev
Access to at least one Bedrock model (e.g., Claude)
We’ll reference: awslabs/amazon-bedrock-agentcore-samples
Agenda (2 hours)
15 min — Context & goals
35 min — Theory walkthrough (architecture, patterns, gotchas)
50 min — Live demo (zero → working agent)
10 min — Q&A + pitfalls
10 min — Homework lab & repo pointers
Takeaways
Slides and a reproducible demo repo
A mini runbook for local → cloud deployment
A checklist to productionize your first AgentCore agent