Agentic Build Day and Community Activity
Summary Report: “Agentic Build Day and Community Activity”
Event Objectives
- Provide a 3-hour technical deep-dive into AWS’s agentic services
- Walk through a real-world reference architecture: an AI-powered marketing campaign platform that orchestrates multiple specialized agents to automate audience segmentation, campaign creation, and promotions end to end
- Give attendees a working mental model of how AWS agentic services fit together
- Combine technical content with a hands-on community activity (making no-sew plush toys for children)
Speakers & Hosts
- Diem My / Dinh Nguyen – Community Activity hosts
- My Nguyen – Why Agentic AI & the MarTech use case
- Dai Truong / Thi Nguyen – Kiro Workshop Guidance
- AWS GenAI Builders Club team – technical sessions
Agenda Timeline
| Time | Session | Speaker |
|---|
| 13:00 – 14:00 | 🧸 Make No-Sew Plush Toys for Children (Community Activity) | Diem My / Dinh Nguyen |
| 14:00 – 14:15 | Why Agentic AI & the MarTech use case we’ll explore | My Nguyen |
| 14:15 – 15:00 | AWS Agentic Services in Action: AgentCore Runtime, Memory, MCP Gateway & Agent-to-Agent (A2A) Communication | — |
| 15:00 – 15:15 | ☕ Tea Break | — |
| 15:15 – 15:40 | The Strands Agents Framework & how it ties everything together | — |
| 15:40 – 16:10 | Full Workflow Walkthrough: tracing the code from user prompt to campaign creation | — |
| 16:10 – 16:30 | Security Patterns, Session Persistence & Infrastructure as Code | — |
| 16:30 – 16:45 | Key Takeaways & Source Code Tour | — |
| 16:45 – 17:00 | Kiro Workshop Guidance | Dai Truong / Thi Nguyen |
Key Highlights
- A warm, hands-on opener where attendees crafted no-sew plush toys to donate to children
- A reminder that a builders’ community is about people, not just technology
My Nguyen – Why Agentic AI & the MarTech use case
- Why agentic AI is different from traditional prompt-response models
- Introduction to the MarTech reference use case: an AI-powered marketing campaign platform
- How multiple specialized agents collaborate to automate audience segmentation, campaign creation, and promotions
AWS Agentic Services in Action
- AgentCore Runtime: the execution environment for running agents
- Memory: how agents retain and recall context across interactions
- MCP Gateway: connecting agents to tools and data through the Model Context Protocol
- Agent-to-Agent (A2A) Communication: how specialized agents coordinate with each other
The Strands Agents Framework
- Overview of the Strands Agents framework
- How it ties the agentic services together into a cohesive workflow
- The role of orchestration in multi-agent systems
Full Workflow Walkthrough
- Tracing the code end to end — from a user prompt to a created campaign
- Seeing how the reference architecture executes in practice
Security Patterns, Session Persistence & Infrastructure as Code
- Security patterns for agentic workloads (IAM, least privilege)
- Session persistence to maintain state across agent runs
- Infrastructure as Code (CDK) to make the architecture reproducible
Key Takeaways & Source Code Tour
- A recap of the core concepts and how the pieces connect
- A guided tour of the full source code for self-paced exploration
Dai Truong / Thi Nguyen – Kiro Workshop Guidance
- Guidance on using Kiro for the workshop and building agentic features
- How to apply the spec-driven workflow to real projects
Key Takeaways
- Agentic AI moves beyond single prompts toward systems of collaborating agents
- AWS provides building blocks — AgentCore Runtime, Memory, MCP Gateway, A2A — that fit together
- The Strands Agents framework is the glue that orchestrates multi-agent workflows
- Production agentic systems still need security, session persistence, and IaC to be reliable
- Having a complete reference architecture + source code is the fastest way to learn by adapting
Applying to Work
- Use the MarTech reference architecture as a template for any multi-step automation use case
- Experiment with AgentCore Memory to give internal assistants persistent context
- Connect existing tools through an MCP Gateway instead of hardcoding integrations
- Apply A2A communication to break a complex single-agent prompt into specialized agents
- Adopt CDK / Infrastructure as Code so agentic deployments are reproducible and reviewable
- Try Kiro for spec-driven development of agentic features
Prerequisites
- Familiarity with AWS (Lambda, IAM, CDK) and basic Python
- No prior experience with AI agents required
Event Experience
Attending Agentic Build Day and Community Activity on May 29, 2026 was a great mix of meaningful community work and a focused technical deep-dive. Key moments included:
- The event opened with a no-sew plush toy activity for children, hosted by Diem My and Dinh Nguyen — a heartwarming way to connect with other builders before diving into code.
Learning the agentic stack end to end
- My Nguyen framed the day with a clear MarTech use case, making the abstract idea of “agentic AI” concrete.
- The deep-dive into AgentCore Runtime, Memory, MCP Gateway, and A2A finally connected services I had only read about separately.
- Seeing the Strands Agents framework tie everything together clarified how orchestration actually works in practice.
Following real code
- The full workflow walkthrough — from user prompt to campaign creation — was the most valuable part, turning theory into a traceable execution path.
- The session on security, session persistence, and IaC was a good reminder that demos are easy but production needs guardrails.
Hands-on with Kiro
- Dai Truong and Thi Nguyen wrapped up with Kiro Workshop Guidance, showing how to apply a spec-driven workflow to build agentic features.
What I left with
- A working mental model of how AWS agentic services fit together
- A reference architecture I can adapt for my own use cases
- Access to the full source code to explore at my own pace
Some event photos




Overall, Agentic Build Day balanced heart and engineering — giving back to the community in the first hour, then handing us a complete, adaptable blueprint for building real agentic systems on AWS.