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go agentic workshop

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Multi-Agent Platforms & Frameworks
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Basic Information

This repository is a hands-on workshop created for GopherCon 2025 that demonstrates how to build production-ready AI agents using the Go programming language and AWS Bedrock. It provides a guided, practical set of code, examples, and orchestration patterns aimed at teaching developers how to structure agent applications for deployment. The project includes setup and configuration scripts, Docker compose support, Makefile targets to verify and run the environment, and a SETUP.org file referenced for detailed exercises and architecture documentation. The README lists prerequisites such as Go 1.23+, Docker, AWS Bedrock access, and AWS CLI configuration, and explains the overall project purpose of combining Bedrock client integration with common agent orchestration patterns in a reproducible workshop format.

Links

App URL
https://github.com/aygp-dr/go-agentic-workshop
Github Repository
https://github.com/aygp-dr/go-agentic-workshop/blob/main/README.md

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App Details

Features
The repo exposes a clear project structure with a main agent command under cmd/agent and reusable packages under pkg including a bedrock client, orchestrator logic, and common agent patterns. It contains examples and benchmark folders for sample implementations and performance testing, plus a setup directory for installation and configuration scripts. Development convenience is provided via Makefile targets such as setup, docker-up, run, test, and docker-down. Documentation includes platform support information for multiple architectures and operating systems, a contributing section, a commit convention using Conventional Commits, and the project is licensed under MIT.
Use Cases
This workshop repository helps developers learn practical techniques for building and running Go-based AI agents by providing runnable code, integration examples, and environment automation. The included Bedrock client and orchestrator packages illustrate how to connect to managed model services and organize agent workflows. Setup scripts and Docker compose allow reproducible environments and quick verification, while examples and benchmarks let users explore implementations and measure performance. Multi-platform support and contribution guidance make it easier to test on different targets and collaborate. Overall it is a teaching and bootstrap resource to accelerate building production-oriented agent systems using Go and modern orchestration patterns.

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