Workshop Studio

Amazon Bedrock AgentCore is an AWS service for deploying and operating AI agents in production. It provides a framework- and model-agnostic runtime for agents built with systems such as Strands Agents, CrewAI, LangGraph, LlamaIndex, Google ADK, or OpenAI Agents, with support for Python and TypeScript applications. Its capabilities include managed agent runtime hosting, sessions, memory, identity and access management, a gateway for turning APIs, Lambda functions, and services into MCP-compatible tools, built-in tools such as code execution and web search, and OpenTelemetry-based observability for tracing, debugging, and monitoring. The linked AWS Labs repository provides sample applications, tutorials, deployment templates, integrations, and blueprints covering these capabilities. The AgentCore CLI scaffolds projects, supports local development with hot reload and local invocation, and deploys agents to AWS with commands such as `agentcore deploy` and `agentcore invoke`. The samples repository is licensed under Apache 2.0.

The Mastering AI Observability Workshop repository is a hands-on workshop resource for building a trace-backed support-agent improvement workflow with Braintrust. It provides a local Python workshop app, setup instructions, a support agent using tool calls, seeded evaluation cases, production-like trace generation, Braintrust datasets and evaluations, hosted scorers, Topics facets, sample-trace imports, and optional draft evaluation cases derived from traces. The workflow connects tracing and online analysis to offline evaluations, custom scoring, failure investigation, regression cases, and reviewable code changes. The repository includes a public WORKSHOP.md guide, environment setup through uv and Make commands, local database seeding, a web interface, and configuration for Braintrust Gateway model calls.

Agent Context Workshop is a hands-on workshop resource for building and evaluating context layers for coding agents. It uses selected crates from the Qdrant Rust codebase to extract syntax with tree-sitter, resolve symbols and relationships with rustdoc JSON, store the resulting code knowledge graph in Neo4j, and expose graph tools such as search, blast-radius analysis, and implementor lookup to an agent. The workshop compares graph-based agents with grep-style agents using gold-verified questions, deterministic scoring, cached evaluation results, tool-adoption measurements, and trace inspection. Additional notebooks cover static Python resolution with Griffe and an optional Fenic-and-LLM semantic layer. The GitHub repository maintains the workshop through ordered Jupyter notebooks, typed extraction and graph code, evaluation harnesses, tests, committed Qdrant seed data, and a committed evaluation cache; it is licensed under Apache-2.0.

Multi-Agent Workbench is a local-first browser control room for orchestrating coding agents such as Claude Code, Codex CLI, and generic PTY-based command-line agents. Agents work in task rooms under editable YAML role cards that define permissions, speaking style, and decision boundaries; a rule-driven orchestrator pauses execution and risky commands for human approval, while persistent sessions expose terminal activity and status. The system uses a local event-driven architecture with a React interface, Fastify backend, REST API, server-sent events, agent adapters, an approval service, and a SQLite event store. Every action passes through the API and is recorded in an append-only event log, whose events are projected into timelines, decisions, terminal views, artifacts, and diff views. It also provides task templates, Markdown reports and decision logs, real-time room updates, and configurable risk resolutions. Code-writing agents are intended to use isolated Git worktrees, with diff and patch review before changes reach the main workspace; the repository marks this worktree and merge flow as in progress.

Agent Plugins for AWS is an AWS Labs collection of plugins for AI coding agents, helping them architect, deploy, and operate on AWS. Supported agents include Claude Code, Codex, and Cursor. Each plugin can package agent skills—structured workflows and best-practice playbooks—alongside MCP servers that provide access to live documentation, pricing data, and other APIs; hooks that validate changes or trigger workflows; and references containing documentation and configuration defaults. The repository describes the plugins as reusable, versioned capabilities intended to reduce prompt context and standardize agent behavior. It warns that generative AI can make mistakes and recommends reviewing generated code, costs, security, and credentials. The repository also identifies Agent Toolkit for AWS as the successor for production use, while stating that this project continues to work and accept contributions.