GGoldwater.dev

Hands-on

Labs

Build it to understand it. Each lab is a self-contained, runnable walkthrough — step-by-step instructions, real code, and a starter repo you can download. Standalone labs stand on their own; series are meant to be worked through in order.

Hands-on Labs

6 labs
Intermediate45–60 min

Agent-to-Agent Collaboration (A2A)

Wire up the Agent-to-Agent protocol so independent agents can discover each other and collaborate on a task — with a worked, offline Acme example.

AgentsA2AProtocolsStart
Intermediate45–60 min

Evaluating Agents (Evals as Code)

Treat agent quality like code: build a version-controlled evaluation harness that scores real cases and catches regressions before they ship.

EvalsQualityTestingStart
Intermediate45–60 min

Build an MCP Server

Build a working Model Context Protocol server from scratch and call it from a client — the standard way to give AI agents governed access to your tools and data.

MCPToolsIntegrationStart
Beginner–Intermediate45–60 min

Portable Knowledge for AI with the Open Knowledge Format

Author, validate, consume, and generate institutional knowledge in the Open Knowledge Format — portable AI context that's just markdown files with YAML frontmatter, managed in git.

KnowledgeMetadataStandardsStart
Intermediate45–60 min

Discovering and Trusting Agentic Resources with ARD

Stand up both halves of Agentic Resource Discovery offline: publish and cryptographically sign a catalog, run a registry and client, and watch trust verification reject an impersonator.

AgentsSecurityDiscoveryStart
Intermediate45–60 min

Building with Google's Interactions API

Build a stateful, agentic workflow on Google's Interactions API — multi-turn server-side state, function calling, tool combinations, and background tasks — in one small Python program.

GeminiAgentsAPIStart

ADK Series

5 parts

Gemini Enterprise Agent Platform

11 parts
Part 1Beginner–Intermediate45–60 min

Platform Tour & Your First Agent in Agent Studio

Get oriented in Google's Gemini Enterprise Agent Platform and build a working agent with no code — instructions, a sample tool, and a live test — in Agent Studio, then clone a ready-made agent from Agent Garden.

GeminiAgent PlatformAgent StudioStart
Part 2Intermediate45–60 min

Agent Engine: Deploy to the Managed Runtime

Take a code-defined ADK agent and deploy it to Agent Engine, the platform's managed runtime — then call it over the network with managed sessions and watch it in the console. No infrastructure to operate.

GeminiAgent EngineDeployStart
Part 3Intermediate45–60 min

Grounding with Vertex AI Search & RAG Engine

Ground the agent in your own documents so its answers are accurate and cite their sources — via a Vertex AI Search data store in the console and a RAG Engine corpus in code, then read the grounding metadata for citations.

GeminiRAGGroundingStart
Part 4Intermediate45–60 min

Tools & Connectors: APIs, Databases, and MCP

Give the agent hands: connect it to real systems through four tool types — a function tool, an OpenAPI toolset, a governed Integration Connectors data connector, and an external MCP server — all surfaced as ordinary, read-only tools.

GeminiToolsMCPStart
Part 5Intermediate45–60 min

Sessions & Memory Bank

Give the agent managed short-term memory (Sessions) and long-term memory (Memory Bank) so it remembers a customer within and across conversations — generating and recalling durable facts without running your own store.

GeminiMemorySessionsStart
Part 6Intermediate45–60 min

Example Store: Steer Behavior with Few-Shot Examples

Curate few-shot examples centrally in Example Store and retrieve the relevant ones at runtime to steer the agent's behavior — improving quality without retraining a model or bloating the prompt.

GeminiQualityFew-shotStart
Part 7Intermediate45–60 min

Gen AI Evaluation: Measure and Gate Quality

Evaluate the agent with the platform's managed Gen AI Evaluation service — define a dataset, score it with model-based and computation metrics, compare two versions head-to-head, and gate ship/no-ship on the numbers.

GeminiEvalsQualityStart
Part 8Intermediate45–60 min

Model Armor & Safety Filters

Put a managed safety perimeter in front of the agent: screen user prompts and model responses for prompt injection, jailbreaks, harmful content, malicious URLs, and sensitive data — centrally configured and enforced, not left to the agent's own instructions.

GeminiSafetySecurityStart
Part 9Intermediate45–60 min

Agent Identity & the Agent Registry

Govern who an agent is and what it may reach: a verifiable SPIFFE/X.509 identity, a namespaced URN in the Agent Registry, an egress policy via Agent Gateway, and a published catalog so agents can discover and trust each other across the org.

GeminiGovernanceIdentityStart
Part 10Intermediate45–60 min

Observability, Tracing & Cost

See what deployed agents actually do and what they cost: enable tracing and telemetry, read spans to debug a request, watch the built-in dashboard, alert on errors and latency, and bound spend with budgets and quotas.

GeminiObservabilityCostStart
Part 11Intermediate–Advanced45–60 min

Interoperability Capstone: A2A + ADK on the Platform

Tie the managed platform to the open ecosystem: a platform-hosted agent that consumes an MCP server, delegates to a peer over A2A, and is itself exposed over A2A — managed core, open edges, no lock-in.

GeminiA2AInteroperabilityStart

Microsoft Foundry

12 parts
Part 1Beginner–Intermediate45–60 min

Platform Tour & Your First Agent

Get oriented in Microsoft Foundry and build a working agent with no code — deploy a model from the catalog, give it instructions and a built-in tool, and test it in the playground.

FoundryAzureAgentsStart
Part 2Intermediate45–60 min

Foundry Agent Service & the SDK

Build and run the agent from code on the managed Foundry Agent Service — connect with the SDK, create an agent, run it over a thread, and meet the OpenAI-compatible Responses path. Python-primary, with the .NET equivalent noted.

FoundrySDKAgentsStart
Part 3Intermediate45–60 min

Grounding with Foundry IQ

Ground the agent in your own documents and data so its answers are accurate and cite sources — via File Search (a vector store on Azure AI Search), a connected search index, and Foundry IQ, the unified knowledge layer with agentic retrieval.

FoundryRAGGroundingStart
Part 4Intermediate45–60 min

Tools: Built-in, Custom, OpenAPI & MCP

Give the agent hands: built-in tools (code interpreter, web search), your own function tools, an entire REST API via OpenAPI, and the 1,400+ tools available through MCP — all surfaced as ordinary, read-only tools.

FoundryToolsMCPStart
Part 5Intermediate45–60 min

Threads & Memory

Give the agent durable context: managed threads for a conversation, managed memory across conversations, and bring-your-own thread storage in Azure Cosmos DB so conversation data stays in your own resources.

FoundryMemoryThreadsStart
Part 6Intermediate45–60 min

Evaluations

Measure the agent with Foundry's managed evaluators — define a dataset, run local and hosted evaluation with results linked to the agent trace, compare versions, and gate ship/no-ship on the score.

FoundryEvalsQualityStart
Part 7Intermediate45–60 min

Content Safety & Prompt Shields

Put a managed safety perimeter around the agent: content filters on the deployment, Prompt Shields for prompt-injection and XPIA, plus PII, groundedness, and protected-material checks — centrally configured, not left to the agent's instructions.

FoundrySafetySecurityStart
Part 8Intermediate45–60 min

Identity, Access & Governance

Govern who the agent is and what it may reach: a managed Microsoft Entra Agent ID, least-privilege RBAC role assignments, and network isolation — identity and access management, for agents.

FoundryGovernanceIdentityStart
Part 9Intermediate45–60 min

Connected Agents & the Microsoft Agent Framework

Compose a multi-agent system: a primary concierge that delegates to focused specialist agents via connected agents — no external orchestrator — built with the Microsoft Agent Framework.

FoundryMulti-AgentAgent FrameworkStart
Part 10Intermediate45–60 min

Observability & Cost

See what deployed agents do and what they cost: OpenTelemetry tracing to Application Insights (model calls, tool calls, sub-agent hops), Azure Monitor dashboards and alerts, and budgets and quotas to bound spend.

FoundryObservabilityCostStart
Part 11Intermediate–Advanced45–60 min

Fine-tuning & Model Customization

Customize the model itself — fine-tuning, distillation, and GPT-5 RFT — and, just as important, learn when not to. Prepare data, run a job, and prove the customized model beats the base before shipping.

FoundryFine-tuningModelsStart
Part 12Intermediate–Advanced45–60 min

Interoperability Capstone: MCP, A2A & Microsoft 365

Tie a Foundry agent to the open ecosystem and the surfaces your users live in: consume MCP tools, interoperate with peers over A2A, and publish the agent into Microsoft 365 — managed core, open edges.

FoundryA2AInteroperabilityStart

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