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Build, evaluate, and deploy advanced AI agents with a code-first Go toolkit.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "adk-go" yet — see the docs or source repo.
Using adk-go, design a Go agent that accepts a user question, calls a retrieval tool for context, and returns a structured answer. Provide the project structure, core code samples, and execution flow.
An adk-go agent implementation plan with folder structure, key Go code, and run steps.
Using adk-go, create an evaluation workflow for my customer support QA agent covering accuracy, response consistency, and tool-call success rate. Include sample test cases and evaluation scripts.
An executable agent evaluation plan with metrics, sample data, and test scripts.
Explain how to deploy a Go agent built with adk-go to production, including configuration management, logging and monitoring, containerization, and CI/CD recommendations, with example configs.
A production deployment guide covering containers, monitoring, configuration, and delivery workflow.
Deploy LangGraph or Google ADK agents as production-ready FastAPI services.
Extend AI coding agents with curated skills for development and professional workflows.
Diagnose AI workflow nodes for failure, security, and handoff risks.
Build, test, deploy, and optimize Agentforce agents across the full lifecycle.
Turn AI coding sessions into weekly reports, ADRs, and a searchable knowledge graph.
Query and understand large codebases with a fast knowledge graph for AI agents.