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Artículo: AMZ-B0FPRF6XSQ
Mastering Claude Code Subagents : Architecting Reliable, Debuggable, and Autonomous AI-Powered Programming Systems with Anthropic Tools & Modern Frameworks
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Kindle
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0.20 kg
0.20 kg
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Nuevo
Nuevo
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Amazon
Amazon
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USA
USA
Sobre este producto
- Mastering Claude Code Subagents: Architecting Reliable, Debuggable, and Autonomous AI-Powered Programming Systems with Anthropic Tools & Modern FrameworksClaude code subagents are the next frontier in AI-assisted programming. This hands-on guide takes you from first principles to full production systems, showing you how to design, orchestrate, and deploy reliable subagent pipelines that actually work in real-world CI/CD environments.Why this book?Purely practical: arrow-only flowcharts, structured tables, and runnable code—no filler.Modern stack: Claude 3.5+, LangChain, LangGraph, Semantic Kernel, MCP, RAG, FastAPI, Next.js, Docker, Kubernetes, Prometheus/Grafana, GitHub Actions, and more.Production mindset: contracts-first design, sandbox validation, observability, and human-in-the-loop safety.What you’ll build:Subagent foundations: context isolation, debug loops, internal self-checks.Reliable pipelines: error reduction, execution simulation, handling large inputs.Framework integrations: Claude with LangChain, LangGraph DAGs, Semantic Kernel planners, and MCP tools.Data & ML workflows: Pandas cleaning, NumPy/PyTorch error correction, RAG augmentation.CI/CD automation: test generation, AI-powered reviews, GitHub Actions, VSCode extensions.Full-stack deployment: FastAPI backend, Next.js dashboard, Kafka queues, Postgres persistence, Docker/Kubernetes autoscaling.Observability & safety: logging, metrics, tracing, security scans, RBAC, sandbox testing.Scaling & future-proofing: hybrid Claude + GPT + local LLM routing, memory layers, multi-subagent orchestration, math and planning subagents.Practice Labs you’ll keep using:Build your first Claude subagent in Python.Construct a debuggable data transformer.Orchestrate with LangGraph and MCP.Create a subagent-driven ML preprocessing pipeline.Automate test suites and reviews.Deploy a full-stack production debugger with Docker & Kubernetes.Architect a memory-augmented multi-subagent orchestrator.Who this book is for:Developers and DevOps engineers building AI-assisted tooling.Data/ML engineers integrating debugging pipelines with Claude.Architects and tech leads designing multi-agent, multi-LLM systems.Inside the Appendices: Prompt patterns you can paste into production, API integration recipes (LangChain, LangGraph, Semantic Kernel, MCP), deployment cheat sheets (Docker, Kubernetes, Vercel, Serverless), benchmarking frameworks, and further Anthropic ecosystem resources.You won’t just “use” Claude—you’ll master subagent architecture and build systems that are measurable, observable, secure, and ready for scale. Whether automating code reviews, hardening CI pipelines, or deploying a full debugging platform, this book gives you the blueprint.Order your copy now and start architecting AI-powered programming systems you can trust.
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