Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
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概要と使いどころ
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
日本語の概要は準備中です。原文の説明を表示しています。
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches. AI agents running in CI/CD pipelines.
日本語の概要は準備中です。原文の説明を表示しています。
Prepare for Anthropic-specific technical interviews covering Constitutional AI, RLHF, interpretability, scaling laws, MCP, agentic systems, and AI safety. Activate on "anthropic interview", "constitutional AI prep", "alignment interview", "safety interview", "RLHF opinion", "interpretability prep", "anthropic technical". NOT for general ML interview prep, system design interviews, coding challenges, or behavioral interview practice.
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Architecture and systems design for agents that retain bounded state across sessions. Covers durable event history, owned state, derived memory, retrieval indexes, framework evaluation, recovery, deletion, and rebuild behavior. Uses constructed implementation examples and workload calibration rather than universal vendor, latency, similarity, retention, or cost claims. Activate on: "always-on agent", "persistent agent architecture", "episodic memory system", "agent memory design", "long-running agent", "stateful agent", "agent that remembers", "MemGPT architecture", "Letta deployment", "/always-on-agent-architecture". NOT for: choosing what data to feed the agent (use always-on-agent-inputs), brainstorming applications (use always-on-agent-applications), safety and privacy concerns (use always-on-agent-safety), general agentic patterns (use agentic-patterns).
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Build production-grade AI agents from scratch using patterns inspired by production-grade agentic systems like Claude Code. Covers two audiences — (1) workflow builders who need planner+executor pipelines, human-in-the-loop checkpoints, and multi-agent orchestration, and (2) application embedders who need HTTP/SSE APIs, multi-user session management, and React frontend integration. Use when asked to build an AI agent, create a coding assistant, embed an agent in an app, build an API agent, clone Claude Code, build a CLI agent, design an agent architecture, scaffold an agentic system, or automate a multi-step workflow. Triggers on keywords like agent builder, agent blueprint, coding assistant, CLI agent, agentic tool, claude code clone, agent scaffold, agent architecture, workflow automation, multi-agent, planner executor, SSE streaming, agent API.
日本語の概要は準備中です。原文の説明を表示しています。
Azure AI Voice Live SDK for .NET. Build real-time voice AI applications with bidirectional WebSocket communication.
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Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.
日本語の概要は準備中です。原文の説明を表示しています。
Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.
日本語の概要は準備中です。原文の説明を表示しています。
Azure AI Agents Persistent SDK for Java. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.
日本語の概要は準備中です。原文の説明を表示しています。
Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes.
日本語の概要は準備中です。原文の説明を表示しています。
Azure AI VoiceLive SDK for Java. Real-time bidirectional voice conversations with AI assistants using WebSocket.
日本語の概要は準備中です。原文の説明を表示しています。
Build AI applications on Microsoft Foundry using the azure-ai-projects SDK.
日本語の概要は準備中です。原文の説明を表示しています。
Azure Container Registry SDK for Python. Use for managing container images, artifacts, and repositories.
日本語の概要は準備中です。原文の説明を表示しています。
Azure AI Projects SDK for Java. High-level SDK for Azure AI Foundry project management including connections, datasets, indexes, and evaluations.
日本語の概要は準備中です。原文の説明を表示しています。
Azure AI Voice Live SDK for JavaScript/TypeScript. Build real-time voice AI applications with bidirectional WebSocket communication.
日本語の概要は準備中です。原文の説明を表示しています。
AWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale. Use when working with any AgentCore service including Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, Observability, Agent Registry, or Evaluations.
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Configure AWS CloudTrail for audit logging. Set up organization trails and event analysis. Use when auditing AWS activity.
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Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
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Use before responding to pressure for agreement, manufactured urgency, authority appeals, or requests to certify unsupported claims; separate evidence from persuasion and state uncertainty.
日本語の概要は準備中です。原文の説明を表示しています。
Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.
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Autonomous AI agent tool router register: schema registration, runtime parameter coercion, idempotency keys, and error recovery policies.
日本語の概要は準備中です。原文の説明を表示しています。
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
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Autonomous AI agent benchmark evaluation register: task completion rates, planning accuracy, tool invocation precision, and cost benchmarks.
日本語の概要は準備中です。原文の説明を表示しています。
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
日本語の概要は準備中です。原文の説明を表示しています。