Skill UI

This skill covers the comprehensive architecture design and construction of autonomous AI agents. Experts master advanced concepts including tool use, hierarchical memory systems (episodic, semantic, working), sophisticated planning strategies (ReAct, Plan-and-Execute), and multi-agent orchestration. It focuses on building systems that achieve high levels of autonomy while maintaining critical human oversight, designing for graceful degradation and rigorous error handling.

Deliver production-ready LLM applications, RAG systems, and multi-agent orchestration with vector databases, embedding strategies, safety controls, and observability for enterprise deployments.

Deliver production-ready LLM applications, RAG systems, and multi-agent orchestration with vector databases, embedding strategies, safety controls, and observability for enterprise deployments.

A comprehensive platform designed for building, deploying, and managing continuous, autonomous AI agents. Users can create complex, multi-step automation workflows using a visual, drag-and-drop node editor, or extend functionality using a dedicated developer toolkit. Ideal for implementing persistent agents triggered by webhooks, schedules, or manual input, enabling sophisticated, end-to-end AI automation pipelines.

A comprehensive platform designed for building, deploying, and managing continuous, autonomous AI agents. Users can create complex, multi-step automation workflows using a visual, drag-and-drop node editor, or extend functionality using a dedicated developer toolkit. Ideal for implementing persistent agents triggered by webhooks, schedules, or manual input, enabling sophisticated, end-to-end AI automation pipelines.

Guides building autonomous coding agents with reusable patterns for agent loops, multi-model orchestration, tool schemas, approval flows, and browser automation to keep LLM tool calling reliable.

Guides building autonomous coding agents with reusable patterns for agent loops, multi-model orchestration, tool schemas, approval flows, and browser automation to keep LLM tool calling reliable.

Guides building reliable autonomous agents by covering agent loops, goal decomposition, reflection, and tooling patterns while stressing guardrails, human review, and auditability to curb compounding failure rates in production.

Azure AI Agents Persistent SDK for .NET exposes low-level control over threads, messages, runs, tools, and vector stores so developers can orchestrate long-running, stateful AI assistants hosted in Azure.

Azure AI Agents Persistent SDK for .NET exposes low-level control over threads, messages, runs, tools, and vector stores so developers can orchestrate long-running, stateful AI assistants hosted in Azure.

Low-level Java SDK for creating, running, and cleaning up persistent Azure AI Agents with threads, messages, runs, and tool integrations, ideal for automating multi-step agent workflows within Azure AI projects.

Low-level Java SDK for creating, running, and cleaning up persistent Azure AI Agents with threads, messages, runs, and tool integrations, ideal for automating multi-step agent workflows within Azure AI projects.