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ai-architect-academy
ai-architect-academy enthält 23 gesammelte Skills von frankxai, mit Repository-Berufsabdeckung und Skill-Detailseiten auf SkillsMP.
Skills in diesem Repository
Patterns for multi-agent coordination, task decomposition, handoffs, and workflow orchestration. Best practices for building and managing agent systems.
Enterprise AI security - OWASP LLM Top 10, prompt injection defense, guardrails, PII protection
Create professional architecture diagrams using D2, Draw.io, Mermaid, and OCI official icons for enterprise-grade visualizations
Build AI applications on AWS using Bedrock, SageMaker, and AI/ML services with best practices for enterprise deployment
Build AI applications on Azure using Azure OpenAI, Cognitive Services, and ML services with enterprise patterns
Build autonomous AI agents using Claude Agent SDK with computer use, tool calling, MCP integration, and production best practices
Production-grade AI architecture patterns for enterprise - security, governance, scalability, and operational excellence
Cost optimization for AI workloads - model selection, GPU sizing, commitment strategies, and multi-cloud cost management
Expert in OCI Generative AI Dedicated AI Clusters - deployment, fine-tuning, optimization, and production operations
Train and fine-tune LLMs using HuggingFace TRL, Transformers, and cloud GPU infrastructure with SFT, DPO, GRPO methods
Automated skill for keeping AI knowledge bases current with latest model versions, framework updates, and best practices
Deploy and operate AI workloads on Kubernetes with GPU scheduling, model serving, and MLOps patterns
Build production-grade agentic workflows with LangGraph using graph-based orchestration, state machines, human-in-the-loop, and advanced control flow
Current best practices for Model Context Protocol server design, implementation, and integration. Updated patterns for 2026 MCP ecosystem including multi-server orchestration, security, and performance.
Design and implement Model Context Protocol servers for standardized AI-to-data integration with resources, tools, prompts, and security best practices
Design and deploy AI workloads across AWS, Azure, GCP, and OCI with intelligent routing, cost optimization, and cross-cloud patterns
NVIDIA NIM inference microservices for deploying AI models with OpenAI-compatible APIs, self-hosted or cloud
Expert guidance on Oracle Cloud Infrastructure services, cloud architecture patterns, cost optimization, deployment strategies, and OCI best practices for enterprise solutions
Build production-ready multi-agent systems using OpenAI AgentKit and Agents SDK with best practices for agent orchestration, handoffs, and routines
Build production agentic applications on OCI using Oracle Agent Development Kit with multi-agent orchestration, function tools, and enterprise patterns
Design framework-agnostic AI agents using Oracle's Open Agent Specification for portable, interoperable agentic systems with JSON/YAML definitions
Expert in Retrieval-Augmented Generation systems - knowledge bases, chunking strategies, embedding optimization, and production RAG architectures
Infrastructure as Code for AI workloads using Terraform across AWS, Azure, GCP, and OCI