ai-design-components

MLOps patterns, prompt engineering, LLM evaluation, and embedding optimization

76 skills

AI/ML data engineering and model serving

76 skills

API development, messaging, and real-time communication

76 skills

Database and data storage: relational, vector, time-series, document, graph, plus data ingestion

76 skills

Observability, security, and deployment infrastructure

76 skills

Cloud-specific patterns and best practices for AWS, GCP, and Azure

76 skills

Data architecture, streaming pipelines, transformations, SQL optimization, and performance engineering

76 skills

API design, CLI development, SDK creation, documentation generation, debugging, and Git workflows

76 skills

CI/CD pipelines, GitOps workflows, testing strategies, platform engineering, and containerization

76 skills

Cloud cost optimization and resource tagging strategies

76 skills

Kubernetes operations, infrastructure as code, networking, service mesh, and distributed systems

76 skills

Security architecture, compliance frameworks, vulnerability management, TLS, firewalls, and SIEM

76 skills

Capstone skill for assembling component outputs into unified, production-ready systems with token validation and framework scaffolding

76 skills

Media management and user onboarding components for content-rich experiences

76 skills

Data visualization, tables, and dashboard components for displaying and analyzing data

76 skills

Foundational design system including tokens and theming for consistent styling across all components

76 skills

Form systems, search, and filter components for user input and data collection

76 skills

Interactive components including AI chat interfaces, drag-drop functionality, and feedback systems

76 skills

Navigation, layout, and timeline components for app structure and organization

76 skills