AI/ML Design Services

• A curated collection of design patterns, architectures, and practical examples for building AI/ML-powered applications
• This repo explores the full AI/ML development lifecycle - from foundational models and prompt engineering to agents, vector databases, cloud services, and live application stacks.
• It also includes reference guides, and real-world use cases for AI-driven solutions.

✨ Features

	Remarks
⚙️ Agent Engineering	Design, build, and orchestrate intelligent agents
📝 Prompt Engineering	Strategies for effective LLM prompting
🔗 Context Engineering	Managing memory, retrieval, and grounding
🧩 Vector Databases	Integrations and design considerations
🛠️ MCP Server	Extend AI assistants with custom tools and protocols
☁️ AWS Services	Cloud-native AI/ML infrastructure patterns
🌐 Tech Stacks for Live Apps	Combining models, databases, and APIs
🎯 Use Cases	Practical applications across industries

References

• Getting Started with Generative AI and Foundation Models
• Read more