🏗️ Architecture Insights¶
Architecture Insights is a growing collection of concise, architecture-focused articles that accompany my Enterprise AI Systems Architecture series on LinkedIn.
Each LinkedIn post explores an important aspect of designing modern enterprise AI systems through architecture-focused explanations, diagrams, and practical design perspectives. This section brings those ideas together on the blog as a structured quick recap for AI architects, engineers, and technical leaders.
Each Architecture Insight provides a concise overview of the corresponding LinkedIn topic, focusing on the architectural problem, core components, system interactions, key design decisions, trade-offs, and production considerations.
The goal is to make complex enterprise AI architecture topics easier to revisit and understand without requiring a full deep-dive into an entire handbook chapter.
Topics include:
- Enterprise AI system architecture
- RAG architecture patterns
- AI agents and multi-agent systems
- AI gateways and model integration
- Retrieval and knowledge architectures
- Memory and state management
- AI orchestration patterns
- Observability and evaluation
- Security and governance
- Production AI design trade-offs
This is a continuously growing section. A new Architecture Insight is added alongside each new topic published in the Enterprise AI Systems Architecture series on LinkedIn.
Explore Architecture Insights¶
Use this section as a quick architectural reference to revisit the key ideas, patterns, and design decisions behind modern enterprise AI systems.
Article¶
Canonical technical source
Detailed articles, architecture diagrams, code, and production analysis.
LinkedIn¶
Discovery + discussion
Compact versions, key insights, architecture discussions, and announcements.
Newsletter¶
Recurring audience
Selected new articles and engineering insights.
Handbook¶
Structured reference
Chapter-based technical learning material.
GitHub¶
Implementation
Projects, experiments, and supporting source code.
📚 Enterprise AI Engineering Handbook¶
The Enterprise AI Engineering Handbook provides structured technical reference material supporting this journey.
Enterprise AI Engineering Handbook
💻 GitHub¶
Implementation projects and supporting engineering work:
💼 LinkedIn¶
Follow the journey, article announcements, architecture discussions, and production AI insights:
[LinkedIn](https://www.linkedin.com/in/mihirkrjha/
📰 Enterprise AI Engineering Newsletter¶
Follow the broader technical journey through the Enterprise AI Engineering newsletter:
Enterprise AI Engineering Newsletter
👨💻 About the Author¶
Mihir Jha
Software Architect | AI Engineering | Cloud Architecture | Backend Engineering
Focused on bridging traditional software and cloud engineering with modern AI engineering to design scalable, secure, observable, and production-ready intelligent systems.