From LLM Prototype to Production Service? A Complete Architecture Design Guide for Production Deployment (Including Observability and Security)
Taking an LLM application beyond PoC and deploying it reliably to real users is complex. This guide lays out a full production blueprint—from API gateway through caching, observability, and security—that you need to operate at scale.
[Architecture Guide] LLM-Based Enterprise AI Systems: A Blueprint from Prototype to Production
Beyond simple LLM API calls, this guide presents architecture design strategies for enterprise-grade AI systems that can be applied in real business environments. Explore a practical implementation blueprint centered on three core pillars:
Ditch Simple Diagrams: Completing High-Performance System Design with Data Flow and Latency
Architecture diagrams alone aren't enough. This guide presents a practical methodology for tracing data flow through a system and quantitatively analyzing the latency each component introduces so you can find the real performance bottleneck
End Manual Handoffs Between AI Agents: A Complete Guide to Workflow Orchestration
This guide shows how to fix critical bottlenecks—context loss, unrecoverable failures, and more—that appear as LLM-based agent systems grow more complex. It explains workflow orchestration patterns and lays out a technical roadmap for build
Fatal Errors in LLM-Based AI Systems: 5 Architectural Pitfalls Caused by Failed State Management
As LLM services evolve beyond simple chatbots into complex agents, state management becomes a bigger bottleneck than model performance. This guide diagnoses weaknesses in AI architecture and provides design patterns and an expert checklist
Beyond PoC to Production: An Architecture Blueprint for Enterprise AI Systems (Part 1)
Going beyond simple demo-level AI implementations, this article presents a systematic architecture framework for designing scalable enterprise AI systems that continuously deliver business value. From technology stack selection to governanc
Serverless vs. Edge Computing: A System Architect's Guide to Choosing the Optimal Distributed Computing Architecture
This article analyzes the fundamental differences between serverless and edge computing in addressing latency and data sovereignty problems that the cloud alone cannot solve. It presents a practical framework for designing the optimal hybri
Backend Framework Selection Guide: Optimal Choices by Scenario, from High Traffic to Rapid Development
An in-depth comparison of the core philosophies, strengths, and weaknesses of major backend frameworks including Spring Boot, Django, FastAPI, and NestJS. Practical guidelines for choosing the right tech stack based on project goals such as