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Ray's Galactic Tech

Practice together, never alone. We cover programming languages, development tools, learning methods, and pitfall notes. We simplify complex topics, guiding you from beginner to advanced. Weekly practical content—let's grow together!

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Latest from Ray's Galactic Tech

100 recent articles max

Ray's Galactic Tech

Jul 16, 2026 · Backend Development

Building a Scalable Smart Tag System for 100k QPS with AI‑Generated Code

The article explains that while many teams focus on model accuracy, the real challenges of an AI‑powered tagging system are write spikes, timeouts, duplicate tagging, cost overruns and state inconsistency, and it proposes a five‑layer architecture, async fallback, governance and validation practices to reliably achieve a 100 k QPS target.

AI taggingKafkaLLM Integration

0 likes · 30 min read

Building a Scalable Smart Tag System for 100k QPS with AI‑Generated Code

Ray's Galactic Tech

Jul 16, 2026 · Artificial Intelligence

K8s, Kafka, Nacos Agent Platform to Prevent Token Bankruptcy and Skill Avalanches

The article details how a production‑grade Agent platform built on Kubernetes, Kafka, and Nacos addresses token budget overruns, uncontrolled skill execution, and RAG hallucinations by introducing a four‑layer runtime architecture, token pre‑allocation, explicit state management, dynamic governance policies, and robust skill specifications.

KafkaKubernetesLLM Agents

0 likes · 32 min read

K8s, Kafka, Nacos Agent Platform to Prevent Token Bankruptcy and Skill Avalanches

Ray's Galactic Tech

Jul 15, 2026 · Artificial Intelligence

Scalable Knowledge Base with High‑Concurrency Crawling and Vector Search

The article explains why a production‑grade enterprise knowledge base requires more than just dumping PDFs into a vector store, detailing a distributed, event‑driven architecture with separate collection, processing, retrieval, and governance layers that handle high‑concurrency crawling, real‑time cleaning, versioned indexing, permission filtering, and feedback‑driven updates.

Distributed SystemsRAGState Management

0 likes · 39 min read

Scalable Knowledge Base with High‑Concurrency Crawling and Vector Search

Ray's Galactic Tech

Jul 15, 2026 · Artificial Intelligence

AI Code Generation on Autopilot: Building a Production‑Ready Loop Engineering Loop

The article explains why AI‑assisted coding must move from one‑off prompt engineering to a continuous Loop Engineering approach that observes, plans, acts, verifies, and reflects on each attempt, detailing a four‑plane architecture, budget and safety controls, concrete code examples, and common pitfalls to achieve a convergent, auditable production‑grade code‑generation pipeline.

AI code generationCI/CDDevOps

0 likes · 38 min read

AI Code Generation on Autopilot: Building a Production‑Ready Loop Engineering Loop

Ray's Galactic Tech

Jul 14, 2026 · Cloud Native

Spring Boot + Netty MQTT Gateway for Million Connections & Millisecond Push

To support millions of persistent MQTT connections with sub‑millisecond latency, the article walks through a Spring Boot + Netty cloud‑native gateway design that separates connection, event, state and governance planes, details async authentication, back‑pressure handling, command state machines, and loss‑less Kubernetes roll‑outs.

Cloud NativeKafkaKubernetes

0 likes · 38 min read

Spring Boot + Netty MQTT Gateway for Million Connections & Millisecond Push

Ray's Galactic Tech

Jul 14, 2026 · Backend Development

How We Built a RAG‑Powered Knowledge Base That Actually Understands Source Code

The article explains why traditional FAQs fail for complex production issues, then details the design of a retrieval‑augmented generation knowledge engine that ingests source code, configuration, design docs, and incident reports, offering version‑consistent, permission‑aware answers with evidence‑backed citations.

Knowledge EngineKubernetes DeploymentRAG

0 likes · 27 min read

How We Built a RAG‑Powered Knowledge Base That Actually Understands Source Code

Ray's Galactic Tech

Jul 13, 2026 · Artificial Intelligence

From 22% Error Rate to 1.3%: How I Made an AI Agent Reliably Handle Order Queries and Refunds

This article analyses why Function Call demos often break in production, proposes a four‑plane architecture (control, execution, state, governance), details tool gating, idempotency, state‑machine modeling, observability and evaluation, and shows how these steps reduced the error rate of an order‑query and refund agent from 22% to 1.3%.

AI AgentFunction Callorder management

0 likes · 58 min read

From 22% Error Rate to 1.3%: How I Made an AI Agent Reliably Handle Order Queries and Refunds

Ray's Galactic Tech

Jul 13, 2026 · Artificial Intelligence

When AI Agents Meet Cloud‑Native: Practical Multi‑Agent Orchestration for High‑Concurrency Scenarios

The article explains why naïve multi‑agent demos fail in production, defines the core concepts of Task, Step, Agent Role and Event, proposes a four‑plane cloud‑native architecture, shows concrete Go and Python code, and provides detailed guidance on state machines, reliability, observability, security and budget governance for building scalable, production‑grade AI agent systems.

AI AgentsCloud NativeKubernetes

0 likes · 36 min read

When AI Agents Meet Cloud‑Native: Practical Multi‑Agent Orchestration for High‑Concurrency Scenarios

Ray's Galactic Tech

Apr 27, 2026 · Artificial Intelligence

Using AI to Auto‑Generate Forms: Production‑Ready Low‑Code Form Generation with Spring AI Alibaba ReactAgent

The article presents a production‑grade solution that lets users describe a form in natural language, then uses a Spring AI Alibaba ReactAgent powered by a ReAct reasoning loop to retrieve templates, validate fields, generate layout, enforce governance, and finally emit a versioned JSON schema ready for deployment.

ReActAgentReactSpring AI

0 likes · 29 min read

Using AI to Auto‑Generate Forms: Production‑Ready Low‑Code Form Generation with Spring AI Alibaba ReactAgent

Ray's Galactic Tech

Apr 27, 2026 · Backend Development

Java Engineer’s Complete Guide to Enterprise LLM Apps: LLM, Agent, RAG & Skill

This article walks Java engineers through building production‑grade enterprise AI assistants, explaining the roles of LLM, RAG, Agent and Skill, detailing a layered architecture, best‑practice code samples, deployment strategies, observability, security and cost‑control considerations.

BackendJavaLLM

0 likes · 37 min read

Java Engineer’s Complete Guide to Enterprise LLM Apps: LLM, Agent, RAG & Skill