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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

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Ray's Galactic Tech

Jul 19, 2026 · Artificial Intelligence

Why the Real Production Bottleneck for AI Agents Is the Harness, Not the Model

The article explains that when AI agents move from prototype to production, failures usually stem from the execution harness—issues like multi‑step orchestration, tool integration, context overflow, and lack of observability—rather than the underlying language model itself, and it provides a concrete seven‑layer framework (ETCLOVG) to diagnose and engineer a reliable harness.

AI AgentsETCLOVGHarness engineering

0 likes · 32 min read

Why the Real Production Bottleneck for AI Agents Is the Harness, Not the Model

Ray's Galactic Tech

Jul 18, 2026 · R&D Management

Stop Treating 22 Agent Hacks as a Checklist: A Practical Roadmap for Agentic Engineering

The article analyzes why AI coding agents succeed in simple tasks but falter on cross‑module work, argues that the core issue is missing state management, and proposes a step‑by‑step evolution—from extracting plans to multi‑agent governance—to make Agentic Engineering production‑ready.

AI AgentsPlan ManagementRAG

0 likes · 19 min read

Stop Treating 22 Agent Hacks as a Checklist: A Practical Roadmap for Agentic Engineering

Ray's Galactic Tech

Jul 17, 2026 · Artificial Intelligence

High‑Concurrency RAG: When to Use Classic, Graph or Agentic Architecture

The article analyzes why production‑grade RAG systems fail under load and explains how Classic, Graph, and Agentic RAG each address specific problem stages, offering concrete engineering guidelines for query normalization, caching, versioned knowledge, graph construction, stateful agents, and governance to achieve stable high‑throughput performance.

Agentic RAGKnowledge GovernanceRAG

0 likes · 31 min read

High‑Concurrency RAG: When to Use Classic, Graph or Agentic Architecture

Ray's Galactic Tech

Jul 17, 2026 · Backend Development

Three Critical Guarantees for Message Queues: No Loss, No Duplicates, No Disorder – Deep Dive into Production‑Grade Solutions

This article dissects why modern systems must enforce three reliability guarantees—no message loss, no duplicate processing, and no out‑of‑order delivery—by examining real‑world order flows, outbox patterns, idempotent keys, partitioning strategies, consumer acknowledgments, and operational safeguards such as replay, dead‑letter handling, and monitoring.

IdempotencyKafkaMessage Queue

0 likes · 28 min read

Three Critical Guarantees for Message Queues: No Loss, No Duplicates, No Disorder – Deep Dive into Production‑Grade Solutions

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.

Knowledge BaseRAGState 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 NativeGatewayKafka

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 DeploymentObservability

0 likes · 27 min read

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