#LLM development
3639 related articles
·3 min
Java + AI in Practice: Building an Enterprise-Grade Airline Intelligent Customer Service System
Learn how Java engineers can enter AI application development using Spring AI to build an enterprise-grade airline intelligent customer service system with RAG, Function Calling, and more.
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·2 min
Embabel: A Deep Dive into the AI Agent Framework Built for the JVM
Embabel is a JVM agent framework written in Kotlin, enabling Java/Kotlin developers to build AI Agents within their familiar tech stack. A deep analysis of its positioning, technical advantages, and synergy with the Spring ecosystem.
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·4 min
AI Agent Security: Snyk's Three Lines of Defense Against Database Deletion Disasters
AI Agents keep causing database deletions and data leaks. Snyk proposes three ADS defense lines: trusted code generation, supply chain protection, and behavioral governance using hooks and deterministic guardrails.
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·5 min
Harness: The Operating System That Takes LLM Agents from Demo to Production
Deep dive into Harness technology: how context engineering, memory management, and multi-agent architecture transform LLM agents from stochastic demos into stable production systems.
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·3 min
Cognitive Debt: When Developers Outsource Their Own Thinking
A real case of a tech lead who outsourced all thinking to AI and fell into cognitive hollowing. Explore the definition, dangers, and strategies for cognitive debt in the AI era.
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Java Backend to AI: A Practical Guide to Multi-Agent Collaboration with Spring AI
How can Java backend engineers transition to AI Agent development? This guide covers the evolution from Chat to Agentic AI, ReAct decision-making, MCP tool calling, and multi-Agent orchestration with Spring AI.
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·4 min
Getting Started with LangChain 1.3: Ecosystem Architecture & Agent Development Complete Guide
Complete guide to LangChain 1.3 ecosystem: four core modules (LangChain, LangGraph, DeepAgent, LangSmith), from setup to building your first Agent with tools, prompts & memory.
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·2 min
MCP Protocol Explained: The Unified Standard for AI Tool Calling and a Practical Guide
Deep dive into MCP (Model Context Protocol): how it unifies LLM tool calling standards, enables cross-model tool reuse, and decouples Agents from tools for efficient AI development.
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·4 min
6 Must-Do Tasks Before Deploying Enterprise AI Agents: A Complete Guide to Observability + Evaluation
A detailed guide to 6 critical engineering challenges for enterprise AI Agents before production, covering Langfuse-based tracing, observability, evaluation stages, prompt governance, and high-concurrency architecture.
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·5 min
Building Data Agents with BigQuery and ADK: AgentOps in One Line of Code
Deep dive into Google Cloud's complete stack for building data Agents with BigQuery and ADK, covering MCP Toolbox parameterized SQL, managed MCP servers, and Agent Analytics one-line observability.
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·3 min
Tutorial: Connect Claude, Codex, and Other LLMs to Copilot in VSCode
Learn how to connect Claude, Codex, and other LLMs to VSCode's Copilot Chat via a third-party API proxy plugin. Four steps: get a Key, install plugin, manage models, and switch freely.
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·3 min
What Are AI Agents? A Deep Dive into the Three Core Components: Perception, Decision, and Action
A deep dive into AI Agents: their definition and three core components—Perception, Decision, and Action. Learn what distinguishes real AI agents from chatbots and automation scripts.
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·4 min
MCP + Skill in Practice: A Guide to Building an Automated Enterprise Regulatory Risk Alert System
A detailed guide on building an automated enterprise regulatory risk alert system using MCP protocol and Agent Skill, covering data collection, six evidence thresholds, applicability judgment, actionable measures, and delivery via Feishu/email.
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·3 min
EgoLite Browser Deep Dive: Why It's Better Than Playwright MCP for Personal AI Automation
Deep dive into EgoLite Agent browser, comparing it with Playwright MCP and Browser Use. Analyzing Space isolation, script-based operations, and Skill features.
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·3 min
GitHub Daily · August 13: Local AI Tools Surge in Popularity, Privacy-First Becomes the Dominant Theme
GitHub Trending Aug 13: Local-first AI tools dominate with FluidVoice, unsloth, and modly, while Agent integration projects like holaOS and obsidian-skills reshape workflows.
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·4 min
OpenCode Practical Guide: Installation, Configuration & Usage Tutorial for This Open-Source Claude Code Alternative
Complete guide to OpenCode, the open-source Claude Code alternative: covers desktop and WSL installation, model configuration, rule files, custom commands, and MCP service integration.
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·3 min
Unsloth Desktop: The First Open-Source AI Desktop App Supporting Local Training + Inference
Unsloth Desktop is an open-source app for Mac/Windows/Linux that integrates local model training and inference with 2x speed, 70% VRAM savings, GGUF/MLX support, and Claude Code connectivity.
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·3 min
How a Senior Data Scientist Navigates Job Hunting After Being Laid Off: A Survival Guide for the AI Job Market
A senior data scientist with a Physics PhD and 4.5 years of experience gets laid off, revealing the AI job market's shift from traditional ML to Agent engineering. Practical advice on bridging skill gaps.
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·2 min
Reasoning Chain Theft Attacks on Closed-Source LLMs: Security Risks of API Side Channels
Are hidden reasoning chains in closed-source LLMs truly secure? Research shows attackers can reconstruct full thought chains via API side-channel signals, threatening trade secrets and IP.
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·3 min
DeepSeek Plans Significant Price Hikes: Is the Era of Cheap AI Coming to an End?
DeepSeek plans significant API price hikes, signaling the end of ultra-cheap AI. We analyze the drivers, developer impact, and industry shift from price wars to rational pricing.
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