#LLM application layer
2309 related articles
Tech Frontiers·2 min
OpenAI Voice Hackathon: 4 Real-Time Voice AI Projects Built in Just 6 Hours
OpenAI hosted Voice Hack Night where teams built 4 real-time voice agent projects in 6 hours. Deep analysis of technical challenges, use cases, and developer ecosystem trends in real-time voice AI.
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Tutorials·3 min
Build a Claude Code Agentic OS in 3 Steps — Stop Using AI Like a Slot Machine
Learn how to transform Claude Code from a random prompting tool into a systematic Agentic OS through three layers: architecture, Obsidian memory, and an observability dashboard.
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Industry Insights
The Cnblogs Account Ban Incident: Why …
·3 min
The Cnblogs Account Ban Incident: Why a Legacy Tech Community Is Losing Its Creators
A veteran Cnblogs blogger was banned for 15 days over an AI programming tutorial. This article examines the incident, the platform's declining quality, and the survival crisis facing legacy tech communities.
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Product Reviews·3 min
Zion No-Code Platform Hands-On: Building a Production-Ready E-commerce Mini Program from Scratch Without Writing a Single Line of Code
Hands-on review of Zion no-code platform: building a production-ready e-commerce mini program from scratch with visual design, built-in database, workflow orchestration, AI Agent integration, and one-click multi-platform publishing.
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Tech Frontiers·2 min
Step 3.7 Flash: Deep Dive into the 198B Sparse MoE Multimodal Model
Deep dive into StepFun AI's Step 3.7 Flash, a 198B sparse MoE vision-language model with 256K context and 3-level reasoning, excelling in multimodal understanding, AI coding, and Agent tool orchestration.
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Tech Frontiers·2 min
LFM2.5-8B-A1B: A MoE Model with 1.5B Active Parameters Delivering 4x Its Weight Class Performance
Liquid AI releases LFM2.5-8B-A1B, a MoE model with 8B total params but only 1.5B active, matching 6B-class models in tool calling. Supports 128K context, local deployment, multilingual, with SGLang Day-0 support.
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Tech Frontiers·1 min
SGLang Hosts Agent Loops Office Hour, Focusing on Agentic Loop Architecture Optimization
SGLang team hosts an Agent Loops Office Hour exploring inference optimization for agentic loops, covering KV Cache reuse, low-latency multi-turn dialogue, and tool calling techniques.
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Tutorials·3 min
Spring AI Agent Utils: A Java Agent Toolkit Reverse-Engineered from Claude Code's Core Features
Deep dive into Spring AI Agent Utils toolkit covering Skill modules, Ask a User Question, To Do Write, Auto Memory, and multi-Agent orchestration — empowering Java developers to build powerful AI Agents.
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Product Reviews·3 min
Claude Code with MiniMax M2: Testing a Low-Cost AI Coding Solution Across Three Real Projects
Real-world testing of MiniMax M2 as Claude Code's backend model across three projects: framework migration, iOS development, and full-stack MVP — at just 8% of Claude's price.
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Industry Insights·3 min
Deep Dive into Three Major LLM Career Paths: Requirements, Tech Stacks, and Career Prospects
Deep analysis of three core LLM roles—Application Engineer, Development Engineer, and Algorithm Engineer—covering technical requirements, salary thresholds, and career prospects including RAG, fine-tuning, and inference deployment.
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Tutorials·2 min
MCP Protocol Practical Guide: The Standard Interface for Connecting LLMs to Everything
Deep dive into MCP (Model Context Protocol) principles and practical applications. Learn how LLMs connect to external tools via MCP to become agents, covering Java tech stacks, MCP Server ecosystem, Cherry Studio demos, and A2A protocol comparison.
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Tutorials·3 min
Bolt.DIY + Claude 3.7 Sonnet: Building Full-Stack Apps with Zero Code
Learn how to use open-source Bolt.DIY with Claude 3.7 Sonnet to build full-stack web apps with zero code. Includes local deployment tutorial, hands-on demo, and cost analysis—an AI course platform built in 13 minutes for $3.
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Tutorials·2 min
Bolt.diy + Gemini 2.0: A Complete Tutorial for Free No-Code APP Development
Learn how to use open-source Bolt.diy with Gemini 2.0 via OpenRouter to build complete apps for free with zero coding. Covers setup, hands-on demo, and pros/cons analysis.
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Deep Dives·3 min
memU Memory Framework Explained: Unifying Multi-Modal Agent Memory with a File System
Deep dive into the memU open-source memory framework: how it organizes Agent memory as a file system with three-layer semantic abstraction, dual-loop collaboration, and two retrieval modes.
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Tutorials·3 min
Practical Guide to Building Multi-Agent Collaborative Applications with CrewAI + FastAPI
Learn how to build a multi-Agent collaborative system with CrewAI and FastAPI. Covers Agent, Task, Crew concepts, GPT/Tongyi Qianwen/Ollama integration, with complete code examples and model comparisons.
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Tutorials·2 min
WenzAgent Open-Source Framework: A Practical Tutorial for Multi-Agent Collaborative Management on LAN
A detailed guide on deploying WenzAgent, an open-source multi-Agent management framework under Apache License, supporting LAN-based multi-device AI agent collaboration with Server-Client architecture.
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Tutorials·3 min
The Complete Guide to Spring AI: A Full Learning Path for Java Engineers Building AI Applications
A comprehensive guide to Spring AI covering LLM integration, prompt engineering, RAG knowledge bases, and five AI Agent patterns, with three enterprise projects for Java engineers.
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Tutorials·3 min
Getting Started with LangChain: Core Concepts and Hands-On Guide for LLM and Agent Development
A systematic guide to LangChain's core features, covering LLM vs. Agent concepts, unified interface design, multi-provider support, environment setup, and hands-on code examples for AI app development.
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Tech Frontiers·3 min
Generic Agent: A Self-Evolving AI Agent Built with Just 3,000 Lines of Code
Generic Agent builds a self-evolving AI agent with just 3,000 lines of code, 9 atomic tools, and a five-layer memory architecture — using only one-sixth the tokens of competitors.
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Tutorials·3 min
AI Agent Learning Roadmap: From Beginner to Enterprise-Level Development in Three Months
A detailed three-month AI Agent learning roadmap covering LLM basics, ReAct paradigm, LangChain, memory mechanisms, tool calling, and multi-agent collaboration with practical project suggestions.
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