#Claude Code memory layer
1266 related articles
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·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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Industry Insights·3 min
Six Foundational Upgrades to Claude Code: AI Programming Moves from Lab to Industrial Scale
Anthropic's largest-ever foundational upgrade to Claude Code fixes six critical issues at once—terminal flickering, thinking freezes, cryptic errors, context deadlocks, unstable connections, and session crashes—shifting AI coding competition to the infrastructure layer.
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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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Tutorials·2 min
Harness Engineering Deep Dive: Multi-Level Memory and Multi-Agent Collaborative Development in Practice
Deep dive into Harness Engineering: deconstructing Claude Code's multi-level memory, defense-in-depth, Hermes Agent autonomous evolution, and multi-Agent collaboration for industrial-grade AI development.
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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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Tutorials·2 min
Multi-Model Hot-Swap Architecture: Switch AI Models at Minimal Cost
A complete guide to building a multi-model hot-swap architecture for production AI projects, covering abstraction layers, adapter patterns, visual configuration, and error-fixing workflows.
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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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Product Reviews·3 min
Web Studio: Open-Source Local AI Coding Workbench Integrating Three Major Agents
Web Studio is an open-source desktop AI coding workbench integrating Cloud Code, Gemini CLI, and Codex into a local-first app with multi-repo management, structured code review, and smart PR workflows.
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Product Reviews·3 min
OpenCode: A Deep Dive into the Terminal AI Coding Tool Built with Go
Deep dive into OpenCode, a terminal AI coding tool built with Go. Blazing-fast startup, multi-model support (Gemini, Claude), built-in Vim editor, and LSP integration. Compared with Claude Code and Aider.
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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·2 min
Building an Agent Framework from Scratch: Breaking Down the Four Core Modules with Code Implementation
Learn how to split AI Agent capabilities into four modules—Tool Registry, Message Store, Agent Runtime, and Built-in Tools—and build a reusable, extensible Agent framework using Python decorators.
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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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Tutorials·3 min
Harness Engineering: A Practical Guide to AI Programming — From Prompts to Mastery
Explore the three stages of AI programming evolution: from Prompt Engineering to Context Engineering to Harness Engineering. Master enterprise-grade AI coding with Cloud Code + VS Code.
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Tutorials·3 min
Claude Code: 19 Essential Commands Explained with Practical Tips to Avoid Common Pitfalls
A deep dive into 19 essential Claude Code commands across conversation management, settings, utilities, permissions, and plugins, plus a golden workflow to double your dev productivity.
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Product Reviews·2 min
CodexPlusPlus: A Rust-Rewritten Codex Enhancement Tool That 10x Improves the Experience
CodexPlusPlus is a Rust-built open-source enhancement for OpenAI Codex with snippet management, multi-cursor editing, and auto login bypass. 4000+ GitHub Stars.
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Product Reviews·2 min
feishu-claude-bridge Open Source Project Analysis: A Practical Guide to Integrating Claude Code with Feishu
In-depth analysis of the feishu-claude-bridge open-source project: how to use Claude Code for AI programming directly in Feishu, covering architecture, deployment, and use cases.
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