#Token optimization
1823 related articles
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Deep Dives·3 min
Claude Code Source Code Leak Revealed: Seven Core Mechanisms of the Harness Architecture Explained
Deep analysis of the Claude Code source code leak, revealing seven core mechanisms of its Harness architecture including context management, tool call orchestration, and state tracking for AI Agent developers.
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Product Reviews·4 min
Hermes Agent Web UI Complete Review: Kanban Feature + Desktop App Hands-On Experience
In-depth review of Hermes Agent's Web UI, Kanban board, desktop app, and Terminal UI dashboard. Compared with Claude Code, see how this free open-source AI Agent framework makes automation accessible.
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Deep Dives·3 min
Deep Dive into Hermes Agent: A Self-Evolving AI Framework That Uses Fewer Tokens Than OpenManus
Deep analysis of Hermes Agent: lower Token usage than OpenManus, persistent long-term memory, and a self-learning loop. See how this 120K-Star GitHub project redefines AI Agents.
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Research·3 min
MEMOIR: Solving AI Agent Memory Management with Git Version Control
MEMOIR is an open-source tool bringing Git version control to AI Agent memory management, with branching, rollback, semantic paths, and visualization to solve context pollution and memory drift.
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Deep Dives·3 min
Deep Dive into ByteDance's Hermes Agent Orange Book: A 198-Page Complete Guide to AI Agent Development
Deep dive into ByteDance's Hermes Agent Orange Book covering self-evolution loops, three-layer memory systems, Skill ecosystems, and multi-Agent collaboration — a complete 198-page technical guide.
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Tutorials·4 min
AI-Powered Research in Practice: From LLM Selection to Building Automated Workflows with N8N
A deep dive into AI-driven research methodology: LLM selection, Python automation, Zotero reference management, Overleaf writing, local LLM deployment, and N8N workflow automation.
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Deep Dives·4 min
Harness Engineering Explained: The Third-Generation Development Paradigm for Taming AI Agents
Deep dive into Harness Engineering: the third-gen AI development paradigm. Learn its three-layer architecture for effectively harnessing AI Agents to complete complex development tasks.
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Tutorials·4 min
A Practical Guide for Java Developers Transitioning to AI Agent Development: Technology Selection, Architecture Design & Resume Positioning
A systematic guide for Java developers entering AI Agent development, covering core concepts, Workflow vs. Agent architecture comparison, Spring AI Alibaba selection, and resume positioning strategies.
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Deep Dives·4 min
From AIGC to AI Agent: Core Strategies and Practical Guide for Multi-Agent Development in 2025
Deep analysis of AIGC vs AI Agent differences, covering multi-agent system architecture, task orchestration, hallucination control, with developer skill roadmap and career outlook.
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Expert Opinions·3 min
Sam Altman in Conversation with Garry Tan: How OpenAI and YC Are Co-Shaping the AI Startup Ecosystem
Sam Altman and YC President Garry Tan discuss the convergence of OpenAI's foundation models and YC's startup ecosystem, revealing key signals about the next phase of AI entrepreneurship.
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Tutorials·4 min
A Practical Guide for QA Engineers: Building 18 AI Agents with 5 Essential Tools
Learn how QA engineers can build 18 AI Agents using Coze, LangChain, Dify, Cursor, and Skills — covering requirements analysis, test case generation, script writing, and regression testing with up to 10x efficiency gains.
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Product Reviews·3 min
How to Choose an AI Agent Framework in 2026? Pros and Cons of Four Leading Solutions
Compare four leading AI Agent frameworks in 2026: Coze, AutoGen, CrewAI, LangChain, and AutoGen Studio — covering coding requirements, private deployment, and commercialization.
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Deep Dives·3 min
Microsoft Tutel: A Deep Dive into the MoE Model Acceleration Library with FP4/FP8 Low-Precision Support
A deep dive into Microsoft's open-source Tutel MoE optimization library, supporting FP8, NVFP4, and MXFP4 multi-precision computation for DeepSeek, Kimi-K2, Qwen3, and other leading MoE models.
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Tutorials·4 min
LangChain Agent in Practice: Building a Production-Grade AI Agent from Scratch
A comprehensive guide to building production-grade AI Agents with LangChain, covering architecture design, tools, memory systems, ReAct strategy, and enterprise deployment.
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Tutorials·4 min
Coze AI Agent Tutorial: A Complete Guide to Building AI Agents from Scratch
Complete guide to building AI agents on Coze from scratch, covering LLM configuration, prompt writing, plugin integration, knowledge base setup, and memory systems.
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Tech Frontiers·2 min
Bugbot Custom PR Review Depth: Cursor Team's New Approach to AI Code Review
Cursor's AI code review tool Bugbot adds custom review effort, letting developers adjust PR review depth by code importance. Analysis of usage strategies and workflow impact.
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Tutorials·4 min
LangChain Deep Agents in Practice: Ten Agent Development Pain Points and Their Solutions
Deep dive into LangChain Deep Agents paradigm, analyzing ten Agent development pain points including tool sprawl and context pollution, with practical enterprise solutions using Deep Research.
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Tutorials·3 min
4-bit QLoRA Fine-tuning LLaMA 3 in Practice: A Guide to Training 8 Billion Parameter LLMs on Consumer GPUs
Learn how to fine-tune LLaMA 3 8B on consumer GPUs using QLoRA and Unsloth. Covers 4-bit quantization, LoRA adaptation, Alpaca data format, training pipeline setup, and model deployment—runs on RTX 3090.
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Product Reviews·3 min
awesome-LLM-resources: A Comprehensive Analysis of the 8,200-Star LLM Learning Resource Repository on GitHub
In-depth analysis of the 8,200-star GitHub project awesome-LLM-resources, covering multimodal generation, Agents, model training, MCP protocol, and more — a one-stop LLM learning guide.
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