#reasoning context persistence
288 related articles
·6 min
GPT-5.6 Sol Hands-On: How Multi-Agent Parallelism Is Reshaping AI Coding Workflows
Based on Fireship's review, an in-depth look at GPT-5.6 Sol's Ultra Mode multi-agent parallelism, its 91.9% Terminal Bench score, and how it differs from Claude Fable in cost, speed, and precision.
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·3 min
Langchain.js Agent Development: A Guide to Deconstructing the OpenClaw Engine Architecture
An in-depth analysis of AI agent development based on Langchain.js—comparing workflow agents and Agent Loops, deconstructing the TypeScript implementation path of an OpenClaw-like engine, covering structured output, MCP, and LangGraph.
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·6 min
AI Agent Development Learning Path: Four Stages from Zero to Hands-On Projects
A systematic breakdown of the AI agent development learning path, covering four stages: fundamentals, RAG knowledge bases, tool use, multi-agent collaboration, and hands-on projects.
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·7 min
Breaking Down the Core Skills of an AI Application Engineer: From Beginner to Industrial-Grade Deployment
Knowing how to call an API doesn't make you an AI engineer. This article breaks down the complete skill structure of an AI application engineer, covering Python fundamentals, LLM fine-tuning, Agent development, and enterprise projects.
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·5 min
GPT-5.6 In-Depth Field Test: A Real-World Log After Burning Through $200K
A developer stress-tested GPT-5.6 for six weeks across 67 projects, burning $180K-$240K in inference. Real cases of task persistence, Rust rewrites, autonomous browser control — plus honest frontend and 3D shortfalls.
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·6 min
An Efficient Learning Guide for Data Science: Study Partnerships and Hands-On ML in Practice
Struggling to learn data science alone? This article explores the value of study partnerships and pairs them with the classic Hands-On ML textbook to offer a phased learning plan from math foundations to deep learning.
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·5 min
Getting Started with LangGraph: Building AI Agent Workflows with Graph Structures
Master LangGraph core concepts: nodes, edges, and routing functions. Learn StateGraph, MemorySaver, and ToolNode through a weather-query Hello World example, and understand how LangGraph relates to LangChain and powers Agent workflows.
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·3 min
Hermes Agent for Kubernetes Cluster Management: AIOps Tool Selection and Cost Analysis
An in-depth review of managing Kubernetes clusters with Hermes Agent, covering K8S AIOps tool evolution, the truth about Token costs, and a three-level AI operations framework.
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·3 min
Building a Local AI Coding Agent on Mac: A Complete Guide with Ollama, OpenCode, and MCP
A complete guide to building a local AI coding agent on a 32GB Mac: Ollama for local inference, OpenCode as the agent framework, and MCP memory servers for cross-session context. Code stays on-device, no subscription fees.
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·5 min
AI Agent Custom Tool Development Guide: Boost Efficiency by One-Click Reuse of Repetitive Tasks
An in-depth guide on developing Custom Tools for AI agents, compressing repetitive tasks like Excel-to-Markdown conversion from 30 minutes to under 5 seconds. Covers AGENTS.md registration, tool directory setup, and AI-assisted development.
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·3 min
The Complete AI Agent Development Workflow: A Seven-Step Guide from Requirements Analysis to Deployment
Want to build an AI Agent but don't know where to start? This guide covers the complete seven-step workflow—from requirements analysis, platform selection, prompt engineering, data storage, and UI building to testing and deployment.
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·6 min
AI Agent Development in Go: A Hands-On Guide to ByteDance's Eino Framework and Its Seven Core Capabilities
Build production-grade AI Agents with a pure Go stack using ByteDance's Eino framework. A deep dive into seven core capabilities: multi-Agent orchestration, long-task execution, command approval, RAG, MCP, Skills, and database reporting.
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·7 min
GPT-5.6 Full Model Lineup Hands-On Guide: A Deep Dive into API Relay Stations and Their Risks
The full GPT-5.6 model lineup is live. How can domestic developers access it at low cost via API relay stations? This article explains the principles, registration, token setup, client integration, and key risks.
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·4 min
Dify Getting Started: A Complete Guide to Building AI Workflows Without Code
A complete guide to Dify's core features and 1.8.0 deployment. Covers 5 app types, Docker setup, Workflow vs Chatflow differences, and RAG knowledge bases for beginners.
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·4 min
Tencent Open-Sources Agent Memory: A Fully Local AI Long-Term Memory Solution with Zero External Dependencies
Tencent Cloud open-sources TencentDB Agent Memory — a fully local AI Agent memory system with a 4-tier progressive pipeline, zero external API dependencies, and 8,100+ GitHub Stars. Ideal for finance, healthcare, and privacy-sensitive use cases.
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·6 min
OpenAI Releases GPT-5.6: Cybersecurity Capabilities Take Center Stage
OpenAI launches the GPT-5.6 model family with cybersecurity as its biggest highlight. A deep analysis of GPT-5.6's differentiation, double-edged-sword effect, and enterprise strategy.
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·4 min
Kun: An Open-Source AI Coding Agent Deeply Optimized for DeepSeek
Kun is an open-source AI coding agent optimized for DeepSeek and domestic users, with nearly 5,000 GitHub stars. Features include requirements drafting, inline diffs, cost visualization, and mobile monitoring. Real-world cache hit rates reached 97%, keeping costs extremely low.
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·6 min
AI's Second Half: The Decisive Battle Shifts from Models to Infrastructure
Model capabilities are converging, making inference cost and scalability the new focus of AI competition. A deep analysis of AI infrastructure's core layers.
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·4 min
9 Proven Methods to Make Hermes Agent Actually Work for You
9 battle-tested methods from hundreds of hours with Hermes Agent: model selection (Opus/ChatGPT/GLM), multi-agent failover, cross-device coordination via Tailscale, and reverse prompting workflows.
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·4 min
Why General-Purpose Agents Don't Work: How a Job Interview Reshaped One Developer's Thinking
An Agent developer's three-round interview reveals why general-purpose Agents are a dead end for startups. The path forward: vertical Agents, domain context, and iteration speed as a moat.
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