#Agent tooling
302 related articles
·2 min
LLM Thought Visualization: Making AI Reasoning Transparent and Interpretable
LLM thought visualization is emerging as a key breakthrough in AI explainability. This article explores the value, technical approaches, and challenges of visualizing Chain-of-Thought reasoning.
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·7 min
Connecting Hermes Agent to MCP: One Protocol to Unify All External Systems
Learn how to extend Hermes Agent's external system capabilities via MCP (Model Context Protocol): setup, whitelist permissions, WSL-to-Chrome bridging, and multi-server orchestration for AI Agent developers.
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·5 min
A Programmer's Guide to Large Language Models: The Complete Path from Prompts to Agents
A tailored large-model learning path for ordinary programmers: from prompt engineering, API calls, and LangChain, to RAG, Agents, fine-tuning, and enterprise deployment—six steps to build AI application skills fast.
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·3 min
Zhipu GLM-5.2 Officially Launches | Full Breakdown of Anthropic's U.S. Export Control
Zhipu GLM-5.2 launches with tiered thinking and long-context support, while Anthropic faces rare U.S. export controls over AI security vulnerabilities. Full breakdown.
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TaskPeace: An AI Coding Agent Task Que…
·2 min
TaskPeace: An AI Coding Agent Task Queue System Built on the MCP Protocol
TaskPeace is a task queue system for AI coding agents that uses the MCP protocol to let Claude, Cursor, and other AI assistants autonomously claim and execute tasks.
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·2 min
Sazabi Backed by The Agent Fund: AI Agent Space Enters a New Phase of Competition
The Agent Fund publicly backs AI startup Sazabi, reflecting the capital frenzy around AI Agents. A breakdown of the team, the fund, and the shift from conversational to autonomous AI.
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·3 min
Three Fatal Flaws of AI Script Writing — and How MCP Services Fix Them
AI script development plagued by amnesia, blindness, and repeat errors? This article examines how MCP service tools — history nodes, node preprocessing, and an error library — systematically fix AI programming's structural flaws.
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·3 min
AI + Python Reimagines Empirical Research: From Stata to Fully Automated Paper Generation
A PKU-Stanford trainer breaks down how Python surpasses Stata and R, how AI-driven Skills and Paper Workflow automate empirical research from data to LaTeX paper drafts.
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·3 min
Loop Engineering: The New Paradigm for AI Self-Evolution
Loop Engineering by Anthropic is a new AI paradigm using four components—Mutator, Executor, Evaluator, Selector—to build self-iterating closed loops. Learn the architecture, use cases, and how to get started.
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·3 min
Agentic AI in Practice: Core Principles, Engineering Challenges, and Practical Recommendations
A deep dive into Agentic AI: core components (planning, tool calling, memory), engineering challenges (reliability, cost, safety), and practical development recommendations for production deployment.
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·6 min
LangChain 1.0 Comprehensive Guide: Three Core Frameworks and Hands-On AI Application Development
Deep dive into LangChain 1.0's architecture: LangChain framework, LangGraph multi-Agent orchestration, and LangSmith observability platform, with hands-on RAG and intelligent customer service projects.
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Launch a Cloud Dev Environment in One …
·4 min
Launch a Cloud Dev Environment in One Prompt: A Deep Dive into the Codex DigitalOcean Plugin
OpenAI Codex's DigitalOcean plugin lets developers launch persistent cloud dev environments with a single natural language prompt. A deep dive into capabilities, use cases, and risks.
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GPT-5.5 and Codex: The Paradigm Shift …
·4 min
GPT-5.5 and Codex: The Paradigm Shift from Executor to Director in AI Programming
Deep analysis of an OpenAI interview: how GPT-5.5's multimodal creativity breaks new ground, and how Codex multi-agent workflows are reshaping software development — from executor to director.
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Beware of Big Tech AI Agents: How to P…
·2 min
Beware of Big Tech AI Agents: How to Protect Your Research Intellectual Property
Are your research code, algorithms, or unpublished papers safe with Big Tech AI agents? This deep dive explores data risks and offers practical protection strategies.
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·3 min
Herdr: A Terminal AI Agent Multiplexer Built with Rust
Herdr is an open-source Rust-written terminal tool positioning itself as an AI Agent multiplexer, unifying Claude Code, Cursor, and more in one CLI interface.
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·3 min
Meta Open-Sources Astryx: The First Design System Built for AI Agents
Meta open-sources Astryx on GitHub — an Agent Ready design system built for AI coding assistants. 5,600+ Stars and growing. Learn how it tackles AI hallucination in UI code generation.
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After Spending $85,000: Real-World Les…
·2 min
After Spending $85,000: Real-World Lessons and Cost Insights from Lovable's Agentic Coding Journey
Lovable spent $85K on API tokens scaling Agentic Coding. Key lessons: context management, model routing, circuit breakers, and ROI tracking for AI-driven development.
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Reviving Legacy SOAP APIs: Building a …
·2 min
Reviving Legacy SOAP APIs: Building a JSON and MCP Wrapper for Spain's Cadastre API
A developer built a modern JSON wrapper and MCP integration for Spain's 2003-era SOAP Cadastre API, enabling AI assistants to query land registry data directly.
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Software Factories Will Reshape Progra…
·2 min
Software Factories Will Reshape Programming Paradigms — A Deep Analysis from Warp's CEO
Warp CEO Zach Lloyd introduces the "software factory" concept: AI agents will take over repetitive coding tasks, shifting engineers from code executors to system architects.
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·2 min
Files as Memory: How to Finally Cure AI Coding Agents of Context Amnesia
AI coding agents suffering from context amnesia? The planning-with-files project uses Markdown file persistence to enable cross-session task continuity, compatible with 60+ tools including Claude Code and Cursor. 24K+ Stars.
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