#AutoGPT
335 related articles
Product Reviews·4 min
AI Agent Framework Selection in 2025: Pros and Cons of Coze, AutoGPT, LangChain, and AutoGen
2025 comparison of four major AI Agent frameworks: Coze for beginners, AutoGPT/LangChain/MetaGPT for developers, Microsoft AutoGen for enterprise self-hosted deployment. A practical selection guide.
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·3 min
The ISNAD Framework: Building a Trust Verification Layer for Multi-Agent AI Systems Using a Millennium-Old Scholarly Tradition
The ISNAD framework adapts Islamic chain-of-transmission verification to build a trust layer for multi-agent AI systems, focusing on claim verification over agent authentication to combat hallucinations and silent failures.
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·2 min
Can 45 Yes/No Questions Let an LLM Identify 16 Cards? An Information Theory Perspective on AI Reasoning
Analyzing whether LLMs can identify 16 cards through 45 yes/no questions from an information theory perspective. Exploring AI reasoning capabilities in constraint-based multi-turn tasks.
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·2 min
Google's Beyond Zero: An Enterprise Security Framework That Goes Beyond Zero Trust for the AI Era
Deep dive into Google's Beyond Zero security concept, exploring how enterprises can move beyond traditional Zero Trust models in the AI era to address prompt injection, data poisoning, and other emerging threats.
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·5 min
Loop Engineering Explained: The New Programming Paradigm Where AI Prompts Itself
Loop Engineering is a paradigm shift in AI usage. Learn how to build automated loops where agents explore, execute, and verify tasks autonomously, with a hands-on e-commerce case study.
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·5 min
Learn AI Agent Development from Scratch: A 3-Step Practical Path to Get Started Quickly
How to learn AI Agent development from scratch? This article outlines a clear 3-step path: Python crash course, LLM theory & practice, and LangChain framework project implementation.
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·3 min
How to Choose an AI Agent Platform for Your Team: 5 Evaluation Dimensions and a Decision Framework
Choose the right AI Agent platform by evaluating model flexibility, observability, tool integration, security compliance, and total cost. A complete decision framework to help technical leaders avoid vendor lock-in.
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·3 min
How to Choose an AI Agent Platform for Your Team: 5 Evaluation Dimensions & Decision Framework
Choose an AI Agent platform by evaluating model flexibility, observability, tool integration, security compliance, and total cost. A complete decision framework to avoid vendor lock-in.
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·4 min
WebMCP in Practice: How MakeMyTrip Is Reshaping the Travel Booking Experience
India's largest OTA platform MakeMyTrip uses WebMCP to standardize AI Agent interactions with web apps, replacing fragile DOM scraping with natural language-driven test automation and simplified complex booking scenarios.
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·4 min
WebMCP in Practice: How MakeMyTrip Is Reshaping the Travel Booking Experience
India's largest OTA platform MakeMyTrip uses WebMCP to standardize AI Agent interaction with web apps, solving DOM scraping fragility, enabling natural language test automation, and simplifying complex international flight bookings.
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·3 min
Using AI Agents to Write Research Experiment Logs: A Complete Methodology and Workflow
A detailed guide on using AI Agents to build Research Logs for scientific experiments, covering skeleton structure, daily workflows, pre-experiment thinking standards, code change tracking, and Agent-researcher division of labor.
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·3 min
Using AI Agents to Write Research Experiment Logs: A Complete Methodology and Workflow
Learn how to use AI Agents to build a Research Log for scientific experiments, covering structure, daily workflows, pre-experiment thinking, code change tracking, and human-AI division of labor.
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·3 min
From RAG to Agent Tuning: A Complete Guide to Deploying LLM Agents
A deep dive into LLM Agent frameworks covering RAG, Agent core components (tools, memory, planning), and Agent Tuning workflows with cost considerations for production deployment.
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·4 min
What Is the True Nature of Large Language Models? A Super Compressor Analogy to Help You Fully Understand
Large models aren't search engines — they're more like super compressors. This article explains how LLMs compress data to learn semantic patterns, and explores the phenomenon of intelligent emergence.
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·3 min
From Frontend to Agent Development: A Complete 6-Week Systematic Learning Path
A 6-week systematic learning path for frontend engineers transitioning to AI Agent development, covering core architecture, ReAct, multi-agent collaboration, RAG integration, and deployment.
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·5 min
Complete Breakdown of Core Competencies for AI Agent Engineers: From Demo to Production-Grade Systems
Deep breakdown of 4 core AI Agent engineer competencies: business decomposition, multi-Agent architecture, quantitative evaluation, and engineering delivery—bridging the gap from Demo to production.
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·4 min
What Is the True Nature of Large Language Models? A Super Compressor Analogy That Makes Everything Click
LLMs aren't search engines — they're more like super compressors. This article explains how large models compress corpora to learn semantic patterns, and explores the principles and limitations of emergent intelligence.
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·2 min
ag-kit: A Deep Dive into the TypeScript-Based AI Agent Development Toolkit
An in-depth analysis of ag-kit, a TypeScript-based AI Agent development toolkit covering core architecture, modular design, use cases, and tech selection advice for full-stack developers.
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·3 min
Simplified Technical English (STE): A Cross-Disciplinary Approach to Optimizing LLM Prompts
Explore how ASD-STE100 Simplified Technical English from aviation can be applied to LLM prompt engineering. STE's disambiguation principles—controlled vocabulary, short sentences, active voice—can improve LLM output accuracy and consistency.
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·4 min
The More Complex the AI Agent, the More It Hallucinates? The Hidden Cost of Architectural Complexity
Why do AI Agents hallucinate more as they grow more complex? This article analyzes the causes from error accumulation, context noise, and model completion nature, with 5 practical production strategies.
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