#context forgetting
238 related articles
·3 min
Long Documents Don't Work: Why AI Agents Can't Follow Your Rules
Analysis of why AI Agents can't reliably follow long policy documents, covering context dilution, rule conflicts, and soft constraint limitations, with more reliable governance architectures.
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·3 min
Kimi Delta Attention Explained: The Evolution from Standard Attention to Linear Attention
A deep dive into Kimi Delta Attention (KDA): tracing the evolution from quadratic Softmax attention through linear attention, Delta rules, and gated decay mechanisms, with insights on associative memory and hardware optimization.
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·3 min
Kimi Delta Attention Explained: The Evolution from Standard Attention to Linear Attention
Deep dive into Kimi Delta Attention (KDA): from standard Softmax attention's quadratic bottleneck through linear attention, Delta Rule, and gated decay mechanisms — the complete evolution explained.
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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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·4 min
Kimi K2/K3 Technical Speculation: Deep Dive into RL Hyperparameters and Multi-Teacher Distillation
Deep analysis of RL hyperparameter tuning challenges and 9-policy multi-teacher distillation in Kimi K2/K3 training, exploring the shift from scale to training craft.
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·2 min
Chrome Web Store Review Approval Guide: Dead Code Cleanup and Packaging Best Practices
Chrome Web Store submission rejected? Learn how to pass review by cleaning dead code, removing node_modules from builds, and ensuring compliance with store policies.
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·3 min
Deconstructing Agents: Task Decomposition, Context Compression, and the Case Against Heavy Frameworks
A deep engineering analysis of Agent internals: how LLMs decompose tasks via tool calling, why context compression and memory are essential, and why solo developers should avoid heavy frameworks.
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·4 min
Choosing the Wrong Agent Ruins Everything: Why the Same Model Can Perform Like Two Completely Different AIs
The same LLM API performs drastically differently under different Agent frameworks. Through a real database crash case, this article analyzes why choosing the right Agent matters more than switching models.
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·4 min
IntelliJ IDEA Efficiency Configuration Guide: Lessons from Seven Years of Java Development
A senior Java developer shares 7 years of IntelliJ IDEA configuration tips: JVM tuning, AI-assisted coding, Testcontainers testing, debugging tricks, and Spring toolchain setup.
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·5 min
Is the Self an Illusion? Neuroscience Reveals the True Nature of Identity
Emory neuroscientist Gregory Burns argues the self is a story the brain weaves. From the Ship of Theseus to memory confabulation, explore how identity is shaped by narrative and how we can rewrite it.
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·3 min
If Digital Computers Have Consciousness, It Exists Only at the Hardware Level — Not in Software
If digital computers can produce consciousness, does it reside in software algorithms or physical hardware? Exploring causal closure, substrate independence, and implications for AI consciousness.
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·4 min
Claude Code Tutorial: Environment Setup, Command Reference & Git Workflow in Practice
Complete guide to Claude Code covering CLI installation, domestic model switching, core commands, Git automation workflows, and automated code review and fix loops for enterprise projects.
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·5 min
From Chat to Agent: Automating Your Entire Business Workflow with AI Agents
Veteran AI practitioner Remy breaks down the leap from chat models to AI agents: how agents work, the three pillars of context, tools, and skills, MCP connections, and hands-on architecture to make you a 100x employee.
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·3 min
GLM 5.2 Hands-On: An Open-Source, Low-Cost Model That Rivals Opus
In-depth hands-on review of GLM 5.2: a 753B-parameter open-source model with a 1M-token context, rivaling Opus 4.8 at about one-tenth the price. Full setup guide for Claude Code and Cursor.
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·3 min
Hermes Agent in Practice: A Self-Evolving AI Agent Framework
Hermes Agent is a mature AI Agent framework with built-in Claude Code and Codex coding capabilities, supporting 200+ models, multi-platform deployment, and WeChat integration. Its layered memory and self-evolution features enable low-Token automated task execution.
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·3 min
Introduction to How AI Large Models Work: A Must-Read Guide for Test Engineers
A clear explanation of how AI large models work: from concept hierarchy and Transformer mechanics to probabilistic traits, helping test engineers grasp AI testing.
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·3 min
Introduction to AI Large Language Models: A Must-Read Guide for Test Engineers
A thorough explanation of the essence of AI large language models: from conceptual hierarchy and Transformer mechanics to probabilistic nature, helping test engineers understand LLM strengths and weaknesses.
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·3 min
The Vibe Coding Trap: You're Just Producing Garbage Faster
Vibe Coding lets non-coders build apps and websites fast with AI, but efficiency gains don't equal value gains. This article dissects the core trap and offers the right order: needs first, code later.
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·3 min
The Trap of Vibe Coding: You're Just Making Garbage Faster
Vibe Coding lets non-coders build apps and sites fast with AI, but faster isn't better. This piece dissects its core trap—building isn't succeeding—and offers the right "demand first, code later" order plus three questions to gauge a project's value.
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·3 min
In-Depth Analysis of Three AI Test Automation Approaches: Code Scripting, DOM Parsing, and Visual Models
A systematic breakdown of the three mainstream test automation approaches in the AI era: AI-generated code scripts, DOM parsing driven, and LVM visual model driven. In-depth comparison of principles, pros/cons, and use cases.
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