#model self-correction
168 related articles
·3 min
Kimi K3 Launch: A 2.8 Trillion Parameter Flagship Model Makes Its Grand Entrance
Moonshot AI launches Kimi K3 with 2.8 trillion parameters and 1M token context. Google delays Gemini 3.5 Pro, AI coding tools upgrade collectively as competition shifts to coding and Agent capabilities.
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·6 min
Harness Engineering: From Context Engineering to the Third Phase of AI Programming
Explore Harness Engineering: the next evolution beyond context engineering for AI programming. Learn how to build enterprise-grade Skill systems and deliver real projects with mid-tier models.
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·4 min
Laguna S 2.1 Deep Dive: Hands-On Local Deployment of a 118B Parameter Coding Model
In-depth review of Poolside's Laguna S 2.1 open-source coding model: MoE architecture, RL training, DGX Spark local deployment, and real-world agentic coding tests with 8B active parameters.
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·4 min
GPT-5.6 Value Maxing Practical Guide: From Token Stacking to Output Optimization Methodology
Deep dive into OpenAI GPT-5.6 Value Maxing strategies covering Sol/Terra/Luna model selection, KV cache optimization, Prompt compression, and programmatic tool calling to help developers achieve more output with fewer Tokens.
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·3 min
After 6 Billion Tokens, Here's What I've Learned About AI Agents
A power user who consumed over 6 billion Tokens shares real insights on AI Agents, exploring spending money, investing time, and managing life changes with AI.
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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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·2 min
GPT-5.6 Goes Live with Dual Quota Reset as AI Models Update Rapidly
GPT-5.6 fully launches with enhanced coding, computer operation, and long-horizon agent tasks, plus a dual quota reset. Meanwhile, ByteDance opens its C-Dance 2.5 API and Mistral debuts a single-RGB-camera natural language navigation model.
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·3 min
Zhipu's Mobile AI Agent Tested: A Full Breakdown of the Cloud Phone Approach — Capabilities and Limitations
Hands-on test of Zhipu's mobile AI Agent: using a cloud phone to bypass permission limits, it supports natural language-driven automation. We cover its core mechanics, real performance, app restrictions, and future potential.
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·5 min
From Vibe Coding to AI Engineering: A Complete Guide to Enterprise-Grade Development
In the AI programming era, Vibe Coding alone can only build toys. This article deeply analyzes the complete engineering path from Vibe Coding to SDD spec-driven development, covering Claude Code and Codex tool selection, the SuperPower plugin, and domestic LLM comparisons.
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·2 min
GPT-5.6 Three-Model Showdown: Sol vs Terra vs Luna — Which One Should You Pick?
OpenAI GPT-5.6 launches Sol, Terra, and Luna simultaneously. We compare benchmarks and real-world coding tests to help you choose the right model for your needs.
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·6 min
The Complete Guide to Using Claude in China: In-Depth Comparison of 4 Solutions and How to Choose
How can users in China use Claude? This article deeply compares four solutions: official subscription, proxy subscription (WildCard), relay platforms (2233/0011.ai), and API aggregation (OpenRouter).
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·7 min
The Complete Guide to LLM Application Engineer Interviews: Six High-Frequency Agent Topics
A focused guide to core LLM application engineer interview topics, covering agent architecture, Multi-Agent, Langfuse evaluation, security, and RAG optimization.
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·7 min
The Complete Guide to LLM Application Engineer Interviews: Six High-Frequency Topics in the Agent Domain
A focused guide to the core interview topics for LLM application engineers, covering agent architecture, Multi-Agent, Langfuse evaluation & tracing, security, and RAG optimization.
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·6 min
30-Minute Hands-On: Building a Working AI Agent from Scratch
Skip the dry theory and get hands-on! This article demonstrates step by step how to build a working AI Agent from scratch in 30 minutes using AI coding tools—covering the agent skeleton, tool system, memory mechanism, Flask web UI, and DeepSeek API integration.
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·3 min
LangChain v1.3 Hands-On Tutorial: Deep Dive into Agents, RAG, and Local Model Deployment
Deep dive into LangChain v1.3: compare LangChain, LangGraph, and DeepAgent paradigms, explore RAG pipelines, multi-agent systems, and local LLM deployment for enterprise AI apps.
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·6 min
Claude Sonnet 5 In-Depth Testing: 8 Real-World Tasks Reveal Its True Capability Boundaries
Bilibili creator KaterSony tests Claude Sonnet 5 across 8 real-world tasks—image recognition, 3D modeling, web generation—comparing it against GPT-5.5, Gemini 3.1 Pro, and revealing its true capability limits and cost traps.
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·5 min
DeepSeek V4 Enters Grayscale Testing, Grok 5.0 Ready to Launch | Latest AI Model Developments
This AI Daily covers five sectors: DeepSeek V4 reportedly enters grayscale testing with improved chain-of-thought; Musk previews Grok 4.6 and 5.0 with 2T parameters; Intern-S2 open-source model beats Claude Opus 4.8; xAI builds 2000MW Colossus cluster; NVIDIA RoboTTT breaks long-horizon robotics barriers.
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·2 min
OpenAI's New Voice Assistant Tested: It Interrupts, Simultaneous Interprets, and Gets Flustered
OpenAI's upgraded voice assistant can speak dialects, do real-time simultaneous interpretation, teach English, and even get flustered. Here's what changed.
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jcode Deep Dive: Why Rust Is the Ideal…
·3 min
jcode Deep Dive: Why Rust Is the Ideal Foundation for a Coding Agent Framework
jcode is an open-source Coding Agent framework built in Rust, gaining nearly 200 GitHub Stars in a day. Explore its architecture, Rust advantages, and application potential.
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·3 min
Building a Video Generation Agent: Lessons Learned from Brief to Storyboard
A developer's hands-on account of building a brief-to-storyboard video Agent: JSON errors, missing fields, pacing issues — and how JSON Schema, retry loops, and MCP tools solved them.
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