#Meta vs OpenAI
473 related articles
·7 min
From Chat to Agent Platform: A Practical Guide to Engineering AI Applications
A deep dive into engineering AI applications: from a simple chat page to a multi-layer Agent platform, covering RAG knowledge bases, Workflow scheduling, multi-model management, and run tracing.
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·4 min
Vibe Coding vs. AI-Assisted Engineering: An In-Depth Look at Enterprise-Level Development
Can AI coding tools let non-developers replace programmers? This deep dive examines Vibe Coding's real limits, compares Claude Code vs. Codex, and reveals the methodology behind enterprise-grade AI-assisted software engineering.
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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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·2 min
Dify + RAG in Practice: Building a Game-Specific AI Assistant from Scratch
Build a RAG knowledge base from scratch using Dify's low-code platform. A hands-on Delta Force game assistant case study covering agents, knowledge base setup, and private deployment.
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·2 min
3-Month Roadmap to Becoming an AI/LLM Engineer: A Systematic Learning Guide
A 3-month structured roadmap for developers transitioning into AI/LLM engineering: Python & API basics, LangChain/FastAPI stack, and RAG/Agent projects.
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·3 min
Enterprise RAG Knowledge Isolation in Practice: Physical Isolation vs. Adaptive Soft Boundaries
A deep dive into two enterprise RAG knowledge isolation strategies: physical isolation vs. adaptive soft boundaries — covering metadata tagging, dynamic user-profile filtering, hybrid retrieval architecture, and data quality best practices.
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·2 min
AI Model Performance vs. Cost: What Does Top-Tier Intelligence Actually Cost?
A deep dive into performance scores and inference costs of 15 top AI models using the Artificial Analysis Intelligence Index — helping developers and enterprises build a cost-performance framework.
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·2 min
Daedalus: A Deep Dive into the Ollama-Based Local AI Engineering Runtime
Daedalus is an open-source local AI engineering runtime built on Ollama, covering architecture, debugging, and security. Zero token costs, full privacy, integrates with Claude Code and OpenCode.
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·2 min
Vibe Coding vs AI Engineering: A Practical Enterprise-Level Comparison Guide
A deep dive comparing Vibe Coding vs AI Engineering, with hands-on analysis of Claude Code and Codex, two real projects, and the role of Skills in enterprise AI development.
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·3 min
DeepSeek and Zhipu Race to Build Custom AI Chips: China's Path to AI Compute Independence
DeepSeek seeks $7B for custom AI inference chips; Zhipu AI explores ASIC. Deep dive into China's AI compute independence strategy, multimodal generation, agents, and hardware trends.
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·2 min
On-Device LLMs, Custom Silicon, and 100K-GPU Clusters: AI Industry Enters Full-Spectrum Competition
Apple's 1-bit compression fits 27B models on iPhone, Meta builds custom chip Iris, China's 100K-GPU cluster goes live, Samsung enters AI PC — a deep dive into AI's new full-spectrum competition.
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·4 min
GPT-5.6 & OpenAI Super App Deep Dive: Loop Engineering as the New Paradigm Replacing Prompt Engineering
Deep dive into GPT-5.6 (Sol/Terra/Luna) and OpenAI's Super App: Loop Engineering, Parallel Agents, and Computer Use — unpacking the shift from prompt to loop engineering with real test cases and a startup framework.
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·5 min
AI Coding Getting Worse With Every Edit? Skills v1.1 Reveals the Real Cause and Solution
AI code getting messier with edits? The root cause isn't weak model capability but a lack of context and process. A deep dive into Matt Pocock's Skills v1.1: grilling, vertical-slice tickets, TDD, and WebFinder.
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AI: Bubble or Revolution? A Deep Dive …
·3 min
AI: Bubble or Revolution? A Deep Dive into Speculative Growth
Is the AI boom a speculative bubble or a real revolution? This analysis examines speculative growth economics, compares optimist and pessimist views, and draws lessons from railway and dot-com history.
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·2 min
AI Agent Development Roadmap: A Four-Stage Guide from Zero to Production
A four-stage AI Agent development roadmap: from core theory and ReAct paradigm to multi-agent collaboration and production deployment. Covers DeepSeek, Coze, Dify, and more.
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·4 min
OpenAI's 5% Equity Offer for Political Cover: Rescue Mission or High-Stakes Business Gamble?
OpenAI offers Trump's government a 5% stake for regulatory relief. We analyze the financial black hole, regulatory capture risks, and nationalization undercurrents behind this high-stakes equity gamble.
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·2 min
GPT-5.6 Soul In-Depth Review: Can Multi-Agent Programming Mode Reshape the AI Development Tools Landscape?
GPT-5.6 Soul review: Super Mode hits 91.9% on TerminalBench. We break down multi-agent scheduling, benchmark controversies, and real-world dev tool comparisons.
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·5 min
A Deep Dive into Vector Search for AI Agents: The Technical Foundations of RAG and Long-Term Memory
An in-depth look at the core tech behind AI Agents: how the HNSW, IVF, and PQ vector search algorithms power RAG and long-term memory. Understand where a model's "memory" and "knowledge" come from.
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·2 min
DecisionRL: An Open-Source Reinforcement Learning Library Built for Operational Decision-Making
DecisionRL is an open-source RL library for operational decision-making, with six built-in scenarios (inventory, pricing, energy), OR baselines, and support for DQN, PPO, SAC, and more.
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The AI Whale Fall: How Big Players' Tr…
·2 min
The AI Whale Fall: How Big Players' Training Costs Nourish the Open Source Ecosystem
The "AI Whale Fall" reveals a hidden industry symbiosis: giants like OpenAI and Meta spend billions training models, and their open weights and research continuously nourish the open source ecosystem.
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