#peer instruction
116 related articles
Can LLMs Really Understand Computer Ar…
·3 min
Can LLMs Really Understand Computer Architecture Papers? A Deep Dive into Comprehension Capabilities
Can LLMs truly understand computer architecture papers? This article analyzes core challenges—from surface pattern matching to deep reasoning—and defines their capability limits for researchers.
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·2 min
LangGraph Multi-Agent Architecture in Practice: From Core Components to Production Deployment
A deep dive into LangGraph multi-agent architecture — covering hierarchical, network, and pipeline patterns with three hands-on projects using LangGraph 0.3.
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·4 min
AI Agents Automating JS Reverse Engineering: A Deep Dive into the New Paradigm for Web Scraping
AI agents are revolutionizing JS reverse engineering. This deep dive covers built-in tool chains, automation modes, prompt engineering for e-commerce, and full pipeline automation from parameter extraction to database storage.
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·3 min
AI Daily: Alibaba Open-Sources Dance Model, World Model Launches, First AI-Native Phone Debuts
Alibaba open-sources 14B dance model Wan-Dancer, AutoNavi launches World Studio, Stepfun debuts AI-native phone STEPS NEO; GPT-5.6 file deletion and AI companion shutdowns spark safety and regulation debates.
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GPT-5.6 Proves 50-Year Math Conjecture in One Hour — AI Independently Cracks a Scientific Problem
GPT-5.6 Sol Ultra proved the 50-year-old Cycle Double Cover Conjecture in one hour for under $500. Plus: Apple sues OpenAI, Google open-sources Gemma 4, and Zhipu AI targets AGI.
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·2 min
AI Cracks a 50-Year Graph Theory Conjecture in One Hour: The Art of Asking Questions Is Becoming the Core Skill of the AI Era
OpenAI's new model reportedly proved the Cycle Double Cover Conjecture in under an hour using 64 parallel sub-agents. The real lesson? In the AI era, knowing how to ask the right questions matters more than knowing how to calculate.
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·2 min
The Complete AI Agent Development Roadmap: A Four-Stage Guide from Zero to Production
A complete four-stage AI Agent development roadmap: from LLM fundamentals and core modules, to ReAct/CoT paradigms, multi-agent collaboration, and real-world projects.
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·2 min
Reinforce: A Developer's Open-Source Python Library for Reinforcement Learning — Lightweight and Readable
Developer Denis Drobyshev releases Reinforce, his first open-source RL Python library on GitHub. Learn about its value for beginners, common challenges in new open-source projects, and how to contribute.
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Loot Raiders: An Indie Dev Journey Bui…
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Loot Raiders: An Indie Dev Journey Building a Backpack Loot Web Game with Svelte
Loot Raiders is an ARC Raiders-inspired backpack loot web game built with Svelte. This article explores its gameplay design, Svelte's technical advantages for interaction-heavy games, and the indie dev journey from idea to launch.
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·3 min
The Complete Guide to OpenAI Codex: AI Agent Programming and Automation in Practice
A deep dive into OpenAI Codex: browser automation, Goal execution, plugins, Skills ecosystem, and coding power. Master 90% of Codex's features and transform your workflow.
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·5 min
Open-Source MCP Server: Automatically Verifying the Authenticity of AI-Generated Paper Citations
AI "citation hallucination" threatens academic integrity—LLMs generate perfectly formatted but nonexistent references. This open-source MCP server verifies AI citations in real time against CrossRef, PubMed, and more, catching fakes at the source.
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·2 min
AI Agent Learning Path: Mastering Intelligent Agent Development from 0 to 1
Many people learn tons of fragmented content yet remain confused. This article maps out the complete AI Agent knowledge landscape—from LLM and prompt basics, tool calling, and RAG to LangChain and multi-agent collaboration—with a clear learning order.
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·6 min
AI Agent Development Learning Path: Four Stages from Zero to Hands-On Projects
A systematic breakdown of the AI agent development learning path, covering four stages: fundamentals, RAG knowledge bases, tool use, multi-agent collaboration, and hands-on projects.
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·6 min
Airtel Gives Away Free Perplexity Pro: Will You Be Charged Automatically When It Expires?
Airtel partnered with Perplexity to offer users a free one-year Pro subscription, but the renewal charging mechanism worries many. This article breaks down the billing logic of operator-bundled subscriptions and offers practical self-protection tips.
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·4 min
Coze in Practice: A Complete Guide to Building Multi-Agent Collaboration Teams
A systematic guide to Coze's positioning and capabilities, covering Agent-building platform categories, Skill modules, workflow orchestration, and multi-Agent team building.
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·4 min
Getting Started with Coze: Build AI Agents from Scratch
Coze is ByteDance's low-code AI Bot platform for building AI agents without coding. Learn the differences between the domestic and international versions, core feature comparisons, and monetization potential.
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·4 min
AIML Capstone Project Selection: Is a Multi-Agent Debate System Worth Building?
Torn over your capstone topic? This article analyzes the academic value, feasibility, and innovation potential of a Multi-agent Debate system to help AIML students decide.
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·5 min
From Large Models to AI Agents: A Complete Analysis of the Four Evolutionary Stages and Four Major Commercial Tracks
Prompt engineering and RAG can no longer meet enterprise digital transformation needs—AI Agents are the key. This article breaks down the four evolutionary stages of large model deployment and the four major Agent commercial tracks.
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·6 min
Grok 4.5 Hands-On: A Faster, Cheaper Coding Dark Horse — Can It Replace Opus and GPT?
In-depth Grok 4.5 hands-on review: priced at a fraction of Opus 4.8, twice the token efficiency of peers, and coding ability in the top tier. A real-project breakdown of its strengths, highlights, and shortcomings.
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·8 min
GPT-5.6 Hands-On: Farm Automation, Mathematical Breakthroughs, and End-to-End AI Execution
GPT-5.6 (Sol, Terra, Luna) hands-on testing: a Hokkaido farmer controls a greenhouse with AI, a NYC small business builds custom software, and a Polish mathematician breaks a 3-year problem. A deep dive into end-to-end autonomous execution.
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