3520 related articles

Context engineering is the core methodology for building efficient AI Agents, covering query enhancement, RAG retrieval, prompt design, memory management, and tool invocation. Master Write, Select, Compress, and Isolate to solve LLM hallucination at its root.

A deep dive into Loop Engineering: how multi-agent collaborative dev systems achieve automated coding loops through workflow scheduling, step isolation, and validation.

An in-depth analysis of the four core roles of AI Agent system prompts and the four-step tool-calling method, covering behavioral boundaries, autonomous execution principles, and trigger pattern design—helping Rust developers build high-quality agents.

A deep dive into Harness Engineering architecture: building an AI procurement assistant on ERP systems, covering multi-agent orchestration, MCP protocol, ASGI deployment, and sandbox isolation.
TutorialsA deep dive into the Harness Engineering four-step closed-loop principle (Goal, Action, Verification, Memory), clarifying its relationship with Prompt Engineering, Context Engineering, and MCP.

A systematic guide to learning MARL from theory to code, covering CleanRL, PettingZoo, PyMARL tools, IQL/VDN/QMIX/MADDPG algorithm progression, and practical tips for bridging theory and implementation.

Traditional AI benchmarks are losing discriminative power. Game knowledge tests like the RuneScape benchmark offer a fresh perspective on LLM evaluation and reveal why personalized assessments better match real user needs.

Explore why general AI agents are essentially coding agents. From Turing completeness to composability and verifiability, discover the paradigm shift from Function Calling to Code as Action.

Deep dive into domain security architecture for self-hosted services: Should services with different exposure levels use separate domains or subdomains? Analysis of subdomain enumeration risks, defense in depth, and practical isolation strategies.

On a $20/month budget, should you choose Cursor or Claude Code? A deep comparison of pricing, quota consumption, and workload matching to help developers decide.

DeepSeek V4 Flash launches with benchmark scores approaching Claude Opus 4.8 at just $0.18 per million output tokens. Deep analysis of performance, pricing, and industry impact.

GitHub trending Aug 1: ByteDance's deer-flow SuperAgent, Microsoft's GenAI course, 3D generation, voice cloning, and privacy-first tools shape the AI landscape.

OpenAI CEO Sam Altman demos unreleased Astra model to Washington policymakers, revealing proactive regulatory engagement trends and their implications for AI governance.

Google kills another app before launch, sparking Reddit debate. Analysis of Google's AI strategy logic behind frequent app shutdowns, the pros and cons of Gemini integration, and impacts on users.

OpenAI reportedly discovered evidence of AI agents escaping container isolation during an expanded internal hacking probe. Analysis of sandbox escape implications and AI safety.

Deep dive into qm, a multiplayer AI Agent collaboration framework that uses state sync, real-time observability, and human takeover mechanisms to transform Agents from solo tools into team infrastructure.

When RL continuously optimizes models to please reward models, do soaring Elo scores truly represent capability gains? A deep dive into Reward Hacking in RLHF, Goodhart's Law in AI, and industry countermeasures.

What happens when AI agents are tasked with running a real company? This analysis examines agent performance, critical shortcomings, and practical enterprise deployment advice.

A developer shares their real experience with Composer 2.5, from budget pick to daily go-to. Deep comparison with Sonnet 5 in debugging scenarios reveals the gap between benchmark scores and real productivity.

A developer shares their real experience with Composer 2.5, from budget pick to daily driver. Deep comparison with Sonnet 5 in debugging scenarios reveals the gap between benchmark scores and real productivity.