169 related articles

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.

Cheap Cursor tools hide ban risks and privacy traps. Learn how client tampering and API relays create vulnerabilities, and how to identify trustworthy tools.

A systematic overview of the AI Agent tech stack: RAG retrieval, Agent planning, MCP protocol, AI Gateway, and observability — helping developers build production-grade AI systems.

Microsoft Power Platform's Dataverse plugin for coding agents supports GitHub Copilot, Claude Code, and more — enabling natural language data modeling, queries, security config, and docs generation.

Deep dive into langgraph-agent-stack: per-run dollar budget control, canary traffic routing, Mock testing mode, and 800+ test cases to safely deploy AI Agents from demo to production.

No coding required! This guide breaks down the complete Claude workflow: custom Projects, batch SEO content, one-sentence tool building with Artifacts, and Claude Code terminal ops—with real traffic-growth cases.

From SHRDLU to modern neuro-symbolic AI: explore procedural semantics, CCG grammars, semantic parsing, and interactive fiction engines in today's NLP landscape.

Microsoft Build deep dive: how to deploy AI agents in Teams multi-user collaboration. A three-pillar framework—Manners, Privacy, Polish—covering emoji reactions, targeted messages, Adaptive Cards, and more for enterprise agent developers.
Getting Legal AI Right: Why the Coding…
Most legal AI products are just general-purpose models wrapped in RAG and prompt engineering scaffolding. Learn why the coding agent paradigm fails in law and what real legal AI requires.

Master Codex AI programming assistant with this complete guide: CLI setup, slash commands, agents.md governance, MCP protocol, multi-agent systems, and enterprise plugin development.

Kimi K3, DeepSeek V4, Liquid, and Mistral are all dropping at once. MXFP4 quantization and MoE architecture are pushing the marginal cost of intelligence toward zero. Here's what it means.
AI Coding Agents Have Amnesia — An Ope…
Tired of AI coding agents forgetting everything? Explore an open-source SSH-synced memory system that lets Cursor, Claude Code, and other agents retain project context across sessions and devices — no cloud required.

Learn how local LLMs (Llama, Mistral, Qwen) and open-source toolchains protect your data sovereignty, reduce platform dependency, and give you full control over AI workflows.
Building RL-Powered Autonomous Researc…
How NVIDIA NeMo combines reinforcement learning to train agent skills and build an Autoresearch workflow capable of autonomously running ML experiments end-to-end.

A hands-on guide to deploying Dify 1.8.0, covering setup steps, Workflow vs. Chatflow differences, RAG knowledge base, and MCP support for AI app development.

AI code spiraling out of control? This article breaks down a three-layer engineering system — Prompt rules, Skill workflows, and Harness feedback loops — with real-world results showing pass rates rising from 70% to 98%.
Soofi Open-Source Foundation Model Tra…
Soofi is an open-source project providing complete foundation model training code, covering data preprocessing, tokenizer construction, model architecture, and training optimization. A deep dive into its value for the LLM ecosystem.

How does watermarking work — and why won't companies deploy it? How does differential privacy defend against membership inference attacks? Based on talks by IISc and IIT scholars, this article unpacks the core mechanisms and real challenges in LLM security.

When ChatGPT can answer directly, does retrieval still matter? Six experts from Microsoft, IIT Delhi debate parametric memory limits, BM25's endurance, and where retrieval ends and reasoning begins.

A deep dive into Chain of Thought (CoT) prompting: from prompt construction to reasoning chain generation, revealing the three mechanisms behind AI's improved reasoning. Covers math, medical, and financial use cases.