120 related articles

Master LangChain from scratch: the three limitations of LLMs, init_chat_model unified interface config, the Message type system, and the path from LLM calls to Agent development.

Anthropic's AI collaboration platform Claude Cowork officially expands to mobile and web, breaking free from desktop-only limits. Max subscribers get early access, with other plans rolling out over the coming weeks.

Frontend hiring now treats AI capabilities as a core assessment, covering RAG knowledge bases, AI Agent development, and LangChain.js engineering. Learn how LangChain.js + Nuxt.js helps frontend developers build memory- and retrieval-capable AI full-stack apps.

By capturing and analyzing ChatGPT's real network traffic during web retrieval, this article reveals the underlying logic of AI source selection—covering the layered mechanisms of retrieval recall and content filtering, domain preference patterns, and practical insights for content creators and SEO professionals.

The rise of Zhipu's GLM 5.2 is accelerating the democratization of LLM capabilities. This article analyzes the commoditization of foundation models, the logic behind margin collapse, and the opportunities and challenges facing application-layer and foundation model firms.

Deep dive into NVFP4 quantization: using NVIDIA Model Optimizer to compress Nemotron 3 Ultra to FP4 checkpoints, reducing memory by 75% and boosting inference throughput on Blackwell GPUs.

Deep dive into NVIDIA AI-Q Blueprint production deployment on Oracle Cloud Infrastructure, covering NIM microservices, RAG architecture, multi-agent orchestration, and OCI GPU selection for enterprise AI agents.

Deep dive into NVIDIA AI-Q Blueprint production deployment on Oracle Cloud Infrastructure, covering NIM microservices, RAG architecture, multi-agent orchestration, and OCI GPU selection.

AI workspaces face cross-tenant session and cache leak risks that can expose sensitive enterprise data. This article analyzes multi-tenant isolation pitfalls, common architectural flaws, and actionable defenses.

Manticore Search restructured its ONNX inference path to achieve 14x faster text embeddings. Deep dive into batching, session reuse, zero-copy memory, and thread tuning for vector search systems.
Smart Routing to Cut Claude Code Token…
Learn how smart routing reduces Claude Code token costs through tiered model scheduling, context compression, and request caching — a practical guide for developers and teams.

A detailed four-stage competency model for AI Agent development: from Python/RAG basics (15K) to workflow orchestration (20K), inference optimization (30K), and Agent cluster governance (40K RMB).

The core of enterprise AI isn't calling general models—it's building a self-reinforcing "model-harness-sandbox-eval" flywheel. This article analyzes the four components, tacit knowledge moats, and the "token value per watt" efficiency metric.

Hands-on comparison of GLM5.2 vs GPT5.5 frontend development: GLM5.2 edges ahead in page aesthetics but slow inference and limited API access remain major drawbacks.

Analysis of a 748-episode, 198-hour AI LLM development tutorial covering API integration, prompt engineering, RAG, AI Agents, fine-tuning, multimodal development, and deployment.

A systematic breakdown of the complete skill structure for AI application engineers, covering Python & deep learning fundamentals, small model engineering, LLM fine-tuning, Agent development, and enterprise projects.

From manual AI prompting to building automated loops — let Agents prompt, review, and merge code themselves. A real-world case: one message triggers four PRs auto-reviewed and merged overnight.

AI inference startup Baseten is raising $1.5B at a $130B valuation. We analyze why inference infrastructure is booming, the competitive landscape, and what this mega-round signals.

Cursor built Composer 2.5 on Kimi K2 open-source model, ranking 3rd on coding benchmarks and surpassing K2.6. Deep dive into Cursor's data flywheel, product architecture, and pricing.

Fireworks AI launches Qwen 3.7 Plus with latency/throughput optimization, zero data retention, and 99.9% SLA enterprise guarantees. Explore the full-stack deployment solution for commercial open-source model inference.