399 related articles

Build a production AI voice agent with Claude Code + Telnyx single-stack — no code needed, live phone number in 5 minutes. Covers 5 business scenarios including appointment booking, lead qualification, and support triage.

Model performance gaps are closing. Real competitive advantage lies in portable AI agent architecture. Learn how to build a workspace that works across Claude Code, Codex, and beyond — no vendor lock-in.

A comprehensive guide to AI-native application architecture: LLM inference, RAG retrieval (vector DB/knowledge graph/BM25), Agents, MCP tool calling, AI gateways, and observability — end-to-end.

Andrew Ng's DeepLearning.ai teams up with Anthropic to teach Agent Skills: file structure, progressive disclosure, MCP integration, and the full path from Claude.ai to the Agent SDK.

Pi is a minimalist open-source Agent framework with just 4 default tools and under 1,000 tokens in its system prompt, with 70K GitHub stars. Deep dive into its 4 core advantages vs. Claude Code and Codex.

OpenSpiel 2.0 by Google DeepMind adds LLM fine-tuning examples, MCP tool server, JSON trajectories, AlphaZero on JAX, 19 new games, and Windows support.

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.

OpenCode is an open-source terminal coding agent with 180K+ GitHub stars, supporting hundreds of models and a dual-layer agent architecture — completely free. See how it compares to Claude Code.

A comprehensive guide to Coze by ByteDance: multi-agent collaboration, local tool integration, cross-platform sync, and credit system. Compare with Dify to get started fast.

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.

A deep dive into LangGraph multi-agent architecture — covering hierarchical, network, and pipeline patterns with three hands-on projects using LangGraph 0.3.
BAML: A Type-Safe Programming Language…
BAML is a domain-specific language for AI Agent development that uses a type system to solve unreliable LLM structured output and unmaintainable prompts.

Why do AI results vary so dramatically? LangChain V1.3 reveals the answer: engineering mindset. Covers LangGraph, Deep Agent, RAG, Time Travel, and more.
Anthropic Open-Sources CWC Workshops: …
Anthropic open-sources cwc-workshops on GitHub — a TypeScript-based, structured workshop covering Prompt design, Tool Use, and Agent orchestration to help developers master Claude integration.

Learn LangChain 1.3 core concepts including LLM model abstraction, RAG retrieval-augmented generation, and Agent orchestration. Build a Deep Agent with planners, tools, and reflection modules.

A clear breakdown of the four core AI Agent concepts: Function Calling, Tool, MCP, and Skill — understand the full tech stack behind intelligent agent development.

New to AI Agents? This guide breaks down the full learning path — covering Agent principles, Prompt Engineering, RAG, multi-Agent systems, and hands-on projects to get you building fast.

Meta Muse Spark 1.1 deep dive: native multimodal architecture, platform tools, social data retrieval, e-commerce vision — Meta's first closed-source API model benchmarks against Anthropic Sonnet.

No coding needed: master Claude Code workflows with folder structure, sub-agents, third-party connectors, and scheduled routines to build your own AI automation OS.

A structured AI Agent learning path covering core principles, prompt engineering, tool use, multi-agent systems, and frameworks like LangChain, CrewAI, and Dify for enterprise deployment.