239 related articles

Learn LangChain Prompt templates and prompt engineering to build a customizable AI assistant like JARVIS. Covers LLM vs Chat Model differences with practical examples.
TutorialsLearn LangChain FewShotPromptTemplate: core parameters, implementations for text completion and chat models, and practical use cases like batch file renaming to reduce LLM hallucinations.
TutorialsA deep dive into LangChain prompt templates covering ChatPromptTemplate basics, Few-Shot prompting, and Chain-of-Thought techniques with RAG examples to build high-quality prompt pipelines.

An in-depth analysis of Mu, a toolset platform built for AI Agents, exploring the importance of Agent tooling, Mu's design philosophy, competitive landscape, and its value in AI deployment.

Developer builds ARYA, a voice AI assistant that controls real apps like WhatsApp and Spotify with vector memory. Deep dive into its technical implementation, AI Agent trends, and opportunities for builders.

In-depth analysis of enterprise LLM governance challenges, comparing real capabilities of Portkey, Orq.ai, LangSmith, Azure, and AWS Bedrock, revealing the critical divide between routing control and organizational governance.

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.

A detailed guide to LangChain Guardrails covering layered ecosystem architecture, middleware implementation, deterministic and model-driven protection for building production-grade secure AI Agents.

A systematic breakdown of the AI LLM learning roadmap covering prompt engineering, AI Agent development, RAG knowledge bases, model fine-tuning, and hands-on projects for beginners.

Deep dive into Spring AI framework's core features including provider-agnostic unified API abstraction, RAG retrieval-augmented generation, and structured output to help Java developers build enterprise AI apps.

Deep dive into Spring AI framework's core features including provider-agnostic unified API abstraction, RAG retrieval-augmented generation, and structured output to help Java developers build enterprise AI apps.

Choose the right AI Agent platform by evaluating model flexibility, observability, tool integration, security compliance, and total cost. A complete decision framework to help technical leaders avoid vendor lock-in.

Choose an AI Agent platform by evaluating model flexibility, observability, tool integration, security compliance, and total cost. A complete decision framework to avoid vendor lock-in.

SeaTicket is an AI Agent that automatically resolves GitHub Issues and Discord questions. This article analyzes its architecture, use cases, challenges, and value for open-source maintenance.

SeaTicket is an AI Agent that automatically resolves GitHub Issues and Discord questions. This article analyzes its architecture, use cases, challenges, and value for open-source maintenance.

A 6-week systematic learning path for frontend engineers transitioning to AI Agent development, covering core architecture, ReAct, multi-agent collaboration, RAG integration, and deployment.

Deep breakdown of 4 core AI Agent engineer competencies: business decomposition, multi-Agent architecture, quantitative evaluation, and engineering delivery—bridging the gap from Demo to production.

A detailed guide on building a full-process HR recruitment Workflow Agent with Spring AI Alibaba Graph, covering resume parsing, multi-dimensional screening, tiered questions, human-in-the-loop, and state rollback.

Agent Skills is a lightweight open-source format that extends AI agent capabilities with plug-and-play skill packages. This article dives deep into the Skills architecture, progressive disclosure, and how it differs from Multi-Agent design.

Agent Skills is a lightweight open-source format that extends AI agent capabilities via plug-and-play skill packages. Learn its architecture, progressive disclosure, and how it differs from Multi-Agent.