30 related articles
TutorialsLearn LangChain FewShotPromptTemplate: core parameters, implementations for text completion and chat models, and practical use cases like batch file renaming to reduce LLM hallucinations.
Product Reviews"It's Ready" is an AI hotpot timer mini app — just voice your order and it auto-generates countdown cards that turn green when each dish is perfectly cooked.

Nthly is a privacy-first iOS 2FA authenticator with fully local key storage, no account required, supporting TOTP and HOTP. A deep dive into its features and comparisons.

A detailed guide on GraphRAG vs. traditional RAG, building a knowledge graph from scratch with Neo4j and neo4j-graphrag, and wrapping it as a LangChain Agent tool for multi-hop reasoning.

Warpgate 0.27 adds transparent RDP/VNC proxy, OTP/SSO integration, cluster scaling, and TLS hot-reload. A FOSS alternative to Teleport requiring no agents or clients for unified privileged access.

A systematic guide to standardized datasets for RAG retrieval experiments, covering BEIR, MS MARCO, Natural Questions, and TREC benchmarks for dense, sparse, and hybrid retrieval evaluation.

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.

A deep dive into two frontier dense retrieval works: Hobbit uses gradient analysis to automatically construct hard batches; Disco replaces single-document competition with submodular collaborative coverage, reshaping Top-K retrieval.

Local LLM tool Ollama closes a $65M Series B, bringing total funding to $88M. With 9M developers and 85% of Fortune 500 having deployed internally, this deep dive explores why enterprises embrace local LLMs: compliance, Agent cost savings, and open-source ecosystem.

Learn LangChain Prompt templates and prompt engineering to build a customizable AI assistant like JARVIS. Covers LLM vs Chat Model differences with practical examples.

A deep dive into Databricks Agent Framework (Mosaic AI): unify LangGraph/OpenAI agents via ChatAgent, log & evaluate with MLflow, version with Unity Catalog, and deploy Model Serving Endpoints for production AI agents.

A systematic breakdown of the complete AI Agent learning roadmap, covering prompt engineering, the ReAct paradigm, memory mechanisms, and multi-agent collaboration, with hands-on project advice.

Exposing the phishing trap behind the "free Gemini Pro membership" tutorials circulating on video platforms: they lure users into handing over account passwords and backup recovery codes, leading to account theft. This article breaks down the process technically and teaches you to spot three danger signs.

A systematic four-stage roadmap for AI Agent development: fundamentals, core principles, enhancement, and real-world deployment. Build complete Agent skills.

A complete 6-week AI Agent learning roadmap covering core architecture (planning/memory/tool use), the ReAct paradigm, multi-agent collaboration, RAG integration, and production deployment.

What is an AI Agent? This article systematically explains the core architecture of AI agents (LLM + Planning + Memory + Tools), how they differ from ChatGPT, their combination with robots, and why developers must master Agent development skills.

By introducing an engineered verification loop reasoning framework, DeepSeek's effective pass rate on complex tasks can improve ~4x, matching Claude Opus at one-seventh the cost. A deep dive into verification loops, test-time compute scaling, and their practical implications.

Cut through the Agentic AI hype to see the real value of agentic applications. Based on Andrew Ng's course, learn why Evals and error analysis—not framework choice—separate top developers.

Step-by-step guide to installing Claude Code Desktop, enabling developer mode for account-free use, integrating DeepSeek via CC Switch, Chinese localization, and custom Skills in ten minutes.

A deep dive into Loop Engineering for AI Agents — what loop feedback mechanisms are, how they differ from Harness Engineering, and a complete guide from principles to production implementation.