#LLM application engineer
2535 related articles
Product Reviews·3 min
DifyAIA: A Free Dify AI Workflow Template Library with 2500+ Stars
DifyAIA is a popular open-source Dify workflow template project on GitHub with 2500+ Stars. It offers free DSL workflow files for one-click import into Dify. Learn its features, usage, and use cases.
Read more →
Tech Frontiers·3 min
Gemma 4 + DGX Spark: How Open-Source LLMs and Desktop-Level Compute Are Changing AI Development
NVIDIA and Google DeepMind jointly showcase Gemma 4's vision translation, long-context Q&A, and real-time code generation on DGX Spark, signaling the convergence of open-source AI and edge compute.
Read more →
Tutorials·4 min
Building a Generative Recommendation System with Go and AI Agents: Architecture Design and Practical Analysis
Deep dive into a Go-based generative recommendation system powered by LLMs, covering three-level semantic understanding, three-layer user memory, and five-dimensional feedback design.
Read more →
Tutorials·3 min
NVIDIA Nemotron Labs Open Source Contribution Guide: A Complete Playbook for Developers Joining AI Open Source Projects
A comprehensive guide to contributing to NVIDIA Nemotron Labs open source projects, covering NeMo framework contributions, community participation, and career benefits for AI developers.
Read more →
Tech Frontiers·3 min
Inside the SJSU Hackathon Winning Projects: A Practical Guide to Building High-Impact AI Agents
Deep analysis of SJSU hackathon-winning AI Agent projects covering architecture design, core elements, and UX optimization—a practical guide from prototype to product.
Read more →
Tutorials·3 min
Deploying Gemma 4 on DGX Spark: A Complete Guide to Local AI Supercomputing + Open-Source LLMs
Deep dive into deploying Google Gemma 4 on NVIDIA DGX Spark. Covers hardware architecture, Gemma 4 highlights, local AI deployment benefits, and developer best practices for desktop-class AI supercomputing.
Read more →
Tutorials·3 min
Commercial AI Agent Development Guide: 7 Key Steps to Build from Scratch
A complete guide to building commercial AI Agents in 7 steps: requirements analysis, model selection, prompt engineering, Dify/Coze platform comparison, data storage, testing, and deployment.
Read more →
Expert Opinions·3 min
The Tyranny of Software Is Ending: AI Lets Everyone Build Apps
Programming barriers once divided the world into those who build software and those who merely use it. AI coding tools and LLMs are breaking down that wall, enabling anyone to create apps through natural language.
Read more →
Deep Dives·3 min
Claude Code Source Code Leak Revealed: Seven Core Mechanisms of the Harness Architecture Explained
Deep analysis of the Claude Code source code leak, revealing seven core mechanisms of its Harness architecture including context management, tool call orchestration, and state tracking for AI Agent developers.
Read more →
Expert Opinions·4 min
Interview with a Core Developer of Microsoft's Agent Framework: A Complete Analysis of Architecture Design and Evolution
In-depth interview with Microsoft Agent Framework core developer Roger Barreto on the evolution from Semantic Kernel, middleware architecture design, enterprise stability strategies, and AI development best practices.
Read more →
Tutorials·3 min
Andrew Ng's 2025 New Course: Core Methodology and Best Practices for Building AI Agents
A deep dive into Andrew Ng's latest Deeplearning.AI course on AI Agents, covering Agentic AI use cases, disciplined development workflows, evaluation frameworks, and error analysis methodology.
Read more →
Product Reviews·3 min
AI Voice Workshop + AI Audio Workshop: One Person Can Complete the Entire Production Pipeline for Radio Drama-Quality Audiobooks
AI Voice Workshop and AI Audio Workshop Studio Edition enable full-pipeline audiobook production through AI Agent architecture—from text analysis and character voice acting to post-production mixing.
Read more →
Deep Dives·3 min
Deep Dive into ByteDance's Hermes Agent Orange Book: A 198-Page Complete Guide to AI Agent Development
Deep dive into ByteDance's Hermes Agent Orange Book covering self-evolution loops, three-layer memory systems, Skill ecosystems, and multi-Agent collaboration — a complete 198-page technical guide.
Read more →
Tutorials·4 min
AI-Powered Research in Practice: From LLM Selection to Building Automated Workflows with N8N
A deep dive into AI-driven research methodology: LLM selection, Python automation, Zotero reference management, Overleaf writing, local LLM deployment, and N8N workflow automation.
Read more →
Deep Dives·4 min
From Copilot to Agentic AI: A Complete Guide to Multi-Agent Collaboration Architectures
Deep dive into AI's four-stage evolution from Chat to Agentic AI, covering multi-Agent architectures, ReAct framework, and MCP protocol for developers.
Read more →
Tutorials·3 min
Hands-On Testing OpenAI's Four New APIs: From GPT-4 Turbo to AI Agent Commercial Deployment
Hands-on testing of OpenAI's GPT-4 Turbo, DALL·E 3, Vision, and TTS APIs on AI2Apps, building an AI Agent that auto-generates novel covers from text.
Read more →
Tech Frontiers·2 min
Datasette Launches Official Blog: Simon Willison Built It from Scratch with OpenAI Codex
Datasette founder Simon Willison launches official blog built with OpenAI Codex Desktop, sharing full AI session transcripts and demonstrating transparent AI-assisted development practices.
Read more →
Tutorials·4 min
A Practical Guide for Java Developers Transitioning to AI Agent Development: Technology Selection, Architecture Design & Resume Positioning
A systematic guide for Java developers entering AI Agent development, covering core concepts, Workflow vs. Agent architecture comparison, Spring AI Alibaba selection, and resume positioning strategies.
Read more →
Tutorials·4 min
Agentic RAG Practical Guide: The Complete Evolution from Traditional RAG to Agent-Based Retrieval
Deep dive into Agentic RAG vs traditional RAG, with ChatPDF case study and LangChain code walkthrough covering tool design, multi-turn iteration, and autonomous decision-making for LLM engineers.
Read more →
Expert Opinions·2 min
The Abuse of the AI Agent Concept: Why "11 AI Agents" Is Meaningless
When companies claim "11 AI Agents," what does that number mean? This article dissects the vague definitions, quantity marketing, and Agent Washing plaguing the AI industry.
Read more →