#agent development
140 related articles
Tutorials·3 min
Complete Learning Roadmap for Java Developers Transitioning to AI Engineering
A detailed five-phase learning roadmap for Java developers transitioning to AI engineering, covering Spring AI, LangChain4j, RAG core technology, and Agent development.
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Tutorials·3 min
Andrew Ng's Agent AI Course Fully Explained: Why It's Taking the Tech World by Storm
Deep dive into why Andrew Ng's Agent AI course went viral, covering the five-module agent architecture breakdown, course highlights, target audience, and learning tips for developers.
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Expert Opinions·3 min
The Salary Ceiling for Agent Engineers: Two Critical Dividing Lines
Agent engineer salary gaps hinge on two dividing lines: real production deployment experience and depth of foundational theory including deep learning, fine-tuning, and reinforcement learning.
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Product Reviews·3 min
9 AI Search Tools Compared: Choosing the Right Search Solution for Your Agent
Hands-on comparison of 9 AI search tools including Tavily, Exa, XCrawl, and Firecrawl across search accuracy, web crawling, SERP aggregation, and special features to help developers choose the right search solution for AI Agents.
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Deep Dives·4 min
AI Agents 101: Core Concepts, Technical Architecture, and How They Work
A beginner's guide to AI Agents: understand core concepts, the perception-decision-action loop, LLM, tool calling, memory systems, and RAG architecture explained from scratch.
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Industry Insights·3 min
Decoding Claude's New Policy: Dedicated Monthly Quota Is Actually a Massive Cut to AFK Use Cases
Deep analysis of Anthropic's new Claude subscription policy: dedicated programmatic access quotas appear beneficial but actually slash AFK automation workflow capacity by up to 96%.
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Tutorials·3 min
Andrew Ng's New Course: A Complete Guide to Building Database Agents
Deep dive into Andrew Ng's Building Your Own Database Agent course with Microsoft, covering LLM-SQL interaction, LangChain Agents, Function Calling, and RAG for tabular data.
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Tutorials·3 min
Hermes Agent Framework Practical Guide: Building AI Agents from Scratch
A detailed guide on ByteDance's Hermes Agent framework covering core features, deployment, custom tool development, and enterprise-grade AI Agent applications.
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Tutorials·3 min
LangChain Unified Interface in Practice: A Guide to Avoiding Model Invocation Pitfalls
A detailed comparison of LangChain's two model invocation approaches, focusing on init_chat_model unified interface usage and tips for avoiding DeepSeek V4 Pro Thinking Mode pitfalls in Agent scenarios.
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Industry Insights·3 min
Deep Dive into LangChain's Full-Lifecycle Toolchain for Agent Development
LangChain unveils a full-lifecycle toolchain for Agent development at Interrupt, covering Deep Agents 0.6, SmithDB, Context Hub, LLM Gateway, and LangSmith Engine.
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Product Reviews·4 min
OpenHuman Deep Dive: A Context-First Open-Source Personal AI Agent
Deep dive into OpenHuman open-source AI Agent: context-first architecture, Rust+React hybrid, Memory Tree system, Token Juice compression, and multi-model routing.
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Industry Insights·2 min
Two Major Career Paths in AI Large Language Models: Engineering Implementation vs. Algorithm Research
In-depth analysis of two core AI LLM career paths: engineering implementation vs. algorithm research. Compare education requirements, skills, and job prospects for programmers transitioning to AI.
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Industry Insights·4 min
Google I/O 2026 Deep Dive: From Super Apps to the Battle for Ecosystem Dominance
Deep analysis of Google I/O 2026: Gemini 3.5 Flash, Omni video tools, Spark personal Agent, and how Google, OpenAI, and Anthropic are competing for AI ecosystem dominance.
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Tutorials·3 min
Can You Really Transition to AI/LLM in Three Months? A Deep Dive into the Learning Roadmap
Deep dive into a popular 3-month AI/LLM transition roadmap: from Python basics and Prompt engineering to LangChain, RAG, Agents, and hands-on projects, with realistic time estimates and pitfall warnings.
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Tutorials
Is Context Engineering the Core of Age…
·2 min
Is Context Engineering the Core of Agent Development? A Deep Dive into a High-Frequency Interview Question
Deep dive into a top LLM interview question: Is context engineering the core of Agent development? Covers five context modules, four pain points, and advanced solutions.
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Tech Frontiers·2 min
LFM2.5-8B-A1B: A MoE Model with 1.5B Active Parameters Delivering 4x Its Weight Class Performance
Liquid AI releases LFM2.5-8B-A1B, a MoE model with 8B total params but only 1.5B active, matching 6B-class models in tool calling. Supports 128K context, local deployment, multilingual, with SGLang Day-0 support.
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Tech Frontiers·1 min
SGLang Hosts Agent Loops Office Hour, Focusing on Agentic Loop Architecture Optimization
SGLang team hosts an Agent Loops Office Hour exploring inference optimization for agentic loops, covering KV Cache reuse, low-latency multi-turn dialogue, and tool calling techniques.
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Tutorials
Claude Code Source Code Study Guide: E…
·3 min
Claude Code Source Code Study Guide: Efficiently Mastering Core AI Agent Development Architecture
Learn AI Agent development from Claude Code's 510K lines of source code, covering Agent Loop, context compression, multi-Agent orchestration, and two efficient study methods.
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Tutorials
Spring AI Agent Utils: A Java Agent To…
·3 min
Spring AI Agent Utils: A Java Agent Toolkit Reverse-Engineered from Claude Code's Core Features
Deep dive into Spring AI Agent Utils toolkit covering Skill modules, Ask a User Question, To Do Write, Auto Memory, and multi-Agent orchestration — empowering Java developers to build powerful AI Agents.
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Tutorials
Harness Engineering Deep Dive: Multi-L…
·2 min
Harness Engineering Deep Dive: Multi-Level Memory and Multi-Agent Collaborative Development in Practice
Deep dive into Harness Engineering: deconstructing Claude Code's multi-level memory, defense-in-depth, Hermes Agent autonomous evolution, and multi-Agent collaboration for industrial-grade AI development.
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