#LLM stateless
248 related articles
·6 min
Spec-Driven Development in Practice: The New AI Coding Paradigm from Andrew Ng × JetBrains
Andrew Ng partners with JetBrains to launch a Spec-Driven Development course, teaching how to direct AI coding agents via spec files to boost intent fidelity and build maintainable production apps.
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·4 min
TomoAI vs Daimon: An In-Depth AI Companion Comparison — Which One Is Worth Sticking With?
An in-depth comparison of AI companion apps TomoAI and Daimon: conversation experience, long-term memory, cross-platform support, and pricing to help you find the right AI companion.
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·3 min
GPT-5.6 Sol in Action: A 3D Interactive London Website Generated in 5 Minutes
A Reddit user tested GPT-5.6 Sol with a single prompt. In the Row-Bot framework, the model built a 3D interactive London website in 5 minutes—complete with browser verification and vision analysis. A deep dive into AI coding Agents.
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·5 min
ChatGPT Work Officially Launches: How GPT-5.6 Is Reshaping the Way You Work
OpenAI launches the GPT-5.6 model family (Sol/Terra/Luna) and ChatGPT Work, enabling automated financial analysis, local file operations, Codex coding, and cross-app workflows—AI officially becomes a real work partner.
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·4 min
100,000 Lines of Code in 7 Days: A Solo Developer's Hands-On Guide to AI-Assisted iOS Development
A solo developer iterated an iOS app to 100,000 lines of code in 7 days and shipped it. This article breaks down the core methodology: delegate the frontend to AI, control the backend by hand.
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·5 min
AI Agent Custom Tool Development Guide: Boost Efficiency by One-Click Reuse of Repetitive Tasks
An in-depth guide on developing Custom Tools for AI agents, compressing repetitive tasks like Excel-to-Markdown conversion from 30 minutes to under 5 seconds. Covers AGENTS.md registration, tool directory setup, and AI-assisted development.
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·4 min
Four Major LangChain Updates: OpenWiki, Voice Agents, and Sub-Agent Orchestration Explained
LangChain releases four major updates: OpenWiki for auto-generating codebase docs, voice agent tutorials, Harbor evaluation integration, and deepagents programmable sub-agents.
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·6 min
Andrew Ng × Anthropic: A Hands-On Claude Code Tutorial and Core Methodology
Andrew Ng partners with Anthropic to launch a hands-on Claude Code course, revealing its simple architecture, local security edge, and core context methodology across three cases: RAG chatbot, Jupyter analysis, and Figma-to-frontend.
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·4 min
AI Persistent Memory Three-Layer Architecture Explained: In-Depth Comparison of Mem0, Zep, and ContextNest
Deep dive into the three-layer architecture of AI persistent memory systems—storage, management, and retrieval—with an in-depth comparison of Mem0, Zep, and ContextNest to help developers choose the right memory solution for AI Agents.
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·5 min
Getting Started with LangChain: LLM Invocation, Agent Practice, and Environment Setup Guide
Starting from the three limitations of LLMs, this guide systematically explains LangChain's core positioning, environment setup, API key prep, model init, and the message system. Learn init_chat_model and AIMessage/HumanMessage/SystemMessage.
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·4 min
Tencent Open-Sources Agent Memory: A Fully Local AI Long-Term Memory Solution with Zero External Dependencies
Tencent Cloud open-sources TencentDB Agent Memory — a fully local AI Agent memory system with a 4-tier progressive pipeline, zero external API dependencies, and 8,100+ GitHub Stars. Ideal for finance, healthcare, and privacy-sensitive use cases.
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·6 min
Connecting SQL Projects to Azure DevOps Pipelines: A Hands-On Guide to Automated Builds and Secure Deployment
Learn how to connect SSMS SQL projects to an Azure DevOps CI/CD pipeline—covering YAML build config, SQL code quality analysis, managed identity authentication, and dynamic firewall rules for secure Azure SQL deployment.
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·5 min
MemoryOps AI: Building a Governable, Auditable Memory Layer for AI Assistants
MemoryOps AI is an open-source governed memory runtime that gives AI assistants policy-before-storage validation, context admission, and deletion-proof lineage—solving compliance, multi-tenancy, and deletion verification challenges in LLM memory systems.
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·6 min
Vibe Coding in Practice at Big Tech: How Frontend Engineers Can Avoid Being Replaced in the AI Era
A big-tech interviewer reveals: junior/mid frontend dev is being replaced by AI. This article breaks down 3 core Vibe Coding interview questions to help you master key skills for the AI-assisted coding era.
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·4 min
Proactive AI Agent Monitoring: Stop Fighting Fires, Catch Bugs Before Your Customers Do
A real case study: team builds AI Agent "Oogway" to auto-patrol after every job, investigate anomalies, create tickets, and update a knowledge Wiki — catching bugs before customers do.
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·5 min
Agentic MapReduce: The Key Architecture for AI Agents to Achieve Distributed Reasoning Across Entire Codebases
Cognition's Agentic MapReduce architecture combines classic distributed computing with autonomous agents to break LLM context window limits, enabling multi-Agent parallel reasoning across entire codebases.
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·4 min
OpenWiki: A CLI Tool That Automatically Generates AI Agent Documentation for Codebases
OpenWiki is an open-source CLI tool that automatically generates and maintains structured documentation for AI agents. It addresses the context gap in AI coding assistants like Claude Code and Cursor, helping teams build effective context engineering workflows.
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·6 min
Databricks Agent Framework in Practice: A Guide to ChatAgent Wrapping and Production Deployment
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.
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·7 min
ManagedAgents.sh: A Deep Dive into the Model-Agnostic Open-Source Managed Agent Platform
ManagedAgents.sh is a model-agnostic managed agent platform from OpenComputer, supporting Claude, Pi, and Codex runtimes with Slack and GitHub integration.
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·6 min
A Three-Month AI Agent Learning Roadmap: From Zero to Hands-On Agent Development
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.
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