#business connectors
78 related articles
·4 min
No-Code Guide to Claude Code: Building Your Personal AI Automation OS
No coding needed: master Claude Code workflows with folder structure, sub-agents, third-party connectors, and scheduled routines to build your own AI automation OS.
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·4 min
TigrimOSR: An Open-Source Agent Framework in Rust with Configurable Agent Loops
TigrimOSR is an open-source multi-agent system written in Rust, supporting full agent loop definition via YAML config files with only 250MB memory usage. A deep dive into Loop Engineering, Rust advantages, and self-hosted Agentic AI.
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·6 min
MCP Brings Power Apps Data Seamlessly into M365 Copilot: A Complete Implementation Guide
A Power Platform MVP demonstrates how to use MCP to securely expose Power Apps business data to M365 Copilot. Covers declarative agent creation, custom tool development, and VS Code setup.
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·3 min
Microsoft SQL Major Upgrade: AI Capabilities, Security Enhancements, and Fabric Integration — A Deep Dive
Microsoft SQL team's major updates: Azure SQL adds AI embeddings and dynamic data masking, Fabric SQL gets a Migration Assistant and Fabric Apps, SQL Server CU5 brings memory improvements, SSMS adds a SQL Formatter and Agent mode, and DP-800 certification is now open.
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·4 min
SparkyFitness: The Rise of an Open-Source, Self-Hosted Health Tracking App
SparkyFitness is an open-source, self-hosted alternative to MyFitnessPal and Flo. In one year: 4,500 users, 73 contributors, covering nutrition, sleep, women's health, GLP-1 tracking, and more.
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·4 min
Switching Careers to LLM Development: The Four Core Competency Layers Companies Actually Need
Want to break into LLM development but not sure where to start? This guide breaks the core skills into four progressive layers — from basic knowledge to RAG, fine-tuning, Agents, and multimodal — so you can align with real enterprise needs and land the job.
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·6 min
OpenAI's Head of Evals: We've Been Consistently Underestimating What AI Models Can Really Do
OpenAI Frontier Evals lead Tejal Patwardhan reveals AI models are systematically underestimated — reasoning breakthroughs, wet lab records, the internal AGI Index, and a progress curve far steeper than most realize.
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·3 min
The 7-Level Claude Code Mastery Guide: From Basic Chat to Autonomous AI Agents
From chat to autonomous agents: a 7-level Claude Code mastery guide covering model selection, effective prompting, tool integration, sub-agents, skills, safety, and autonomous operation.
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·6 min
Alibaba Bans Claude Code: The Enterprise Security Red Line for AI Coding Tools
In-depth analysis of Alibaba's comprehensive internal ban on Claude Code: from the hidden-marker controversy and Anthropic's regional-restriction stance to five core questions of enterprise AI coding tool security admission.
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·3 min
Dify 1.8 Deployment & Configuration Guide: Comparison with Coze, RagFlow, and N8N
Complete guide to Dify 1.8 deployment changes, five application types explained, and a detailed comparison with Coze, RagFlow, and N8N for enterprise AI platform selection.
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·4 min
The Four Stages of AI Engineering Evolution: From Prompt to Loop Engineering Explained
A systematic breakdown of the four stages of AI engineering: Prompt Engineering, Context Engineering, Runtime Environment Engineering, and Loop Engineering — with core logic, bottlenecks, and real-world use cases.
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·3 min
AI Large Language Model Learning Roadmap from Scratch: From Beginner to Enterprise-Level Practice
A systematic AI LLM learning roadmap from scratch, covering Python basics, Prompt Engineering, RAG, Agent development, and enterprise-level projects.
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·4 min
AI Large Language Model Career Transition Roadmap: A Three-Phase Learning Guide from Zero to Enterprise-Ready
A systematic three-phase AI LLM career transition roadmap: from Transformer fundamentals to RAG, Agent & LangChain development, to LoRA fine-tuning. Build enterprise-ready skills in two months.
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·3 min
Java Developer's Guide to AI: Hands-On with Spring AI and RAG
A practical guide for Java developers to build AI apps without switching languages — covering LLM APIs, prompt engineering, RAG, Spring AI, and Langchain4j.
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·3 min
Claude Code Routines Explained: Automation in Practice with Proactive AI Coding Agents
Deep dive into Claude Code Routines: build proactive AI coding agents with time-scheduled and event-driven triggers. Covers automated docs, deploy verification, and on-call investigation.
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·2 min
n8n from Beginner to Expert: A Complete Guide to Building AI Agent Workflows with Zero Code
Complete guide to n8n's AI capabilities covering AI Agent, Chain nodes, and Tool nodes. Learn to build enterprise-grade AI workflows with zero code, from setup to RAG systems.
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·4 min
The Complete Beginner's Guide to Claude Code: Build and Deploy Apps with Zero Programming Experience
A complete guide to Claude Code from setup to deployment, covering Plan Mode, MCP connectors, reusable skills, CLAUDE.md project memory, and Vercel deployment — no coding experience needed.
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·4 min
Spring AI vs LangChain4j: How to Choose a Java AI Framework
In-depth comparison of Spring AI and LangChain4j — two major Java AI frameworks — covering core features, completeness, ecosystem support, and usability to help Java developers make the right choice.
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·3 min
Enterprise-Grade RAG Full-Pipeline Optimization: Multi-Turn Conversations, Retrieval Tuning, and Production Engineering in Practice
A deep dive into full-pipeline optimization for enterprise RAG systems, covering multi-turn query rewriting, retrieval tuning, and quality evaluation to take RAG from demo to production.
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·3 min
OpenAI Codex Data Analytics Plugin in Practice: The Complete Workflow from Data Collection to Report Delivery
Deep dive into OpenAI Codex's Data Analytics Plugin: cross-system data integration, smart chart generation, data provenance, and Google Slides export reshaping analytics workflows.
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