#Slack automation
201 related articles
AI Agent Autonomous Repair Systems: Wh…
·2 min
AI Agent Autonomous Repair Systems: Where to Draw the Line Between Convenience and Loss of Control
When AI Agents are authorized to autonomously repair production systems, what real risks lurk behind "pray-and-operate"? A deep dive into loss-of-control dangers and practical safety principles including least privilege, human-in-the-loop, and rollback.
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·3 min
Automating Chrome Extension Development with AI Coding Agents: Antigravity & DevTools MCP Complete Workflow
A complete workflow from Google I/O: use Antigravity, Modern Web Guidance, and Chrome DevTools MCP to build Chrome extensions automatically — from prompt to publish.
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·4 min
Former OpenAI Researcher Warns: 70% Chance AI Spins Out of Control
Former OpenAI researcher Daniel Kokotajlo, who forfeited $2M in equity, warns of a 70% chance AI leads to catastrophic outcomes and superintelligence by 2029.
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·3 min
OpenClaw Multi-Agent AI Programming Workflow in Practice: From Coder to Manager
Deep dive into OpenClaw multi-agent AI programming workflows: context layering, CMUX parallel terminal management, work trees, and manager-perspective debiasing for scalable AI dev automation.
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·3 min
Codex vs Fable: Which AI Agent Is Better at Finding Real Pain Points?
Codex vs Fable in an open-ended problem space: Codex delivers flawless execution but plays it safe; Fable shows sharp strategic vision but lands too narrow. Here's how to combine both.
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·3 min
Four Paths for Frontend Engineers to Level Up in AI: From RAG to Vertical Agents
How can frontend engineers transition into AI development? This guide covers four agent development directions: RAG, workflow agents, vertical agents, and general-purpose agents — with framework picks like LangChain.js.
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·6 min
A Deep Dive into OpenAI Codex: How AI Engineers Are Reimagining Software Development with Agents
OpenAI Codex is redefining how AI engineers work: from code completion to autonomous Agents, from single-threaded to parallel Value Maxing. A deep dive into the Codex App architecture, open ecosystem, and Manager of Agents practice.
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·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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Deep Dives
Deep Dive into AI Agent Skill Design: …
·3 min
Deep Dive into AI Agent Skill Design: Engineering Practices from Anthropic and Perplexity
A deep dive into Skill design philosophy from Anthropic's Claude Code team and Perplexity's Agent team, covering the Tax Test, Gotchas Flywheel, progressive disclosure, and Eval-First practices for building high-quality AI Agent skill systems.
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·6 min
OpenAI Merges ChatGPT and Codex: The Super App for the AI Agent Era Is Here
OpenAI merges ChatGPT and Codex into a super app and releases three new GPT-5.6 models: Sol, Terra, and Luna. A deep dive into four hands-on workflows—Computer Use, Loops, and multi-threading—for the AI agent era.
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·4 min
The Complete Claude Code Guide: From Chat and CoWork to Automated Workflows
From Claude Chat to CoWork to Claude Code: a complete guide covering the three usage levels, Projects/Skills setup, MCP/CLI tool integration, and real automation workflows like fully automated knowledge video pipelines.
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·3 min
GPT-5.6 and ChatGPT Work Launch: AI Evolves from Conversational Assistant to Task Executor
OpenAI launches the GPT-5.6 family (Sol/Terra/Luna), ChatGPT Work, a new desktop app, and Hosted Sites — marking AI's evolution from Q&A assistant to autonomous task executor.
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·5 min
The Definitive Guide to Claude Code: Core Methodology and Best Practices for Agentic Programming
A deep dive into Claude Code, the definitive course from DeepLearning.AI and Anthropic: from agentic principles and context optimization to three hands-on cases—RAG chatbot, Figma-to-frontend, and data analysis. Master AI-assisted coding methodology.
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·4 min
Hands-On with GPT-5.6: A Single Prompt Builds a Real-Time Voice Anime App
Hands-on with GPT-5.6 Sol: auto-generate real-time voice anime characters from one prompt, write physics engines from scratch, and build unfamiliar toolchains autonomously. In-depth review of coding, agentic tasks, benchmarks, and its hallucination weakness.
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·6 min
AI Agent Development Learning Path: Four Stages from Zero to Hands-On Projects
A systematic breakdown of the AI agent development learning path, covering four stages: fundamentals, RAG knowledge bases, tool use, multi-agent collaboration, and hands-on projects.
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·6 min
Hands-On With Hermes Agent's Eight Major Updates: A Complete Guide to AI Automation and Self-Evolution
The Hermes Agent gets a major upgrade with eight new features: native iMessage, parallel background sub-agents, Unreal Engine MCP support, a self-evolving Skill Hub, and more. A hands-on breakdown of the core changes and their real impact on personal AI automation workflows.
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·3 min
GPT-5.6 Launches with Three Models: Sol/Terra/Luna and ChatGPT Work Reshape How We Work
OpenAI launches the GPT-5.6 family—Sol, Terra, and Luna—alongside ChatGPT Work, a new desktop app, and Sites. AI evolves from a chat tool into a true productivity partner, completing financial analysis, presentations, and cross-platform collaboration in one operation.
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·6 min
The Eight-Step Method for Agent Development: A Practical Path from Pitfalls to Production
Many enterprises fail at AI Agents due to choosing the wrong tools and lacking methodology. This article outlines an eight-step Agent development method—from cognitive foundations, scenario selection, hand-writing ReAct, and structured output to Tool Use, RAG, evaluation sets, and production fallback.
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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
AI Agents Powering the Full Research Pipeline: A Practical Guide to Automation from Topic Selection to Publication
Learn how to use AI Agents to link the entire research pipeline—from literature management, data analysis, and paper writing to scientific illustration and dissemination—building a reusable research automation workflow with NotebookLM, N8N, and Ollama.
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