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Glossary2
Open the full glossary- Workflow GraphA workflow graph uses nodes, edges, branches, and state to make the work route explicit; a node may be an agent, a tool, a check, or a human approval.
- Slash commandA short /command typed by the user that expands into a predefined workflow — triggered by a human, never selected by the model.
Found 16 articles
Multi-Agent Coordination: How Planners and Workers Avoid Fighting Each Other
Hand a task to several AI agents in parallel and three problems appear fast: duplicated work, information silos, and dependency mis-ordering. This article unpacks four design techniques from a public agentic system — role red lines, process-level information exchange, a shared todo list, and a single intent generator — and how they map onto any multi-agent workflow.
Smart Email Classification and Reply Template System
Drowning in email every day? This article teaches you how to use AI to classify incoming messages automatically, match the best reply template, and generate drafts for you to confirm and send quickly. The focus is on designing the 'confidence threshold' and the 'human review mechanism', so the system saves time without ever sending the wrong thing.
Multilingual Document Translation and Localization Workflow
Need to translate product docs, marketing materials or internal standards into multiple languages? This article shows how to build an end-to-end translation workflow with AI plus an automation platform, automating everything from content creation to multilingual publishing. The focus is on balancing AI translation speed against human proofreading quality.
The SEO Keyword Research and Content Optimization Pipeline
How do you build an automated SEO keyword research system — from discovering opportunities, analyzing competition, and generating content outlines to tracking rank changes? This article teaches you to build an end-to-end content optimization workflow that makes every article hit the search intent precisely. The focus is on a 'data-driven content strategy' rather than guesswork.
Automated Weekly-Report Generation System
Spending 3-4 hours every week collecting data, organizing progress and writing the report? This article shows how to use AI to pull data automatically from tools like Jira, Salesforce and Notion and generate a structured weekly-report draft, so you spend just 15 minutes confirming it and adding insight. The focus is on designing the balance between integrating data sources and adding human value.
Where AI Fits in the Research Process: What to Delegate and What to Keep
Breaks the investment research process into seven stages and judges one by one which can be handed to AI, which AI can only assist with, and which cannot be given up one step — with a ready-to-apply division-of-labor table and an implementation checklist that help you draw AI's capability boundary and responsibility boundary clearly.
Compliance Boundaries for Investment-Research AI: Disclaimers, Audit Trails and Traceability
When you put AI into an investment-research workflow, compliance is not one disclaimer line at the end of a report — it is a system-design problem: does the output constitute investment advice, are the data sources licensed, and can every conclusion be traced back to its inputs and prompt versions. This article gives a risk-dimension inventory, an audit-trail architecture, human-review checkpoint design, a question list to take to legal, and a route for strengthening internal policy.
Build Your First AI Workflow Without Writing Code
You can build a usable AI application with your own hands even if you cannot write code. Using a customer-support knowledge-base Q&A as the scenario and no-code platforms like Dify, Coze, and n8n, this article walks you through six steps — prepare the data, build the knowledge base, set the prompt, test, launch, monitor — each concrete enough to follow, without depending on interface details that go stale.
Your First Research Workflow: From Question to Traceable Conclusion
Starting from one vague research question, build a complete workflow that ends in a traceable conclusion: break it into verifiable sub-questions, assign independent sources to each, record findings on evidence cards, cross-verify, mark uncertainty, and finally produce a cited conclusion page.
The Marketing Content Mass-Production Pipeline: From Topic Selection to Finished Draft
Anyone can write one piece of content with AI; the hard part is stable mass production. This article breaks marketing content production into a pipeline: where topics come from, how to use a style guide as the system prompt to lock in style, how to derive versions for multiple platforms, where to place human review, how to troubleshoot unstable quality, and how to measure whether the line is really producing.
Automatically Turning Meeting Notes into Assigned Action Items
When a meeting ends and its action items sink without a trace, that is one of the most common hidden drains in an organization. This article breaks down the complete automation of record and transcribe → extract action items and owners → push assignments → auto-recap before the next meeting, focusing on how to design the human-confirmation step so the system saves effort and stays trustworthy even when extraction accuracy is imperfect.
A 30-Minute Quick Due Diligence Pass on One Company
A 30-minute quick due-diligence process you can follow as written: what to check in each of five phases, where to check it, what counts as a red flag, and what to record — closing with a one-page summary template. The goal is not an investment conclusion but judging whether a company deserves deep research.
Academic Research Skills Deep Technical Breakdown: How 45+ Agents Collaborate to Complete the Full Workflow from Literature Review to Peer Review
Complete technical analysis of the GitHub Trending #3 project Academic Research Skills: the architecture design of a 13-Agent research team, a 12-Agent paper writing pipeline, and a 7-Agent review panel, plus innovative mechanisms such as Socratic dialogue, integrity gates, and style calibration.
OpenClaw Creator and Infrastructure Automation: From Full Podcast Workflow to Self-Healing Servers
An in-depth breakdown of the creative tools in Awesome OpenClaw Use Cases (Podcast, YouTube, AI video editing, game development) and infrastructure DevOps solutions (self-healing servers, n8n orchestration), with complete workflow architecture diagrams.
OpenClaw Productivity Revolution: 22 Automation Solutions Reshaping Daily Workflows
From Personal CRM to Second Brain, from multi-channel customer service to autonomous project management, a deep dive into the 22 most practical productivity automation solutions in Awesome OpenClaw Use Cases, with architecture analysis and practical recommendations.
A Deep Dive into Search Channels: The Underlying Principles and Division of Labor Strategies of DuckDuckGo, Tavily, and Brave
A complete technical primer on three search channels: their respective indexing mechanisms, ranking algorithms, return formats, and cost models, plus how to divide work precisely within AI Agent workflows.