AI Workflow Automation Glossary
Essential terms and definitions for understanding AI-powered workflow automation, file operations, and knowledge work optimization.
AI Agent
Autonomous software that executes tasks and makes decisions without constant human guidance. Unlike conversational AI that requires prompting for each step, AI agents can plan and complete multi-step workflows independently. In the context of Stash, AI agents autonomously edit files, manage workflows, and maintain persistent memory across sessions.
AI Agents vs Conversational AI →Autonomous Execution
The ability of AI to complete multi-step tasks independently without requiring constant prompting or supervision. Autonomous execution means the AI can break down complex requests into subtasks, execute them sequentially or in parallel, and handle errors without human intervention. This differs from traditional AI assistants that require step-by-step guidance.
Bulk File Operations
The capability to perform actions on multiple files simultaneously. Bulk operations enable users to edit, rename, restructure, or update content across hundreds of files at once. For example, updating all client presentations with new branding or standardizing formatting across an entire document library. As of 2025, Stash supports bulk operations on 200+ files simultaneously.
Learn About Bulk Editing →Cloud Integration
The connection between desktop or web applications and cloud storage services such as Google Drive, Microsoft OneDrive, and Dropbox. Cloud integration allows applications to read from and write to files stored in cloud accounts, enabling seamless workflows across multiple storage platforms without manual downloading or uploading.
Conversational AI
Artificial intelligence systems designed primarily for natural language dialogue and interaction. Conversational AI, such as ChatGPT or Claude, excels at answering questions, providing explanations, and generating content through text-based conversation. These systems typically require prompting for each task and do not directly manipulate files or execute workflows autonomously.
Stash vs ChatGPT Comparison →Desktop Application
Software installed and run locally on a user's computer rather than accessed through a web browser. Desktop applications often provide better performance, offline functionality, and enhanced privacy since data can remain on the user's device. Stash is a desktop application built for macOS and Windows.
File Operations
Actions performed on documents and files, including creating, reading, editing, moving, renaming, and deleting. In AI automation contexts, file operations refer to the AI's ability to directly manipulate files in their native formats (Word, Excel, PowerPoint, PDFs, etc.) rather than just generating content for manual copying.
Generative AI
Artificial intelligence systems that create new content such as text, images, code, or data based on learned patterns from training data. Generative AI models like GPT-4 and Claude can produce human-like text, answer questions, and generate code. When applied to workflow automation, generative AI can draft documents, write reports, and synthesize information from multiple sources.
Knowledge Work
Professional work that primarily involves creating, processing, analyzing, or applying information rather than manual labor. Knowledge workers include consultants, analysts, researchers, product managers, and executives. Their workflows typically involve extensive document creation, data analysis, and information synthesis—tasks that AI automation can significantly streamline.
Large Language Model (LLM)
A type of artificial intelligence trained on vast amounts of text data to understand and generate human language. LLMs like GPT-4, Claude, and Gemini can perform various language tasks including translation, summarization, question-answering, and code generation. Modern AI agents often use LLMs as their reasoning engine while adding capabilities like file manipulation and workflow execution.
MCP (Model Context Protocol)
An open protocol that enables AI applications to connect with external tools, data sources, and services. MCP allows developers to extend AI capabilities by adding custom integrations, such as connecting to databases, APIs, or specialized software. Stash uses MCP to enable users to build custom automations and integrate with their existing tools.
Open Source
Software with source code that is publicly available for anyone to inspect, modify, and distribute. Open source projects like Stash promote transparency, community collaboration, and freedom from vendor lock-in. Users can verify security, customize functionality, and contribute improvements. Open source software is typically free to use under licenses like MIT or Apache 2.0.
Persistent Memory
The ability of AI systems to retain information across multiple sessions and conversations. Unlike conversational AI that forgets context between chats, persistent memory enables AI to remember user preferences, project details, file locations, and conversation history over weeks or months. This eliminates the need to repeatedly re-explain context or re-upload files.
Learn About Stash's Memory →Version Control
A system that tracks changes to files over time and enables users to revert to previous versions. Version control maintains a complete history of modifications, showing who made changes and when. In AI automation contexts, version control provides safety when making bold changes—users can instantly rollback to earlier versions if needed. Stash includes built-in version control for all file operations.
Workflow Automation
The use of technology to execute recurring tasks or processes automatically without human intervention. Workflow automation can include scheduled actions (e.g., generating monthly reports), triggered responses (e.g., updating files when new data arrives), or AI-driven task completion (e.g., synthesizing research from multiple sources). Effective workflow automation saves time and reduces human error in repetitive processes.
Learn More About Stash
Ready to see how AI workflow automation works in practice?