GlossaryAgentsNew to AI

Artifacts

Also written: Artifacts feature, Artifacts tab, Manifest, Agentic artifacts, Production-ready assets, Analysis assets, Artifact limit, Attachments

Tangible outputs from AI agents, like documents, code, or visuals, that can be saved, shared, and built upon.

In plain terms

Artifacts are the concrete results or deliverables that an AI agent produces. Think of them as the tangible things an AI creates that you can see, save, and use later.

For example, if you ask an AI to help you write a report, the final document it generates is an artifact. Other examples include code snippets, summaries of information, or even custom charts and diagrams.

The expert version

Artifacts represent persistent, shareable outputs generated by AI systems, often as a result of agentic workflows or specific user requests. These outputs can range from textual documents, code, and data analyses to more complex deliverables like interactive visualizations or executable scripts.

Their significance lies in moving beyond ephemeral conversational turns to create lasting, actionable results. This enables collaboration, iteration, and integration into broader software development or business processes. The ability to manage and version these artifacts is crucial for reliable AI agent development.

Why it matters now

Anthropic is heavily promoting its new 'artifacts' feature, which allows users to create and save outputs like documents, designs, and code directly within Claude. This move suggests a push towards making AI assistants more useful for persistent work and collaboration, moving beyond simple chat interactions. Other companies are also exploring ways to integrate AI-generated outputs into workflows, as seen with GitHub Copilot plugins.

Where it shows up 24 items, newest first
How each company uses it
Anthropic Claude
Anthropic's Claude now features 'artifacts' for creating and saving outputs like documents, designs, and code directly within the chat interface, and is promoting their use.
Google Gemini
Google Gemini is exploring ways to integrate AI-generated outputs into workflows, potentially including features similar to artifacts.
Microsoft Copilot
Microsoft Copilot is enabling the sharing and updating of custom AI coding tools, which can be considered a form of artifact.
Related terms

AI AgentsWorkflowsOutputsDeliverablesPersistenceShareability

Often confused with
Ephemeral Outputs
These are temporary results, like a single chatbot response t
Training Data
This is the information used to teach an AI, whereas artifacts ar
Model Weights
These are the internal parameters of an AI model, not the externa
Origin

The term 'artifact' in software development refers to any output of the development process. In the context of AI, it has been adopted to describe the tangible results produced by AI agents or systems.

Try this about 5 minutes

In Claude, try asking it to write a short Python script to print 'Hello, World!' and then save or share the resulting code. In ChatGPT, ask it to summarize a provided text and then copy the summary to use elsewhere. These saved outputs are examples of artifacts.

Try it: Playbook entries that use thisPlaybook →

The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.

Questions people ask

What is the difference between an artifact and a chatbot response?
A chatbot response is often temporary and part of a live conversation. An artifact is a saved, persistent output that can be shared, edited, or used in other applications.
Can AI create different types of artifacts?
Yes, AI can create various artifacts including text documents, code, data visualizations, summaries, plans, and even interactive elements.

First seen on Subvolts May 7, 2025. Updated Oct 16, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.