Level 2 · Guide 09
Visualize and iterate with Claude Artifacts
Artifacts provide a workspace beside the conversation for documents, code, and visual outputs that can be revised. Define the audience, purpose, approved data, and required interactions first, then test displayed values and behavior against the brief.
Product features may change. Check the last verified date and official sources.
Core concepts to know first
Focus on the decisions these terms support in real work rather than memorizing them.
Core concepts
1. An Artifact is a reviewable work surface
A visual result can be persuasive while still being wrong. Treat data labels, calculations, states, links, and responsive behavior as testable requirements, not decoration. In this guide, the first observable move is to specify audience, data fields, interactions, and acceptance criteria.
2. Purpose and audience shape the artifact
Build with synthetic data and inspect every displayed value. Preserve the approved input and the evidence behind the result so a reviewer can distinguish what the source says from what Claude inferred. This directly controls the risk that a polished chart can conceal wrong calculations.
3. Data and interaction both need verification
Test links, empty states, mobile layout, and sharing scope. Record the decision and the remaining uncertainty instead of hiding it in polished prose. The review must explicitly test whether interactions may fail outside the preview.
4. Sharing scope is part of the design
Treat the possibility that publishing can reveal embedded data or broad sharing permissions as a required test case. The intended result is an interactive artifact with an explicit purpose and review checklist, not an unreviewed answer that merely looks complete.
5. Visual polish never replaces evidence
For Visualize and iterate with Claude Artifacts, the final concept joins the earlier checks into an operating boundary: use approved inputs, expose evidence and uncertainty, and stop before a consequential action. Ownership and a reproducible review determine whether an interactive artifact with an explicit purpose and review checklist may move beyond training.
Synthetic work scenario
How this applies at work
This scenario was written for learning and is not a real customer case.
A fictional sales-operations team creates a dashboard from synthetic pipeline data. It checks every total against the source table, tests empty and mobile states, and keeps publishing disabled until the owner reviews it.
The scenario is newly written for this guide and is neither a customer case nor a performance claim. Its specific deliverable is an interactive artifact with an explicit purpose and review checklist. A reviewer can reproduce the work from the synthetic inputs without access to customer, employee, health, contract, or confidential company data.
Try it yourself
Choose one small task and follow the steps. Confirm organizational policy and data boundaries before using sensitive materials.
Step 1. Specify audience, data fields, interactions, and acceptance criteria
Specify audience, data fields, interactions, and acceptance criteria. Use only approved synthetic material and record both the evidence and any remaining uncertainty.
Verify: Confirm that another reviewer can reproduce the input, result, evidence, and stop point.
Step 2. Build with synthetic data and inspect every displayed value
Build with synthetic data and inspect every displayed value. Use only approved synthetic material and record both the evidence and any remaining uncertainty.
Verify: Confirm that another reviewer can reproduce the input, result, evidence, and stop point.
Step 3. Test links, empty states, mobile layout, and sharing scope
Test links, empty states, mobile layout, and sharing scope. Use only approved synthetic material and record both the evidence and any remaining uncertainty.
Verify: Confirm that another reviewer can reproduce the input, result, evidence, and stop point.
Completion checklist
Check only what you verified yourself. Every item must be checked before saving completion.
Some items are still unchecked. Review the result again.
What could go wrong?
Plausible language does not guarantee accuracy. Compare the result with originals, calculations, permissions, and current information.
- A polished chart can conceal wrong calculations
- Interactions may fail outside the preview
- Publishing can reveal embedded data or broad sharing permissions
Boundaries that require human review
Academy practice stops at draft, preview, or approval pending. Actions with real impact require separate owner approval outside Academy.
What AI can do
- Step 1. Specify audience, data fields, interactions, and acceptance criteria
- Step 2. Build with synthetic data and inspect every displayed value
- Step 3. Test links, empty states, mobile layout, and sharing scope
What a person must approve
- Applicable law, contract, organizational security policy, and explicit approval boundaries take priority. Stop and ask the responsible owner when they conflict.
- Academy exercises never send, publish, purchase, delete, execute contracts, or change permissions. A responsible person performs any real action through a separate process.
This guide is educational and does not replace legal, security, or privacy judgment for your organization.
Questions about this guide
- When is this guide complete?
- It is complete when the stated outcome is ready and another reviewer can retrace the inputs, evidence, boundaries, and decision. The target outcome is “An interactive Artifact with an explicit purpose and review checklist.”
- May I practice with real company data?
- No. Use synthetic material in the Academy. Real data requires a separate review of policy, legal basis, contracts, minimization, retention, deletion, and the approved environment.
- What if the product screen differs from this guide?
- Product behavior can change. Check the verification date and official sources, then retest the current account and plan with a small, low-risk example.
Official sources and further reading
Recheck the current product and policy status in these primary sources.
Authorship and review
Save progress
Completion and checklist items are saved only in this browser. They do not sync to other devices or browsers.
Academy does not collect or store work materials, prompts, or outputs. It runs no separate analytics scripts beyond basic server access logs.