Claude is a conversational AI assistant. Its interface and available capabilities can change by plan and release. This guide focuses on durable workflows: giving context, working with long documents, iterating on writing, using Projects and Artifacts when available, and reviewing outputs before use.
1. Give Claude a concrete job
Start with a deliverable: “Review this proposal and produce a table of assumptions, evidence, risks and unresolved questions.” Add the audience and constraints. Avoid prompts that only say “analyze this” because the model has no definition of success.
2. Use long documents with a question framework
For a report, contract, transcript or research packet, specify which parts matter and what evidence format you want. Ask for section-level references where useful. If multiple documents disagree, require Claude to show the conflict rather than silently merge them.
3. Iterate on writing with explicit editing passes
Separate drafting from editing. First ask for structure, then a draft, then a specific edit pass such as clarity, brevity, tone or fact-check flags. This is easier to control than asking for “perfect writing” in one request.
4. Use Projects for stable context
When Projects are available, group related chats and reference material around one durable objective. Add style guides, background documents or recurring constraints once, then reuse them across conversations. Keep project instructions short enough that you can audit them.
5. Use Artifacts for work you need to inspect
When Artifacts are available, ask Claude to create a document, code snippet, diagram or other work product that benefits from a separate editable/previewable surface. Treat the artifact as a draft you can inspect and revise, not an automatically approved final result.
6. Review coding output like a pull request
For code, define language, runtime, inputs, expected behavior, failure cases and tests. Ask for the smallest change that solves the problem. Before running generated code, inspect dependencies, file writes, network calls, credentials and destructive commands.
Task → source/context → audience → constraints → output structure → uncertainty rule. Example: “Using only the attached brief, draft a one-page launch memo for executives. Separate confirmed facts from assumptions and list missing information at the end.”
Feeding a large document set without telling Claude which source is authoritative; asking it to preserve every detail while also making text much shorter; treating a polished paragraph as factually verified; and executing generated code without review.
What to practice next
Take one real document you understand well. Ask Claude for a summary, then compare it with the source. Rewrite the prompt so every missed or distorted point is addressed by an explicit instruction. That exercise teaches you how to build a reliable review prompt.