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Anthropic (Claude)

Connect Anthropic to power reasoning-heavy AI features with Claude: document analysis, extraction, drafting, and assistants.

The Anthropic connector lets applications you build with condoo.Vibe use Claude models for AI-powered features.

You can use Claude inside your application for experiences such as:

Once Anthropic is connected, tell condoo.Vibe what you want Claude to do inside your product.

Connect Anthropic. Define the AI experience. condoo.Vibe builds the workflow around Claude.

condoo.Vibe vs Claude

condoo.Vibe and Claude play different roles.

You use condoo.Vibe to build and evolve your product.

Claude can then become one of the AI capabilities inside the application you build.

For example:

Build a legal document review platform where users can upload contracts and receive a structured analysis.

condoo.Vibe builds the application.

Claude can power the analysis step.

Conceptually:

You
 ↓
condoo.Vibe
 ↓
Builds the product
 ↓
User uploads document
 ↓
Application
 ↓
Claude
 ↓
Analysis returned
 ↓
Application displays result

Before You Start

You'll need an Anthropic account and the credentials required by condoo.Vibe's Anthropic connector.

API usage may incur charges based on your Anthropic account, model selection, and usage.

Connect Anthropic to condoo.Vibe

Open your condoo.Vibe project and go to Connectors.

Find Anthropic and select it.

condoo.Vibe Anthropic Claude

Follow the connection flow and provide the information condoo.Vibe requests.

condoo.Vibe Claude Config

Once connected, Claude becomes available to use inside the application you're building.

Build Your First Claude Feature

Suppose you're building a document analysis application.

You could tell condoo.Vibe:

Add a Contract Summary feature using Claude. Users should upload a contract and receive an executive summary, key obligations, important dates, risks, and questions they should review.

The workflow might look like:

Upload Contract
      ↓
Extract relevant content
      ↓
Send to Claude
      ↓
Receive analysis
      ↓
Structure results
      ↓
Display to user

Claude becomes one component in the overall application workflow.

Define the Input

Tell condoo.Vibe what information Claude should receive.

For example:

Use the contract text and the user's selected review goal.

Or:

Use the support ticket and the previous five messages in the conversation.

Or:

Use the lead enquiry, budget, timeline, and recent activity.

The model should receive the context it actually needs to perform the task.

Define the Output

Be clear about what you expect back.

For example:

Return:

  • Executive summary
  • Key obligations
  • Important dates
  • Potential risks
  • Recommended questions

Or:

Return sentiment, category, urgency, and a suggested next action.

Structured expectations make it easier for condoo.Vibe to build a useful product experience around the model.

Example: Document Analysis

Claude can be useful in applications that need to process longer or more detailed material.

For example:

Add an AI document review feature. Users should upload a document and receive a concise summary, key decisions, action items, and important dates.

You might then add:

Let users ask follow-up questions about the uploaded document.

Now the experience evolves from one-time generation into an AI-powered document workspace.

Example: Support Assistant

For a customer support application:

Add a Draft Reply button using Claude. Use the current support ticket and recent conversation history to generate a suggested response. Show the draft in the reply editor for the agent to review before sending.

Conceptually:

Ticket
 ↓
Claude
 ↓
Draft response
 ↓
Agent reviews
 ↓
Agent sends

The model assists the support agent rather than automatically speaking to the customer.

Example: Knowledge Assistant

Suppose your application contains company knowledge or project documentation.

You could ask condoo.Vibe:

Add an AI assistant that helps team members understand project documentation. Use the relevant project context to answer questions and cite the source sections used for the answer.

The application can combine stored information with Claude to create a more contextual assistant.

Example: Structured Extraction

Imagine users submit detailed business enquiries.

You could ask:

Use Claude to extract company name, requested service, budget, timeline, pain points, and decision-maker information from each enquiry. Save the structured result to the lead record.

This turns unstructured text into data your application can use.

Use Claude for Product Workflows

Avoid thinking only in terms of:

Ask Claude a question.

Instead, think:

Where does AI improve this workflow?

For example:

Customer submits enquiry
       ↓
Save enquiry
       ↓
Claude analyzes it
       ↓
Structured qualification
       ↓
Save result
       ↓
Sales rep sees summary

That is an AI-powered product workflow.

Human Review

For important actions, consider keeping a person in the loop.

For example:

Use Claude to draft a project proposal, but require the account manager to review and approve it before it can be sent.

Conceptually:

Claude generates
      ↓
Human reviews
      ↓
Human approves
      ↓
Action happens

This is especially useful when AI output affects:

Saving Claude Responses

Decide whether generated output should become permanent application data.

For example:

Save approved contract summaries to the document record.

Or:

Don't save generated drafts until the user clicks Save.

Or:

Regenerate the summary only when the user explicitly requests it.

This affects both product behavior and API usage.

Sensitive Information

Before sending application data to Claude, consider what information the feature actually needs.

Don't send unnecessary private information simply because it's available.

For applications handling sensitive customer or business data, make sure your use of an external AI provider fits your privacy and compliance requirements.

Model Choice

Anthropic may provide multiple Claude models with different characteristics.

Some may prioritize:

If your feature requires a particular model, tell condoo.Vibe which one to use.

Otherwise, describe the product requirement.

For example:

This feature analyzes long documents, so quality and context handling are more important than very fast responses.

Or:

This feature performs thousands of simple classifications, so prioritize speed and cost efficiency.

Control Output Length

AI responses don't always need to be long.

For example:

Return a maximum 5-bullet executive summary.

Or:

Keep suggested support replies under 150 words.

Or:

Return only the structured fields required by the application.

Limiting unnecessary output can improve the user experience and help control API usage.

Handle Loading States

AI generation can take time.

Your application should clearly show when Claude is working.

For example:

Analyzing document...

You can ask condoo.Vibe:

Show a loading state while Claude processes the document and disable the Analyze button until the current request completes.

Handle Failed Requests

AI requests can fail.

For example:

Analyze
  ↓
Claude request
  ↓
Error
  ↓
Show useful message
  ↓
Retry

Tell condoo.Vibe:

If analysis fails, preserve the uploaded document and let the user retry without uploading it again.

The main workflow shouldn't lose the user's work simply because one AI request failed.

Avoid Unnecessary Requests

Don't regenerate expensive AI output every time a page loads unless that's actually required.

For example:

Save the generated document summary and display the stored version whenever the user returns. Only call Claude again when the user clicks Regenerate.

This can improve speed and reduce API usage.

Common Problems

Claude feature doesn't respond

Check whether:

Use Debug Mode with the specific behavior you observe.

Output quality is poor

The issue may be the instructions or context sent to Claude rather than the connection itself.

For example:

The contract analysis is too generic. Improve the prompt so it explicitly identifies obligations, termination clauses, payment terms, deadlines, and unusual risks.

Output format changes

If your application depends on a specific structure, require and validate structured results.

For example:

Ensure the classifier always returns category, urgency, sentiment, and recommendedAction in a predictable structured format before saving it.

Response is slow

Ask condoo.Vibe to inspect:

Long input and complex output can naturally require more processing.

Usage is high

Check whether Claude is being invoked unnecessarily.

For example:

Audit the document detail page and make sure the AI analysis isn't being regenerated every time the page loads.

Debugging Anthropic

A good Debug Mode request could be:

Expected: When the user clicks Analyze, Claude should return a document summary and key risks.

Actual: The loading state appears, then disappears without showing any result.

The uploaded document is available and loads correctly.

Error: [PASTE ERROR IF AVAILABLE]

Debug the Anthropic analysis workflow without changing the document upload feature.

Don't include your API key in the prompt.

Test Your Claude Feature

Before publishing, test:

For important AI-assisted actions, also test the human review workflow.

A Good Claude Prompt for condoo.Vibe

When asking condoo.Vibe to build a Claude-powered feature, define:

Purpose

What should Claude accomplish?

Input

What information does it receive?

Output

What format should it return?

User experience

How does the user interact with the result?

Persistence

Should the output be saved?

Permissions

Who can use it?

For example:

Add a Contract Review feature using Claude. Authorized users should upload a contract and click Analyze. Use the document content to return an executive summary, important obligations, payment terms, deadlines, termination conditions, and potential risks. Display the result in structured sections. Save the approved analysis to the document record and let users regenerate it manually if needed.

OpenAI or Claude?

You don't necessarily need both providers in every application.

The right provider depends on your product requirements, preferred models, cost considerations, and the type of AI experience you're building.

You can even design an application that supports multiple providers when there's a clear product reason to do so.

The key principle remains the same:

Choose the provider that best supports the experience you're trying to build.

Next: Google (Gemini)

Next, we'll look at Google Gemini and how to connect Google's AI models to applications built with condoo.Vibe.

We'll focus on: