Building Production Apps with the Claude API: A Deep Dive for Engineers
The Claude API offers capabilities that go beyond what most developers are using. Extended thinking, computer use, document analysis — here's how to deploy them effectively.
Most developers use the Claude API the same way they use any LLM API: send a message, get a response. That’s a small fraction of what the API supports.
Extended Thinking
Extended thinking gives Claude dedicated pre-response computation to work through complex problems before generating an answer. For tasks involving multi-step reasoning or mathematical derivations, the improvement in quality is substantial.
To use it: enable thinking in the API request with a budget_tokens parameter allocating token budget for the thinking process.
When to use it: complex reasoning tasks where quality matters more than latency, mathematical reasoning, code debugging with multiple potential causes.
Prompt Caching
Prompt caching lets you cache large shared prompt segments so they don’t need to be processed on every API call. For applications sending the same large context repeatedly, caching reduces latency by 85%+ and cost by 90%+ for the cached portion.
Implementation: mark cache checkpoints with cache_control: {"type": "ephemeral"} in your message content blocks. Cache is valid for 5 minutes and renewed on access.
Vision and Document Analysis
Claude 3.5 and later models handle images and PDFs natively. For document analysis applications — contract review, invoice processing, form extraction — sending the document directly often outperforms text extraction pipelines that introduce extraction errors.
Use the document content type for PDFs rather than encoding them as images — it has better support for long-form content and text extraction.
