Anthropic API Guide: Building with Claude in 2026

**Real example:** I fed it a 180-page API documentation PDF and asked it to generate TypeScript types for all endpoints. It caught edge cases the documentation barely mentioned. … **What just happened:** - `max_tokens` is required (unlike OpenAI) - Messages format is similar but not identical to OpenAI - Response structure differs (it’s `content[0].text`, not `choices[0].message.content`) … **Where it struggles:** Handwriting recognition, low-quality images, and precise coordinate identification. … ## Common Mistakes to Avoid ### Sending Unnecessary Context Just because you have 200K tokens doesn’t mean every request needs them. I’ve seen developers send entire conversation history for simple queries, inflating costs 10x. **Fix:** Maintain a sliding context window. Keep recent messages plus essential context, not everything. ### Ignoring Max Tokens Unlike OpenAI, Claude requires `max_tokens`. Forgetting it throws an error. Setting it too low truncates responses mid-sentence. **Fix:** Default to 4096 for most tasks. Adjust based on expected response length. ### Not Handling Rate Limits Claude’s rate limits are reasonable but not published clearly. You’ll hit them during batch processing. **Fix:** Implement exponential backoff: ``` import time from anthropic import RateLimitError def call_with_retry(client, **kwargs): for attempt in range(5): try: return client.messages.create(**kwargs) except RateLimitError: wait_time = 2 ** attempt time.sleep(wait_time) raise Exception("Max retries exceeded") ``` … ## What Claude Can’t Do (Honest Limitations) **No image generation.** Claude analyzes images but doesn’t create them. You’ll need DALL-E or Midjourney. **No fine-tuning.** You can’t train custom Claude models on your data. OpenAI and open-source models win here. **Limited integrations.** The ecosystem is smaller. Fewer libraries, tools, and tutorials. You’ll solve problems yourself that are documented for OpenAI.