Diagnosing Claude API Prompt Cache Misses — How to Read the usage Field
If your Claude API prompt cache isn't reducing your bill, the usage field is where to start. This guide walks through the five most common reasons cache_read_input_tokens stays at zero and how to fix each one.
Production Infrastructure for Claude API — 8 Things You Need Between 'It Works' and 'It Holds Up'
There is a much bigger gap than you'd think between a working Claude API call on your laptop and a service that survives real users. Here are the eight pieces of infrastructure I now consider non-negotiable, learned the hard way.
Production-Grade Hallucination Defense for Claude API: A Multi-Layer Architecture
Prompt engineering alone is not enough to suppress hallucinations in production. After a real customer incident, I rebuilt the system around four defensive layers — input grounding, tool-use escape hatches, citations, and post-hoc verification. This is the implementation playbook.
Replay-Driven Testing for Claude API: A Production Pattern for Recording and Replaying Responses
A production-grade design for stabilizing Claude API tests by recording and replaying real responses. Covers cassettes for Messages, Streaming, Tool Use, CI integration, and incident replay.
How I Cut My Claude API Bill in Half With Prompt Caching
Done right, Anthropic's prompt caching can roughly halve your monthly API spend on workloads with long, repeated system prompts. Here is the design playbook I use after six months of running it in production.
Running the Claude API in Python Production — Rate Limits, Retries, and Timeouts
If you put Claude API into a real backend service, how you handle 429, 503, and read timeouts decides your reliability ceiling. This is the design I settled on after operating it in production.
High-Availability Patterns for the Claude API — Making Sonnet/Haiku/Opus Fallback Work in Production
A single-model Claude API integration will fall over the first time rate limits or a regional hiccup land at peak hours. This is the production pattern for a Sonnet → Opus → Haiku fallback chain, with circuit breakers, streaming coverage, and the pitfalls you only learn the hard way.
Running Claude API Parallel Tool Use in Production — Controlling Concurrency, Designing for Partial Failure, and Cutting Latency
Claude API's parallel tool use can cut agent latency in half — but partial failures and state conflicts show up fast in production. Here's how to control concurrency, design error handling, and add observability.
Claude API × Kotlin Multiplatform — Building Production AI Features for iOS and Android
Integrating Claude API with Kotlin Multiplatform (KMP) to ship production-quality AI assistant features on iOS and Android. Stream termination, mid-stream error events, retry strategies, expect/actual alignment, and testing — written from an indie developer's production experience.
Building Production Conversational AI with Claude API — Context Management, Long-Term Memory, and Safety Filters
Solve context explosion, memory loss, and safety risks in production chat systems with a three-layer memory architecture and integrated guardrails using Claude API
Testing Claude API Applications — Unit, Integration, and E2E Patterns That Hold Up Against Probabilistic Output
Solve the 'AI output changed and broke my tests' problem for good. Learn to combine mocks, semantic assertions, and snapshot testing into a practical test design pattern for Claude API applications.
Intelligent Model Routing with Claude API — Auto-Selecting Sonnet 4.6 and Haiku 4.5 for Optimal Cost and Quality
Build an intelligent routing layer that automatically selects between Claude Sonnet 4.6 and Haiku 4.5 based on request complexity. Covers classifier design, circuit breakers, fallback chains, and cost monitoring for production deployments.