Building a Scalable Real-Time AI Chat Server with Claude API × WebSocket × Redis Pub/Sub — Node.js Production Architecture, Multi-User Management, and Cost Control
Running a real-time AI chat server on Claude API, WebSocket, and Redis Pub/Sub in production. SSE trade-offs, multi-instance routing, and how stop latency quietly corrupts per-user budgets — with the instrumentation code to measure it.
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 in production, including the arithmetic that links hit rate to the bill and the break-even points (about 22% on the 5-minute TTL, 53% on the 1-hour TTL).
Shipping Generative UI on Claude API: A Production Pattern for Streaming Dynamic Components with Tool Use and JSON Schema
Combine Claude's Tool Use, JSON Schema, and partial JSON streaming to render AI-assembled UI components safely. We cover registry design, type-safety, fallback, and the pitfalls you only learn after running this in production.
Claude API × Convex: Reactive AI Apps — Data Flow, Streaming, and Agent Patterns
How to combine Convex's reactive database with the Claude API to build chat and agent applications that hold up in production. Covers schema design, the Action/Mutation/Query boundary, streaming, tool-call state, and the cold-start pitfalls nobody warns you about.
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.
Debugging Claude Code Hooks in Production — Where to Start When Logs Are Missing
Your Claude Code hooks work locally but go silent in production. Here is the three-layer observability pattern I use on real projects, plus a 60-second minimal reproduction recipe for isolating failures.
Shadow Mode with Claude Agent SDK — Measuring Agent Accuracy on Live Traffic Without Touching Users
You want to ship an AI agent to production, but you can't measure its real accuracy without exposing real users. Shadow mode solves that paradox. This guide shows how to run a Claude Agent SDK agent alongside your existing workflow, log the deltas, and promote it step by step.
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.
Using tool_choice to Cut Wasted Inference: Four Modes and Cost Patterns for Production
tool_choice is one of the most underused parameters in the Claude API. The four modes — auto, any, tool, and none — each change both behavior and token cost. Here are the patterns I reach for in production, with runnable code.
Running Claude API Parallel Tool Use in Production — Controlling Concurrency, Designing for Partial Failure, and Cutting Latency
Claude API's parallel tool use can halve perceived latency, but partial failures and duplicate writes arrive just as fast. Concurrency control with asyncio.gather and a Semaphore, three partial-failure policies, idempotency, observability, and a way to measure your real parallel degree.
Implementing Progressive Delivery with the Claude Agent SDK: Canary, Feature Flags, and Automatic Rollback Patterns for Production
Production-grade patterns for safely rolling out AI agents built with the Claude Agent SDK. Combines canary traffic splitting, feature flags, and SLO-driven automatic rollback with runnable TypeScript/Hono implementation code.
Building Fault-Tolerant Long-Running AI Workflows with Claude Agent SDK × Temporal.io — A Production Design Guide to Durable Execution and Saga Patterns
A complete production guide to combining Claude Agent SDK with Temporal.io to build AI workflows that survive crashes, restarts, and multi-day human approval gates. Durable Execution, retry policies, saga compensation, and signal integration patterns.