LLM Circuit Breakers and Fallback Chains: Multi-Provider Failover in Production (2026)
Circuit breakers, fallback chains, hedging, and bulkheads for LLM apps: patterns that keep OpenAI, Anthropic, and Gemini outages from taking you down.
Best Practices
Industry best practices and patterns
LLM Tool Schema Design: JSON Schema Patterns for Reliable Function Calling (2026)
Design JSON Schemas for LLM function calling that hold up under real production traffic. Strict mode, enums, nesting depth, Pydantic-first, and the failure modes I measure across OpenAI, Anthropic, and Gemini.
LLM-as-a-Judge in Production: Bias, Calibration, and Reliable Automated Evaluation (2026)
LLM-as-a-Judge in production: cancel positional, verbosity, and self-preference bias, calibrate against Cohen's kappa with 200+ human labels, and wire reliable automated evaluation into your CI pipeline without breaking the budget.
LLM Streaming in Production: SSE, Backpressure, and Cancellation Patterns (2026)
Production LLM streaming over SSE: fix nginx buffering, propagate cancellation to the provider, handle backpressure, and instrument TTFT for OpenAI, Anthropic, and Gemini.
LLM Rate Limiting and 429 Retries in Production: OpenAI, Anthropic, and Gemini (2026)
A production playbook for handling HTTP 429 responses from OpenAI, Anthropic, and Gemini in 2026: retry-after, exponential backoff with jitter, token buckets, circuit breakers, and multi-provider fallback.
Parallel Tool Calls in Production: OpenAI, Anthropic, and Gemini Function Calling Compared (2026)
Parallel tool calls cut agent latency by 40-70%, but the OpenAI, Anthropic, and Gemini APIs behave differently. Runnable Python for each provider, the opt-out flags that matter, and paired-eval methodology for deciding when to serialize.
Text-to-SQL with LLMs in Production: Schema Linking, Query Validation, and Guardrails (2026)
A practical, evaluation-first guide to shipping text-to-SQL with LLMs in production: schema linking as RAG, semantic layers, three-stage query validation, and defense-in-depth guardrails, with runnable code and 2026 benchmark numbers.
Best Embedding Models for RAG in 2026: OpenAI, Voyage, Cohere, and Jina Compared
Voyage-3-large tops MTEB v2, Cohere Embed v4 handles 128K multimodal, OpenAI is the best default, and Jina wins multilingual. Full 2026 benchmark with code.
OpenAI Batch API vs Anthropic Message Batches: A Production Guide to 50% Cheaper LLM Inference (2026)
OpenAI Batch API and Anthropic Message Batches both cut LLM token costs by 50% in exchange for a 24-hour SLA. Here is when batch wins, working Python for both, and the production pitfalls nobody mentions.
Structured Outputs vs Function Calling: 2026 Decision Guide
When to pick structured outputs vs function calling across OpenAI, Anthropic, and Gemini in 2026: schema enforcement, latency, and runnable code for each pattern.
Prompt Caching in Production: How to Cut Claude, OpenAI, and Gemini Costs by 90%
A production guide to prompt caching with Claude, OpenAI, and Gemini. Learn cache breakpoints, TTL strategy, prompt structure, and the seven mistakes that silently kill your cache hit rate.
Context Engineering for Production AI Agents: A Python Implementation Guide
Context engineering — curating what an LLM sees at inference time — is now the defining skill for AI engineers. This guide walks through the four core strategies (write, select, compress, isolate) with production Python implementations using LangGraph, reranking pipelines, and multi-agent isolation.