A production‑minded guide to building, securing, and shipping Anthropic MCP tools—TypeScript and Python quickstarts, Claude Desktop packaging, and remote setups.
A practical guide to building robust multi-step AI pipelines with prompt chaining, orchestration patterns, state, testing, guardrails, and cost control.
Build end-to-end observability for AI agents: traces, metrics, logs, and evals to debug, govern privacy, and scale quality, reliability, and cost.
A practical playbook to optimize retrieval pipelines for search and RAG: metrics, chunking, hybrid retrieval, ANN tuning, re-ranking, and efficiency.
A practical DSPy tutorial: build modular LLM programs with signatures, teleprompters, and RAG—plus evaluation and production tips.
A practical 2026 guide to comparing AI image upscaling APIs—how to benchmark quality, speed, and cost, and what to demand for production integration.
