A RAG pipeline has five distinct places it can fail before the LLM ever sees your context. This post instruments every stage — query embedding, vector search, document ranking, context assembly, and generation — with OpenTelemetry spans and quality metrics, in Node.js, Python, and C#.
Category: AI
The LLM Landscape in March 2026: Open Source Catches Up, Local AI Goes Mainstream
In the span of a single week in early March 2026, more than twelve major AI models shipped across language, video, and spatial reasoning domains.
Prompt Management and Versioning: Treating Prompts as Production Code
Prompt changes are production changes. A wording edit at 3pm on a Friday can silently degrade thousands of responses with no error signal. This post builds a production-grade prompt management system with versioning, A/B testing, quality gates, and rollback in Node.js, Python, and C#.
Evaluating LLM Output Quality in Production: LLM-as-Judge and Human Feedback Loops
Tracing and metrics tell you when something is slow or expensive. Evaluation tells you when something is wrong. This post builds a production-grade LLM-as-judge pipeline in Node.js, Python, and C# — with a human feedback loop that catches what automation misses.
LLM Metrics That Actually Matter: Latency, Cost, Hallucination Rate, and Drift
Uptime and error rate are not enough. This post covers the metrics that actually reveal whether your LLM is working correctly in production — time-to-first-token, cost per request, hallucination rate indicators, output drift, and how to build dashboards that catch silent failures before users do.
Distributed Tracing for LLM Applications with OpenTelemetry
You cannot fix what you cannot see. This post walks through instrumenting a full LLM pipeline with OpenTelemetry in Node.js, Python, and C# — capturing every span from user request through retrieval, model call, tool execution, and response.
Why LLMOps Is Not MLOps: The New Operational Reality for AI Teams
Most teams try to apply their existing MLOps practices to LLMs and hit a wall fast. This post breaks down exactly why LLMOps is a different discipline, where the gaps are, and what the new operational stack looks like in production.
OpenClaw Complete Guide Part 8: Integrating OpenClaw with Your Development Stack
The final post in the OpenClaw series. Learn how to integrate OpenClaw directly into your Node.js and Azure development stack, wire it into CI/CD pipelines, build custom webhook integrations, and package your agent configuration for team deployment.
OpenClaw Complete Guide Part 7: Multi-Agent Workflows and Automation
Learn how to build multi-agent workflows in OpenClaw: running specialized agents in parallel, coordinating tasks between them, scheduling automation with cron jobs, and orchestrating complex pipelines. Part 7 of the complete OpenClaw developer series.
OpenClaw Complete Guide Part 6: Security Hardening and Best Practices
A complete security hardening guide for OpenClaw: CVE mitigations, gateway lockdown, skill auditing, exec tool restrictions, credential protection, and a production security checklist. Part 6 of the complete OpenClaw developer series.
