A practical Docker image optimization guide for smaller, safer, faster containers that build cleanly and deploy reliably.
CI/CD Pipeline Best Practices for Kubernetes Deployments
A practical guide to CI/CD best practices for Kubernetes deployments, from build and scan to rollout, rollback, GitOps, and observability.
Cloud Cost Optimization Checklist for AWS Teams
A practical AWS cloud cost optimization checklist for engineering and finance teams who want lower spend without hurting reliability.
LLM Evaluation Framework: How to Test AI Apps Before Launch
A practical LLM evaluation framework for testing AI applications before launch with golden data, automated checks, review, and release gates.
Prompt Engineering for Production Apps: Patterns That Matter
A practical prompt engineering guide for production AI applications, focused on structure, context, evaluation, versioning, and reliability.
AI App Architecture: Frontend, API, Model Layer, and Data
A practical guide to AI app architecture, covering frontend UX, API design, model orchestration, data controls, retrieval, evals, and monitoring.
MCP Explained: How AI Agents Connect to Tools and Data
A plain-English explanation of Model Context Protocol, how it helps AI agents connect to tools and data, and what teams should secure.
How to Monitor LLM Apps: Logs, Traces, Evals, and Alerts
Learn how to monitor LLM applications with logs, traces, evaluations, feedback loops, cost metrics, latency tracking, and actionable alerts.
How to Reduce OpenAI API Costs in Production
A practical guide to lowering OpenAI API costs in production without wrecking quality, reliability, or the user experience.
AI Agent Security Checklist for Enterprise Teams
A practical AI agent security checklist for enterprise teams covering data access, tool permissions, prompt injection, approvals, logs, and evals.