Troubleshooting Local LLMs: RAM, VRAM, & Disk Gotchas
Memory and IO Troubleshooting for Large Language Model Deployments Practical steps to diagnose and fix RAM, VRAM, and disk IO bottlenecks so your LLMs run
RAG vs. Fine‑Tuning for FAQs: A Cost‑Based Guide
Estimating LLM Deployment Costs: Goals, Tradeoffs, and a Practical TCO Learn how to scope LLM projects, estimate costs across compute, storage, and labelin
100 Useful Prompts for Small Businesses (Copy‑Paste)
AI Prompts for Sales, Marketing, Ops, and Hiring Practical, ready-to-use AI prompts to generate leads, create content, improve support, streamline ops, and
Vector Databases vs. Full‑Text Search: When to Use Each
Choosing Between Full‑Text Search, Vector Databases, and Hybrid Retrieval Decide the right retrieval approach to balance precision and semantic relevance,
Feature Flags for AI: Roll Out Gradually
Feature Flag Strategy for Safe, Controlled AI Deployments Implement feature flags to reduce AI deployment risk, accelerate safe experiments, and rollback q
Measuring Data Quality: Practical Checks
Data Quality Audit Checklist: Ensure Reliable AI/ML Inputs A practical checklist to audit dataset quality for AI/ML—improve model reliability, reduce bias,
AI for Education: Lesson Plans from Syllabi
How to Build AI-Enhanced Lessons from a Syllabus Turn any syllabus into effective AI-enhanced lessons: prioritize objectives, design activities, and iterat
Product Photo Enhancements with AI (Ethical Guide)
AI Image Enhancement for Product Listings: Objectives, Ethics, and Workflow Set clear goals and ethical standards for AI image enhancement to boost convers
Failure‑First Design: Make Agents Fail Safely
Designing for Safe Failures in AI Systems Practical guidance to make AI failures safe, observable, and recoverable — reduce harm, maintain trust, and accel
Post‑Release Monitoring: Catching Silent Failures
Detecting and preventing silent failures in production Stop hidden outages before users notice: practical observability, testing, and alerting steps to sur