Your AI App is Live. Now How Do You Know It’s Actually Working?
Getting a demo to work is easy. Knowing your AI app is working reliably for real users requires monitoring. Here’s the framework I use.
Getting a demo to work is easy. Knowing your AI app is working reliably for real users requires monitoring. Here’s the framework I use.
Most people reach for fine-tuning way too early. Here’s the decision framework for when prompting is enough, when RAG is better, and when fine-tuning actually makes sense.
Building a RAG demo is easy. Building one that handles Sanskrit, Hindi, and English scripture queries without hallucinating a single verse — that’s the real challenge. Here’s what I learned.
The complete troubleshooting guide for OpenClaw in 2026. Covers gateway token errors, port conflicts, config issues, browser control problems, and every other common error with step-by-step fixes.
The definitive guide to vibe coding in 2026. Covers 17 tools across 4 tiers, Spec-Driven Development, OpenClaw orchestration, and practical workflows for beginners and professionals.
Have you ever started a coding project and realized halfway through that you’re juggling too many moving parts? Frontend changes breaking backend logic. Test files falling out of sync. Documentation getting forgotten while you’re deep in debugging mode. If you’re nodding along, you’re not alone. For months, I’ve been using Claude Code as my AI … Read more
I have been running both Claude Code and Codex in production for months. Here is the honest comparison nobody else is giving you — benchmarks, real costs, where each tool wins, and the hybrid workflow that changes everything.
After months of real bills from Claude Code, Codex, Cursor, and GitHub Copilot, here is what these tools actually cost at different usage levels — and which one is right for your budget.