Rishabh Sethia

Prompting vs RAG vs Fine-Tuning: When to Use Each (A Developer's Decision Framework)

Teams waste weeks on fine-tuning when a system prompt would have done the job — or build entire RAG pipelines for problems that didn't need them. Here is the decision framework that eliminates that confusion.

Claude vs GPT-5: Which LLM Actually Performs Better for Code Generation in 2026?

At the frontier, Claude Sonnet 4.6 and GPT-5.4 are within 1.3 benchmark points of each other. What actually separates them is task type — and we have 18 months of production data to show exactly where each wins. No hedging.

How We Built an Agentic Workflow That Saves Our Clients 15+ Hours a Week

A laundry management client was spending 32+ hours a week manually answering WhatsApp queries. We built a three-agent workflow in n8n that now handles 78% of all queries autonomously, recovering 130+ hours per month. Here is the architecture, what broke the first time, and what actually made it work.

Human-in-the-Loop AI: Why Full Autonomy Is Still a Bad Idea for Production Systems

Full autonomy in production AI systems fails in four specific, predictable ways. After building and shipping agentic workflows for clients across India and the Middle East, here is what we have learned — and the framework we use to decide where autonomy is safe and where a human gate is non-negotiable.

The 7 Agentic AI Design Patterns Every Developer Should Know (ReAct, Reflection, Tool Use, and More)

Most AI production failures between 2024 and 2026 were architectural, not model quality failures. These are the 7 agentic design patterns — ReAct, Reflection, Tool Use, Planning, Multi-Agent Collaboration, Sequential Workflows, and Human-in-the-Loop — with production-readiness ratings and real gotchas from building live systems.