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The Frankenstein AI: How to Stop Building Monstrously Complex RAG Pipelines and Start Using Science
Is your AI chatbot a sleek machine or a Frankenstein monster? Too many RAG pipelines are built on "vibes," stitching together complex features without proof they actually work. It’s time to replace the guesswork with science. Learn how to forge a "Golden Dataset," deploy LLM-as-a-Judge metrics, and ruthlessly prune your bloated architecture. Stop engineering monsters and start building lean, accurate systems backed by hard data.

Debasish
Dec 23, 20254 min read


Beyond Tool Calling: Why AI Agents Should Write Code to Speak with MCP
raditional JSON tool calling is fragile. "Code Mode" changes the game: convert MCP tools to TypeScript APIs and let AI agents write executable code. It’s faster, handles complex logic, and uses secure sandboxes. Get the full code demo here.

Debasish
Dec 4, 20255 min read


The Efficiency Gap: Why JSON Might Be Bloating Your LLM Costs
Is JSON bloating your LLM costs? Discover TOON (Token-Oriented Object Notation), the high-efficiency alternative designed specifically for Generative AI. By decoupling schema from data, TOON can slash token usage by nearly 50% compared to standard JSON. Perfect for RAG pipelines, lowering API latency, and maximizing context windows. Check out our head-to-head code benchmark to see exactly how much syntax overhead you can eliminate today.

Debasish
Nov 26, 20253 min read
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