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From the desk

The Canonical.

A converging point for the real and the artificial.

LatestInsight3 min read

AEO vs GEO, Explained: Why a Single Optimisation Mechanic is not the Only Answer

AEO optimises for the short direct answer a voice assistant reads out. GEO optimises for the longer generated reply, and needs AEO underneath it.Indira GuptaRead →

RAG Systems, Explained: Why it is not Just a Smart Filing System

A RAG system answers only from documents you supply, so nothing leaves the building. What it is, how retrieval and generation split the work, and when to use one.
Insight5 min read

Prompted, Week Two: Nike, Just Name It

As of 2025 Nike holds 14.1% of India's sportswear market share. It is #1 on the AI visibility index and has an AI SoV of 18.6%. Discover why.
Insight5 min read

Prompted, Week One: SUGAR Cosmetics Cracked Discovery, Not Identity

SUGAR ranks fifth of six Indian beauty brands on AI visibility. Named prompts find it every time, category prompts only 55 percent. Why entity grounding is the gap.
Insight6 min read

LLMO, Explained: Why Being Trained On Isn’t the Same as Being Understood

LLM Optimisation shapes how your brand exists in the data models learn from. Why you cannot edit what a model already knows, and how brands enter the canon.
LLMO7 min read

Schema Markup, Explained: Why Machines Can’t Take Your Word For It

Structured code removes the ambiguity that makes an AI skip you. How the “museum placard” of the web became one of the quiet foundations of GEO, and where to start.
Schema6 min read

SEO vs. GEO, Explained: Why Ranking on Google No Longer Means You Exist to AI

The shift from being clicked to being cited as true. Why the web did not get smaller, the doorway into it did, and how GEO puts you on the right side of it.
GEO6 min read