Scientist · Builder · Pricing Strategist
Twenty years of asking why things are worth what they're worth. Building tools to find better answers.
"The question nobody is asking clearly enough is not whether AI will take your job. It is which part of what you do is actually yours."
The Knowledge Quadrant Framework maps how people create value at work, showing how exposed that value is to AI displacement. Two axes. The first is the nature of your knowledge: Explicit knowledge is documented, trainable, searchable, the kind AI can replicate at scale. Tacit knowledge is judgment, pattern recognition, contextual instinct earned by living through real situations. You cannot Google it or prompt for it. The second axis is your output: Accuracy means there is a right answer and being wrong has real consequences. Originality means there is no right answer. The value lives entirely in the freshness of what you produce.
Surgeons, lawyers, analysts, engineers writing production code. High stakes, verifiable output. AI is entering this room fastest.
Marketers, designers, copywriters, product communicators. Pattern-based creativity at scale. AI is displacing the volume tier first.
Strategists, senior leaders, negotiators, advisors. Consequential calls on incomplete information. The human premium zone, and it is growing.
This quadrant creates history. AI can assist but cannot originate.
Within these four quadrants live eight personas, from The Doer (highest displacement risk) to The Oracle (minimal). Most people are not where they think they are. Kairos is built to close that gap.
The moment of reckoning. Know where you stand.
I built Kairos because the conversation about AI and jobs is happening at the wrong altitude. Everyone is debating which industries will survive. Almost nobody is asking the harder question: within your specific day, within your specific work, how much of what you do is actually irreplaceable?
Kairos is a self-inquiry tool. You describe your day freely, no forms, no quizzes, no judgment about how you should have spent your time. A local AI model reads your words through the Knowledge Quadrant Framework and sends you back an honest picture: your quadrant blend, your dominant persona, the displacement signals hiding in how you described your own work, and one question to sit with.
No login. No account. Your words never leave the machine. This is a mirror, not a test. Currently in private beta with a trusted network of peers.
Built on Llama 3.2. Runs entirely locally. Private by design.
I write about three things: the future of work and what AI is actually doing to human value, pricing as a strategic discipline rather than a finance function, and the quieter questions about leadership, trust, and what it means to build a life that holds together.
The opening argument. What the Knowledge Quadrant Framework is, why it exists now, and what it reveals about where AI displacement is actually happening.
Eight personas mapped across the quadrant, from The Doer to The Oracle. An honest look at where most professionals actually land.
The apprenticeship pathway that builds judgment is being eliminated by AI, at exactly the moment judgment matters most.
When answers become free, your value comes from the questions you ask.
What happens when a fourteen-year-old builds a chatbot before breakfast, and what that means for the rest of us.
Most people engage with AI at the surface. This is a framework for going deeper.
Your GPS does not run on static maps. So why does your pricing still work like it's 1995?
The companies that price well are not better at math. They are better at making decisions.
The gap between the leader who looks right and the leader who is right.
Cybersecurity explained for everyone who is not a wizard.
What the women in my early life taught me about building something that lasts.
Every morning my dog Jasmine runs in with unfiltered joy. She taught me something about trust I had not expected.
Why so many people feel like they're running on empty, and what evolution has to do with it.
My daughter asked me why I always bring up Lucknow. This is the answer I did not expect to find.
On resilience, the Gomti river, and a grandmother who rebuilt everything from zero.
I did not set out to become a pricing strategist. I set out to understand how things work.
Since 2022 at Cohesity, I have led pricing strategy through the company's transition to cloud-native SaaS monetization. The Knowledge Quadrant Framework and Kairos came directly from this work: watching knowledge get commoditized in real time, and needing a precise language for what was happening.
Before that, Dell was my decade-long graduate school. From 2007 to 2022, across India and Round Rock, Texas, I built prediction models, collaborative filtering systems, and pricing architectures underneath some of the largest commercial decisions the company made. Pricing stopped being a function and became a craft.
Earlier: Marketics in Bangalore taught me rigorous, long-horizon analytics. Coca-Cola taught me something no engineering curriculum does: how to make people want something. The gap between what something costs and what someone pays is not a math problem. It is a human one.
I went to IIM Ahmedabad in 2002 for my MBA, with an exchange semester at HHL Leipzig. Before that: IIT Kanpur, Material Science with a Computer Science minor. And before all of it: two years at Infosys building Goldman Sachs trade processing systems. That is where I first saw how quickly sophisticated technical work gets systematized the moment someone finds the repeatable pattern. The offshore model was the original displacement engine. I was inside it at 22.
I have spent twenty years inside complex commercial problems: pricing architectures built for a different era, deal economics that look healthy at the top line and quietly bleed at the margin, aftermarket and renewal pricing that was never designed but just inherited, and AI-driven intelligence that still needs a business model wrapped around it before it can create real value.
Right now I am not taking on paid projects. But if you are working on something genuinely interesting in B2B SaaS pricing, aftermarket parts pricing, or AI monetization strategy, I am open to a conversation on a pro-bono basis. Good problems are worth talking about regardless.