Essays on AI fairness, machine learning, geopolitics, software craft, and the quiet politics of how we build things. By Mukul Namagiri.
The Writing
A collection of long-form thinking across AI fairness, machine learning theory, responsible scaling, software archaeology, and the geopolitics of intelligence.
Microsoft's Fairlearn enters the ring, armed with charts, good intentions, and a frank acknowledgment that it cannot fix everything — much like us. A sharp, satirical take on how human bias gets laundered into AI datasets with admirable efficiency.
Read essay →"The same snap judgements we pass in the cereal aisle have been laundered into the datasets that now make consequential decisions."
On normalization — the quiet discipline that keeps neural networks from growing unchecked. Drawn from linear algebra and biology, this is about why controlled scaling matters more than raw power.
Read essay → Software CraftOn the quiet collapse of codebases, the illusion of order, and why a cheat sheet might just save us all. A meditation for the weary debugger who arrived from pure science and found beautiful chaos.
Read essay → AI GovernanceAI is an emergent phenomenon, not a developed technology. On responsible scaling policies, the nuclear analogy, and what happens when something this capable is released before we fully understand it.
Read essay → Geopolitics & AIOn trust, trade, and the strange new currencies of model weights being minted at the edge of human intelligence. From Mesopotamian grain trades to AI geopolitics — the question beneath every transaction.
Read essay → Agentic AIOn agentic AI systems, introspection, and what it means for machines to move from thinking to doing. A personal essay on slow deliberation in a world rewarding quick reflexes.
Read essay →Projects
Live applications exploring the intersection of information, fairness, and intelligence.
A live web application — home to essays, experiments, and ideas on AI, agency, and the question of what machines should be allowed to decide.
Visit app →A hosted form application built on PythonAnywhere — part of an ongoing effort to make data collection thoughtful and accessible.
Open form →A long-form publication on AI fairness, bias, and the societal stakes of algorithmic decision-making. Essays that implicate the reader.
Read publication →Portfolio
A curated view of projects, skills, and background — built for those who want the full picture.
Research, writing, and technical work across machine learning, AI fairness, and software. The full professional profile.
View Portfolio →Support
Good writing takes time. If any of this thinking has been useful, interesting, or even just made you pause — a small contribution keeps it going.
Click the button or scan the QR code — whichever is easier.
Scan to support