Mishik Sharma

1 Introduction: Value-Addition and Beyond  India's agricultural transformation has, for decades, been viewed primarily through the lens of production. Better seeds, improved irrigation, mechanisation, crop insurance, soil health and higher yields have all been central pillars of agricultural policy. These efforts have undoubtedly strengthened the country's food security and agricultural capacity. Yet as India's economy has matured, the national conversation has increasingly shifted from producing more to creating more value. Across political speeches, policy documents and development programmes, one phrase has become almost ubiquitous: value addition. The idea is straightforward. Farmers should not merely sell raw agricultural produce. More of that produce should be processed, branded and marketed as higher-value products, enabling producers and rural regions to capture a larger share of the final consumer price. This thinking has inspired several important policy initiativ...

Part I: Reimagining the University The University We Forgot to Build India possesses one of the world's largest higher education systems. Tens of thousands of public colleges, hundreds of universities, millions of students, and an ever-expanding ecosystem of specialized institutions together form an educational network that reaches every district of the country. Over the past three decades, this network has expanded considerably through the establishment of engineering universities, medical universities, agricultural universities, private universities, and specialized institutes catering to increasingly diverse professional needs. Most discussions on higher education naturally revolve around improving research output, increasing employability, strengthening institutional autonomy, modernizing infrastructure, enhancing faculty quality, and improving national and global rankings. These are undoubtedly important priorities. Yet an equally important question is seldom asked: What is th...

Introduction For nearly three years, the global artificial intelligence race followed a remarkably familiar script. Technology companies competed to build larger foundation models, train them on ever-growing datasets, acquire more powerful GPUs, construct hyperscale AI data centres, and climb benchmark leaderboards. Every major announcement revolved around model releases, reasoning capabilities, inference costs, context windows, or custom AI chips. Governments launched sovereign AI missions. Investors poured hundreds of billions of dollars into compute infrastructure. Enterprises rushed to experiment with generative AI. The defining question of the industry appeared straightforward:  Who can build the world's smartest AI? Then, almost quietly, another race has begun. Over the past few months, a series of seemingly unrelated announcements from some of the world's leading technology companies has revealed a remarkable convergence. On 11 May, OpenAI launched the OpenAI Deployment ...