Mishik Sharma

When Y Combinator partner Tom Blomfield posted on X (on 1 March) that "the entire Accenture workforce is about to be outperformed by a 24-year-old who learned Claude Code last Tuesday", he was doing what Silicon Valley does best: collapsing a complex structural question into a punchy provocation.  The post sparked widespread debate about AI disrupting IT, consultancy, and other white-collar jobs. It was covered by multiple outlets in India (where Accenture and similar companies have massive workforces)  feeding an already anxious conversation about AI's threat to India's $290 billion IT services sector. It deserves a serious response — not a defensive one, but a strategic one. The Disruption Narrative Gets the Diagnosis Wrong The fear driving headlines like Blomfield's rests on a simple substitution logic: if AI can do what IT workers do, IT workers become redundant. This logic is not entirely wrong — it correctly identifies that agentic AI compresses the value of...

The announcement of a proposed $300 billion new refinery project in Brownsville, Texas, USA—made directly by Donald Trump yesterday—has been presented as a historic moment in American industrial revival. If realized, the facility would represent the first major new refinery project of its kind in about five decades in the US. Yet beyond the visible political symbolism lies a more structural question: how do large investment announcements translate into real industrial assets? The refinery project, reportedly organised by a new US venture called America First Refining (AFR), illustrates the answer. Projects of this scale require several layers of preparation—financing frameworks, land acquisition, intake and offtake agreements, tax incentives, and regulatory approvals. AFR appears to have assembled much of this political and financial architecture. What remained essential, however, was execution credibility: a partner capable of designing, building, and operating a complex refining syst...

Open any business news app today and the employment headlines seem contradictory. On one side, India's IT sector is visibly pulling back on recruitment, mainly because of the rapid automation of IT (and other office-based) services by advanced agentic AI tools, like Anthropic's Claude Cowork. The sharp drop in Indian IT companies' market valuations last month was precisely because of this fear. On the other side, manufacturers, energy companies, defence contractors, and infrastructure builders are struggling to find engineers — not because engineers don't exist, but because the engineers they need don't quite exist yet. The Manpower Group 2026 Talent Shortage Survey (released a few days back), covering 39,000 employers across 41 countries including 3,051 in India, puts a sharp number on this: 82% of Indian employers report difficulty finding the right talent. That places India among the most talent-constrained markets in the world, worse than the global average of ...

Structural Crisis, Not a Temporary Disruption  The ongoing war in West Asia has disrupted global energy supplies. Most recently, Qatar stopping it's natural gas production has given rise to a potential global gas crisis. For India, this vulnerability is not new. India produces about half of its total gas requirement from domestic fossil sources. The remainder is imported (about half of which from Qatar), leaving industrial supply chains, individual and commercial consumers, and the agricultural sector simultaneously exposed to the same external shock. The consequences are already visible. The government has ordered supply cuts to industrial consumers — steel, ceramics, glass, paper, and food processing among them — while prioritising piped natural gas for homes and commercial establishments, compressed natural gas for vehicles, and gas feedstock for fertilizer production ahead of the Kharif sowing season. These are triage decisions, not policy choices. They signal a supply position...

Government and industry leaders increasingly speak of an AI stack — chips, cloud, models, and applications — as the foundation of technological sovereignty. The ambition is clear: domestic compute capacity, indigenous foundation models, and national applications together reduce strategic dependence. Yet a structural asymmetry persists. While the AI stack is being articulated layer by layer, an equivalent cybersecurity stack is rarely defined with the same architectural clarity. This omission is no longer theoretical. It is operational.  Yesterday, Amazon Web Services (AWS) confirmed that two of its facilities in UAE were directly struck by drones, causing structural damage, power disruptions, and additional water damage from fire suppression efforts. A third facility in Bahrain was also affected by a nearby strike. The strikes led to widespread service outages, including elevated error rates for services like Amazon S3, EC2, RDS, Lambda, and others, with AWS warning of prolonged r...

Artificial intelligence is no longer simply another technological wave. It is rapidly becoming a general-purpose cognitive infrastructure, collapsing the boundary between knowledge production and real-world deployment. Across sectors, AI is shortening the half-life of expertise: models evolve faster than textbooks, and applied knowledge shifts more quickly than curricula can traditionally accommodate.  In such a landscape, the question facing universities is not whether AI should be taught. The deeper question is how universities must reorganize themselves when intelligence itself becomes computationally augmented. Adding AI electives or partnering with online platforms may signal responsiveness, but these remain surface-level adjustments. If AI is infrastructural, the response must be structural. Universities must move beyond offering AI as a specialized track and instead embed it within the epistemic core of each discipline. The challenge is not “AI education”. It is disciplinary...