The AI Transition: Building on Quicksand
We're deploying artificial intelligence at breakneck speed, but we're doing it on infrastructure designed for a different era—one that prioritized velocity over security, market capture over resilience. As AI systems become deeply embedded in critical operations worldwide, three uncomfortable truths emerge: our foundational infrastructure is dangerously inadequate, corporate concentration is creating systemic risk, and we're eliminating the very entry points that build organizational knowledge.
The path forward isn't predetermined. It requires confronting these realities now, before the decisions we're deferring become crises we can't contain. And it offers concrete actions for those already using AI—choices that shape whether we build toward resilience or fragility, distribution or concentration.
This series explores each of these critical challenges and examines the overlooked opportunities that could help us build a more resilient future with AI.
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Building on Quicksand
The accelerating deployment of AI reveals three critical challenges: our infrastructure is inadequate, monopolization threatens resilience, and we're eliminating entry-level career pathways. But the same maintenance backlogs that companies defer also represent an overlooked opportunity—if we choose to use AI to address them rather than eliminate the workers who would learn from them.
The Infrastructure Debt Crisis
Think of AI deployment as running bullet trains on century-old rails. We've built sophisticated AI systems but we're running them on IT infrastructure designed when security was an afterthought and 'move fast and break things' was gospel.
The New Gilded Age
We've been here before. At the end of the 19th century, large industrial corporations captured key economic sectors and the political systems meant to regulate them. Today's situation doesn't just rhyme—it replicates the same logic with a modern twist. Instead of conquering Africa, concentrated capital seeks to conquer cyberspace through what Silicon Valley explicitly calls 'blitzscaling'.
The Entry-Level Extinction
AI is decimating entry-level employment globally. U.S. programmer employment fell 27.5% between 2023 and 2025. Entry-level hiring at the 15 biggest tech firms dropped 25%. This isn't just an employment problem—it's an institutional knowledge crisis. Organizations can't promote from within if there's no 'within' to promote from.
The Overlooked Opportunity
Healthcare, legal systems, and infrastructure all accumulate vast maintenance backlogs that never get prioritized. AI could address these backlogs while providing entry-level workers meaningful projects that build expertise. This is genuine productivity—maintaining employment while increasing value creation—not wealth extraction.
Choosing Resilience Over Concentration
The path we're on leads toward a few dominant AI systems, controlled by a handful of corporations, through which all economic activity must flow. Digital feudalism where the appearance of choice masks monopoly control. It's not impossible. It's not even improbable. It's the direction current incentives point toward—the logical endpoint of a venture capital system explicitly designed to create winner-take-all monopolies.