AI

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.

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.

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'.

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.

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.

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.

We submitted an initial request for a sonnet about war's role in peace and received DeepSeek's first response, which included both its prompt analysis and reasoning process.

This section shows Claude's systematic approach to verifying iambic pentameter in the final sonnet. The AI provides a detailed syllable-by-syllable analysis, marking stressed and unstressed patterns to demonstrate technical compliance with traditional sonnet form.

A curated selection of potential titles for the sonnet exploring how peace emerges from conflict, ranging from metaphorical to direct, with analysis of each option's thematic strengths and a recommendation for the most fitting choice.

The final sonnet after all revisions.

We submitted an initial request for a sonnet about war's role in peace and received DeepSeek's first response, which included both its prompt analysis and reasoning process.

The initial eighteen-line response exceeded the sonnet's fourteen-line requirement. The follow-up tests whether the AI can identify this error.

Since the problem remains undiagnosed, we ask another indirect question to prompt analysis of the response's structure.

We take a more direct approach since the AI hasn't recognized that its response exceeds the fourteen-line sonnet format.

Even though it finally identified that the response was too long, a prompt is required to request to correction to 14 lines.

The final fourteen-line response deviates too much from iambic pentameter, requiring review.