The OpenAI Hype Cycle, Microsoft's Game Pass Failure, Verizon's Satellites (stratechery.com)

The piece argues we’re moving past the OpenAI “hype cycle” peak into a phase of sober reassessment: impressive foundation models and demos remain transformative, but commercial realities—costs of inference, prompt engineering limits, safety and hallucination risks, and integration effort—are forcing customers and developers to recalibrate expectations. That shift matters because it refocuses the AI/ML community on measurable ROI: model specialization, tooling for observability and guardrails, efficient fine-tuning and quantized on-device inference, and clear evaluation metrics rather than headline-grabbing capabilities. At the same time, two business/infrastructure stories illustrate the shape of that recalibration. Microsoft’s recent push to layer AI into subscription gaming and cloud services (the “Game Pass” model) has underperformed versus expectations, highlighting hard monetization and retention challenges when heavy compute raises unit costs and user value isn’t yet clear. Verizon’s satellite investments point to another axis of change: distributed connectivity and edge compute for low-latency inference and wider coverage, but they come with trade-offs in bandwidth, scheduling, regulatory complexity, and economics. Together these developments push the field toward pragmatic engineering—cost-aware architectures, edge/cloud hybrids, model compression and modular AI stacks—and a business focus on sustainable, measured deployments over perpetual hype.