The high cost and scarcity of tokens are ending the 'subsidy era' and making widespread experimentation more difficult.
The rapid, sometimes haphazard implementation of AI agents is creating 'agent debt,' analogous to technical debt, which could cause future performance issues.
Companies are struggling with the shift from seat-based to usage-based pricing, with some burning through annual AI budgets in months.
Opportunities Identified
Significant investment and growth are flowing into the AI inference layer, creating opportunities for companies that optimize model deployment and routing.
The demand for cost-effective performance is driving innovation in smaller, more efficient models that can compete with larger, more expensive ones.
Periods of 'slowdown panic' create an opportunity for knowledgeable and competitive individuals to get ahead while others pull back.