Building Agent Infrastructure for a Months-Long Half-Life

The Reality of Rapid Obsolescence

Traditional enterprise infrastructure typically maintains a three-to-five-year half-life, allowing teams to commit to a stack and optimize deeply. Agentic systems, however, operate on a half-life measured in months. Approaches that were considered industry standard just one year ago—such as graph-based agent traversal—have already been superseded by newer patterns like recursive agentic planning and sandbox-based code execution. This volatility creates a high risk of morale degradation, as engineers often find their work obsolete shortly after shipping.

Strategies for Adaptable Engineering

To manage this pace of change without sacrificing stability, organizations must treat adaptability as a core engineering requirement rather than a failure of planning.

• Normalize change as a cultural standard: Explicitly communicate to teams that architectural pivots are expected and do not reflect poor initial decision-making. This reduces the psychological friction associated with rebuilding systems.
• Implement modular abstractions: Build agentic systems with clear interfaces that decouple the orchestration layer from the underlying model or retrieval logic. This allows teams to swap out components as better technologies emerge without rewriting the entire product.
• Gate migrations with eval sets: Avoid chasing trends or new papers unless they demonstrate measurable improvements. Establish a consistent evaluation suite that measures cost, speed, quality, and capability. Only initiate a migration if the new approach outperforms the existing one on these specific metrics.
• Select vendors based on their history of adaptation: When choosing third-party platforms, prioritize vendors that have successfully reinvented their own technology stacks multiple times in the last year. A vendor's ability to navigate the current pace of AI research is a better predictor of long-term utility than their current feature set.

The Six-Month Review Cycle

Box now mandates a formal review of all AI technology every six months. This cadence acknowledges that the best approach today will likely be suboptimal by the next cycle. By institutionalizing this review, the organization avoids the trap of long-term vendor lock-in or technical debt accumulation, ensuring that the infrastructure remains competitive as the state of the art shifts.