Bessemer Venture Partners just published their AI Infrastructure Roadmap for 2026, and one of the five frontiers they're betting on is the exact problem we've been building Bigspin to solve: the evaluation and observability gap for agentic AI in production.

Their framing lines up closely with ours. Traditional monitoring watches completion rates, latency, and thumbs up or down. But agents don't fail that way. They fail invisibly with things like confident wrong answers, gradual drift from the user's actual intent, plausible-sounding misunderstandings that users don't push back on. These failures don't show up as error codes, or user complaints, or as signals in the dashboard.

Bessemer pulls directly from our Invisible Failures research, citing our finding that roughly 78% of AI failures are invisible, and naming three of the archetypes we identified: The Confidence Trap, The Drift, and The Silent Mismatch. These patterns persist in 93% of cases even as underlying models get more powerful, because they come from interaction dynamics rather than raw capability.

They name Bigspin as part of the new infrastructure layer addressing this: real-time production monitoring of agent outputs against golden datasets and user feedback, beyond pre-deployment testing alone.

This is the instrumentation gap, and it's now firmly on the industry roadmap. Read Bessemer's full piece here: https://www.bvp.com/atlas/ai-infrastructure-roadmap-five-frontiers-for-2026