AI Infrastructure

The concept of Context Graphs has rapidly captured the industry's imagination. The thesis is that the next trillion-dollar enterprise platforms will not be systems of record for data, but systems of record for decisions. But who actually captures this opportunity? The answer is hiding in plain sight—in the agentic tools that are already operating in the wild, generating decision traces every second.

The conversation around context graphs has exploded, but the term itself has become a Rorschach test. This is not about adding memory to your agent—it's about rethinking our assumptions about data, time, and organizational knowledge. The Two Clocks Problem reveals why we're missing half of time in enterprise systems, and why this is fundamentally a representation problem, not a database problem.

After reading Jaya Gupta's post about Context Graphs, I have not been able to stop thinking about it. For me, it did something personal: it gave a name to the architectural pattern I have been circling around in the agentic infrastructure discussions on this blog for the past year. Gupta's thesis is simple but profound—the last generation of enterprise software created trillion dollar companies by becoming systems of record. The question now is whether a new layer will emerge on top of them: a system of record for decisions.

If 2024 was the year of AI experimentation, 2025 was the year of industrialization. The speculative boom around generative AI has rapidly matured into the fastest-scaling software category in history, with autonomous agents moving from the lab to the core of enterprise operations.

The enterprise AI landscape is at a critical juncture. We have powerful general-purpose models and a growing ecosystem of tools. But we are missing a crucial piece: a standardized, portable way to equip agents with the procedural knowledge and organizational context they need to perform real work.

The era of AI experimentation is over. What began as a speculative boom has rapidly industrialized into the fastest-scaling software category in history. Enterprise spending on generative AI skyrocketed to $37 billion in 2025, a stunning 3.2x increase from the previous year.