Aaron Levie has been on the podcast twice before. After we published our context graphs thesis, he wrote a response - so we invited him on to continue the conversation.
A context graph is institutional memory for how an organization actually makes decisions: not how the process doc says it should, but how it works in practice.
Enterprise software is very good at recording outcomes - the final price, the approved discount, the escalated ticket - but not the reasoning behind them. Which exceptions applied? What precedent mattered? Who approved what, and why?
We call these missing records decision traces. Over time, they accumulate into a context graph: a living, queryable map of how an enterprise actually makes decisions, stitched across systems and time so precedent becomes searchable. We think the companies that capture that layer will define the next generation of enterprise software.
Aaron read the piece and joined us to push it further. We get into how the services as software opportunity unfolds as agents scale, and what it actually takes to move them out of the sandbox and into production.
Chapters: