Read closely.
Think practically.
Research on how organizations work, what happens when their systems fail, and what it takes to change them.
Reference reads on systems under stress.
Notes on the primary research shaping the next eighteen months.
Working notes on papers from OpenAI, Anthropic, Transformer Circuits, and Stanford CGRI, read for what they imply about deploying agents and rebuilding workflows in real organizations.
One reading per year, since the year we started.
We read the major firms' tech outlooks the way an operator does. Looking past the trend lists for the operating-model gap that determines who actually captures the gain. One synthesis per year, 2021 through 2025.
We read the original research before recommending a change.
Our edge is that we read the source material directly and regularly, with the question every operator actually has in mind: what does this change about how the work gets done?
AI labs, end to end
OpenAI, Anthropic, and the rest. Read across their product announcements, interpretability work, and formal research. The leading indicator for what's about to be deployable in client workflows, and what's about to be unsafe in them.
Bain, McKinsey, Deloitte. Every year, end to end
Read with an operator's eye, not a strategist's. We look past the trend lists for the operating-model gap that determines who actually captures the gain.
Case studies we keep returning to
Some operating-model lessons travel decades. We catalog the historical scale events (Tesla 2018, WeWork 2019, others) that still shape how we design for clients today.