Field notes.
The company agentic OS architecture
Most AI projects end as brittle demos because they automate on stale data. The fix is not another agent - it is an operating system built on two ideas - a pipeline for structure and a dual-process control model for doctrine - that keeps data true in real time, gates every operation by confidence, and compiles proven reasoning into cheap deterministic reflexes.
3-Layers of AI automation
A practical three-layer model for building AI automation that compounds in value instead of rotting - a shared foundation, vertical business cases, and an orchestration layer that ties them together.
Communication patterns of AI agents
Five ways AI agents talk to each other and to your systems - single agent, pipeline, supervisor-worker, parallel fan-out, and the marketplace - with the trade-offs and the context cost of each.
How to quantify the benefits of AI
A CFO-grade framework for measuring AI ROI - baseline before you build, instrument the workflow, and report against the map in real time, so value is visible rather than asserted.