AI operations
The interesting question is not whether AI can do the task. It is which tasks are safe to hand over, and what has to stay gated behind a person.
The problem it solves
Small teams lose their week to work that is structured, repetitive, and too consequential to do carelessly — catalogue upkeep, reporting assembly, research passes, moving the same data between four systems.
The usual fix is to hire, which changes the economics. The other usual fix is to automate carelessly, which produces confident errors at speed.
What it includes
- 01
Catalog and data pipelines
A defined source of truth that reconciles against the live system, with dry runs before any write. Removals are never automatic.
- 02
Reporting automation
Live dashboards on edge hosting, replacing the assembled monthly deck — which is also what buyers increasingly expect instead of a PDF.
- 03
Research workflows
Multi-agent research passes used inside real delivery, where they have changed strategic recommendations rather than just summarising sources.
- 04
Governance, written down
Least-privilege access, secrets kept out of prompts and source control, staged environments, versioned artifacts, and explicit authorisation before any production write.
- 05
A named human owner
Nothing consequential — financial, legal, employment, medical, or client-facing — is decided without a person approving it.
When this is the right call
Right when there is a repeatable operational process with a clear source of truth. Wrong if the process is not yet defined — automating an undefined process just makes the confusion faster.
- 01 Marketing operating system Install the plan, the measurement, and the review rhythm a marketing team runs on.
- 02 Performance advertising Run paid search and social against business outcomes, not channel metrics.
- 03 Websites & ecommerce Ship sites that load fast, convert, and can be measured.
- 05 Brand & positioning Settle what you sell, to whom, and why it wins — then hold the line.