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ARTICLES · YOUR DUE DILIGENCE

Read, then decide.

Decision guides and engineering notes on choosing, scoping, building and running AI systems that keep working in your daily operations, long after the launch.

  1. ChoosingWhich broken workflow should become software first
  2. BuildingIs your data good enough to start building?
  3. RunningWhat to demand from whoever owns your system

Strategy

Executive signs a project proposal at a lobby counter while an engineer hesitates

You are approving a build nobody has checked

The proposal has a number, a timeline and a team who believe in it. Before you approve it, check whether anyone independent has examined the decision it changes, the data it runs on and the systems it must plug into.

An operations director checks a printed report against her laptop at a desk in an open-plan office

Strategy5 min read

The process that was too small to fix

For years your broken reconciliation was too small to justify a project. The cost of a small, well-specified piece of software has fallen far enough that the answer has expired, and a whole class of that work is now worth doing.

Two colleagues writing down what success looks like in a notebook

Technical5 min read

Nobody wrote down what success would look like

You approved a project to fix a workflow, and months later nobody in the room can say whether it worked. That is a writing failure, not a technology failure: nothing in the specification could be graded pass or fail by an outsider.

A chief financial officer explains the month's results to the chief operating officer in an office seating area, the trend on a wall screen behind them

Strategy5 min read

Measure AI impact by decisions, not accuracy

Model dashboards show accuracy and uptime while the business sees nothing change. This article shows where AI value actually escapes, and how to measure the 2 levels that decide it: outcomes and their business impact.

Omar Trejo checks what the record shows at two monitors in a glass-walled room

Strategy5 min read

Who signed off, and what the record shows

After an incident, you need to know who approved the action and what happened. A mail thread and somebody's recollection of a call are not a control. Build those answers into the record before adding AI to a process.

An engineering director holds a printed code change and asks a senior engineer to explain it at his desk

Strategy5 min read

Your delivery metrics look healthy while risk grows

Your DORA metrics, deployment frequency and recovery time, look healthy while teams quietly lose their hold on the systems they ship. AI makes this drift faster and harder to spot, so pair delivery metrics with comprehension.

AFTER THE READING

Apply the guide to your case.

Bring the decision you are weighing. By the end of the call, what fits your workflow and what comes first are clear.

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Fifteen minutes with Omar.