Shane Butler

How to build a reliable AI analyst is the same list I would use to train a person. Six things, and what each one becomes in the system.

We ran 70 tests on OpenAI's data agent. It caught almost every statistical trap and failed the same organizational errors people do. Where I would use it and where I would not.

Metrics that measure nothing and change nothing burn the reason senior ICs chose the work. The two questions that stop it, and the three kinds of work that fail them.

We read more than 8,000 live US postings across data roles and industries. Where AI is already table stakes, where it is barely asked for, and what to learn depending on the job you want.

The failures we keep hitting while building AI analysts for real companies. Not the demo failures, the ones that show up in week two.

SMEs are building AI products that pass their own evals and fail the users they were built for. Five things that keep an eval honest.

The easy answer is the final decision. That is not enough. Four things a person has to own all the way through the work.

The people who get the raises are the people who get the big projects. Five habits that get you assigned to them.

Analytical thinking was never reserved for a title. The tools built the barriers, and the tools are taking them down again.

Before you build AI for customers, before you build a product, before you pitch your manager on an AI strategy: build an AI version of you. It's the highest-return investment you will make in AI, and it's not close.

The 'augment, not replace' line is over. AI crossed the line where it does the whole data job. Here's what that means and five paths forward for data professionals.

I manually validated every number my AI analyst produced against my own SQL. Found out I was the one who had it wrong. Then I started noticing what the correction log was turning into.

How we designed a single markdown file that regrows an entire multi-agent AI data analyst from scratch. Architect debates, builder agents, and the blurry line between prompts and specifications.

No code. I built an agentic data team that delivers full analyses in minutes instead of weeks.