How to Get Better at AI by Asking AI

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For most of my working life, the first step of any task began with a blank slate: an empty Google Doc, a fresh email, or a new Excel spreadsheet. From researching to writing formulas, the banalities of every stage of construction fell to me. AI made that process faster, but the way I accomplished it wasn’t all that different. I started with a new chat and prompted it over and over until the output matched my unspoken definition of “done.”

When I started at Every in May, I was still working that way. When I needed to issue contractor payments, I worked from one chat thread, prompting sequentially to surface agreement terms, approve payment, and send email confirmations that payment had been issued.

Things look very different today. Last week, I needed to verify the cost of purchasing equity for an employee across multiple grants, strike prices, and vesting schedules. Rather than tackle this complex task in a single thread, I split the project among several subagents that coordinated independently to verify information on signed agreements, run the math, double-check it and flag discrepancies, and return a draft of a Slack message that I could approve with a simple “yes.” That work ran on skills, orchestrator threads, context packets, subagents, MCPs, and computer use. It’s a veritable alphabet soup of technical terms that I was previously sure could only be understood and deployed by Highly Technical People, yet I now find myself reaching for these techniques daily, helping me work faster, with better and more precise results that I can be confident about.

I was prompted to make the shift from a tweet. Katie Parrott tweeted in June that she had asked Codex where she fell on Mike Taylor and Laura Entis’s guide to “Eight Levels of AI Adoption,” and I saw an opportunity to better understand my place in the ecosystem. The guide is a framework that maps a progression from basic chatbot use to full agent orchestration, with each level delegating more work—and trust—to AI. Codex placed Katie at Level 5 (building workflows that make an agent’s output consistent and reliable), with the beginnings of Level 6 (an agent that works proactively in the background without waiting for a prompt).