如何通过向 AI 提问来提升 AI 使用能力
How to Get Better at AI by Asking AI
Every 作者分享用五个提示词将自己从单次对话推进到把整个项目交给智能体团队的经验,其工作流已用到 skills、orchestrator threads、context packets、subagents、MCPs 和 computer use。
Five prompts that took me from one-off chats to delegating whole projects to teams of agents
Oct 2, 2026 · 10 min read
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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).
来源:Every:最新文章 · every.to