AI Operations Role

A dedicated person who automates repetitive tasks across the organization using AI

Dan Shipper
The AI-native startup: 5 products, 7-figure revenue, 100% AI-written code.

AI Operations Role

"We have a head of AI operations. She's just constantly building prompts, and building workflows... that I and everyone else on the team are just automating as much as possible." - Dan Shipper

What It Is

The AI Operations Role is an organizational function dedicated to identifying and automating repetitive tasks across a company using AI tools. Rather than expecting every employee to find time to build their own automations (which rarely happens when people are fighting daily fires), a dedicated AI Ops person works with teams to discover automation opportunities and implement solutions.

This role combines process thinking with tinkering enthusiasm. The ideal AI Ops person understands workflows deeply, gets excited about AI possibilities, and can translate repetitive manual work into prompts, automations, and tools that others will actually use.

How It Works

The role operates through a continuous cycle:

1. Discovery Sessions

  • Meet regularly (weekly) with team members and leaders
  • Identify tasks that are done repetitively
  • Maintain a running to-do list of automation opportunities

2. Solution Building

  • Create prompts that encode taste and standards
  • Build no-code automations and workflows
  • Develop tools that fit naturally into existing work patterns

3. Adoption Support

  • Train people to use new automations
  • Follow up to ensure tools get used
  • Iterate based on feedback and changing needs

At Every, their AI Ops lead focuses heavily on the editorial operation, where tasks like copy editing can now be handled by Claude Opus with a style guide. The prompts created by AI Ops can also transfer across functions—the same style guide prompt used by editors was adapted into a Claude Code command that engineers use to check copy in their code.

How to Apply It

  1. Hire for curiosity over credentials - Look for someone who wants to tinker, loves AI, and understands process. Background in operations, content, or similar fields can help.

  2. Start with leaders - Have the AI Ops person shadow executives and high-output team members first. Their repetitive tasks tend to have the most leverage.

  3. Make it a real role - Don't make this a side project. Give someone dedicated time and accountability for driving AI adoption.

  4. Focus on behavior change - Building the automation is half the job. Getting people to actually use it is the other half. Plan for adoption, not just creation.

  5. Choose a department to start - Don't try to automate everything at once. Start with one function (like editorial or customer success) and expand from there.

When to Use It

  • When your company talks about being "AI-first" but adoption is slow
  • When people are too busy doing work to optimize how they work
  • When you have repeatable processes that vary slightly by person (indicating undocumented best practices)
  • When you want to push taste and standards to the edges of your organization
  • At any company size—Every has 15 people and benefits enormously from this role

Source

  • Guest: Dan Shipper
  • Episode: "The AI-native startup: 5 products, 7-figure revenue, 100% AI-written code."
  • Key Discussion: (00:30:16) - Explaining the AI operations role and how it works at Every
  • YouTube: Watch on YouTube

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