AI Leader Allie K. Miller Uses Claude Code to Automate 10+ Hour Workdays

Allie K. Miller, one of the most influential voices in artificial intelligence, operates with a simple philosophy: ‘By the time you wake up, your AI should have already been working for you for hours.’

Miller, formerly the global head of machine learning for startups and venture capital at Amazon Web Services, is now a leading AI consultant and influencer with over 1.6 million followers on LinkedIn. Through her company Open Machine, she advises major enterprises and business leaders—including teams at OpenAI, Google, Anthropic, and Warner Bros. Discovery—on AI adoption strategies. In 2025, Time named her one of the 100 most influential people in AI.

How Miller Uses Claude Code to Automate Her Workflow

Miller now relies heavily on Claude Code, Anthropic’s agentic coding system, to manage her extensive workload. She maintains multiple instances of Claude Code running simultaneously in separate terminals. These instances have access to her filesystem, enabling them to autonomously complete tasks on her behalf.

To train Claude Code for specific workflows, Miller utilizes Skills, a feature that allows the system to execute and repeat multistep processes. Among her automations:

• Overnight email summaries: A report generated each morning highlighting urgent emails received overnight.
• Daily morning briefings: A review of her calendar that recommends recharge times and blocks deep work slots.

  ‘It’ll tell me, ‘You have four different interviews or six client meetings,’ so I’ve gone ahead and blocked out 30 minutes tomorrow for deep work.’

Another automation streamlines her social media workflow. Whenever Miller edits a social video using CapCut—the video editing app owned by TikTok—and exports it to a specific folder, an automated process triggers. This system then generates a transcript, social media post, and thumbnail screenshot for the video.

Building AI Solutions Tailored to Your Workflow

Miller advocates for a hands-on approach to identifying AI solutions that fit individual needs. Her recommended process:

1. Have your chosen AI model interview you about your work.
2. Ask the AI to identify areas where efficiency or smoothness could be improved.
3. Prompt the AI again with: ‘Make these ideas more proactive, more responsibly autonomous, and more action-forward.’

With this prompt, Miller says, users can begin developing their own AI-driven automations without extensive technical expertise.

Testing Content and Decisions with Synthetic Personas

Miller applies AI not only to workflows but also to content creation and decision-making. When drafting posts for her newsletter, she runs drafts through eight synthetic personas representing different audience demographics.

‘I’m not trying to appease all eight and write a happy-go-lucky version of the newsletter,’ says Miller, ‘but I want to make sure I didn’t miss something important. I want to make sure that a parent reading [the newsletter] isn’t completely misunderstanding my take on something.’

She employs a similar strategy for major career decisions. Miller has built a self-described ‘AI boardroom’, complete with six synthetic personas that weigh in on significant company issues. She rotates which six personas participate depending on the topic at hand.