Cover Image for The AI-Integrated Chief of Staff: Essential Skills for the Post-AI Workplace (feat. DappleAI)
Cover Image for The AI-Integrated Chief of Staff: Essential Skills for the Post-AI Workplace (feat. DappleAI)
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The AI-Integrated Chief of Staff: Essential Skills for the Post-AI Workplace (feat. DappleAI)

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Title: The AI-Integrated Chief of Staff: Essential Skills for the Post-AI Workplace

Host: Chief of Staff Roundtable (CSR)

Guest: Ebony Belhumeur, Founder & CEO @ DappleAI

Being a Chief of Staff means switching gears all day long. One minute you're handling a crisis, the next you're in a sensitive 1:1, and the mental residue from the last task often bleeds into the next one. It's exhausting, and it quietly wears down your focus, memory, and judgment.

That's the problem right in front of you. But it opens up something bigger.

The Chiefs of Staff who get good at managing this constant switching are the same ones best set up to get real value from AI. They can spot the workflows where AI actually helps, put the right tools to work, and keep improving the results over time without cutting corners on quality. Getting better at mode-switching is where you start. Using AI to create real leverage across your work is where you end up.

Join us for a practitioner-led roundtable on what we're calling the "Multimodal Operator's Advantage". We'll look at how AI can help you shift into the right headspace faster, and how to turn those habits into systems that keep paying off.

This isn't a webinar. Everyone contributes. We'll work through five topics together in small-group breakouts:

  • How to keep your momentum through a chaotic day

  • How to switch cleanly between triage, diplomacy, and strategy

  • Which workflows and tools, including DappleAi, actually work

  • How your environment (startup vs. enterprise) changes the playbook

  • What's changing in 2026 that you need to pay attention to

Along the way, we'll dig into the questions every operator is wrestling with: Where can AI actually help without creating risk or hurting quality? Once you find a good use case, how do you roll it out, measure it, and keep making it better? And what should you actually be tracking, time, quality, cost, trust, or output?

You'll walk away with practical approaches you can use right away, and a clearer sense of how to make AI work for you, starting with the parts of your job that drain you most and extending to the places where AI can really change the game.

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