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Rafsan Bhuiyan is a trailblazing U.S. Army veteran turned enterprise AI strategist, whose journey from battlefield discipline to cutting-edge innovation has redefined revenue operations for global businesses. As the Founder and CEO of OrionQ, he leads the charge in developing agentic AI platforms tailored for telecom and automotive dealerships—unlocking billions in untapped revenue through seamless automation and CRM integration. Under his vision, OrionQ isn’t just software; it’s a force multiplier that empowers sales teams to scale smarter, faster, and more humanely.
A proud graduate of Colorado Technical University with a deep-rooted passion for data science and software development, Rafsan has channeled his technical prowess into real-world impact. From overcoming gritty challenges in the POS service industry to coaching leaders on AI adoption, he’s built a reputation as one of the top voices in artificial intelligence. His insights have graced platforms like Authority Magazine, where he recently shared C-suite wisdom on balancing AI’s power with human intuition, and his Medium writings inspire aspiring data scientists to pursue fulfilling, productive lives.
Beyond the boardroom, Rafsan is a devoted dad, an avid growth coach, and an unyielding advocate for ethical AI that amplifies—not replaces—the human spark. Whether dissecting the $3 trillion enterprise revenue opportunity or sharing war stories from his military days, Rafsan’s blend of grit, geekery, and genuine curiosity makes him the ultimate podcast guest for anyone navigating the AI revolution. Tune in as he demystifies the future of work, one breakthrough at a time.
This week, Brian Gracely joins to dissect strategic choices made by Broadcom, Docker, Netflix and Intel. Plus: The AI Bifurcation—are models commodities or product pillars?
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Special Guest: Brian Gracely.

Spotify has introduced the Experiments with Learning (EwL) metric on top of its Confidence experimentation platform to measure how many tests deliver decision-ready insights, not just how many “win.” EwL captures both the quantity and quality of learning across product teams, helping them make faster, smarter product decisions at scale. The outcome must support one action: ship, abort, or iterate.
By Olimpiu Pop