AI for Business Leaders

"Quality over quantity. It is never about the number."Albert Chun is the Founder of AI Circle — a vetted community for business leaders, founders, and operators building at the frontier of AI. Before AI Circle, Albert was a teacher in two of the country's poorest congressional districts, a Harvard grad student, an insurtech operator who scaled from 3 reports to managing 211 people across 13 M&As, and a senior leader at Invisible Technologies — where his team helped train what became the #1 open source frontier model in the world.In this episode, Dennis and Albert get into what it actually looks like inside an AI company building on the frontier, why the AI ecosystem is over-indexed on credentials and under-indexed on experience, and the deeper human problem AI Circle is really solving.In this conversation, we cover:Why Albert walked away from C-level offers at triple the pay to take an AI role that "felt like the A+ problem in the A+ space of the industry"What training a frontier model actually looks like day-to-day — and why reading one arxiv paper can put you ahead of almost everyoneHow Albert thinks about AI ROI when model outputs are stochastic, loss functions don't map cleanly to revenue, and causation is a finger in the windThe gatekeeping problem in AI — why polysyllabic jargon like "chain of thought reasoning" is really just "me sharing what I thought and why I did it"Why Andrew Ng and Andrej Karpathy are both building education — and Albert's theory that education, not GPUs, is the biggest bottleneck in AI accelerationWriting in public since Xanga and Friendster, the story of a broken pair of glasses that led to a $250K donation, and why corporate "stay in-house" advice was the wrong tea leafWhy AI Circle is bootstrapped, not VC-backed — and the fight story from sophomore year that shaped how Albert thinks about community size foreverThe deeper problem AI Circle is really solving: community, connection, and relationship as life gets harder, and friend circles get smallerIf you are a business leader trying to separate real AI signal from buzzword noise — or a founder thinking about how to build trust-based community in an era of vanity metrics — this is one of the most honest conversations on the pod.

What separates a genuine AI commerce startup from AI theater? Gary Benerofe is the General Partner of Mu Ventures, an early-stage venture capital fund investing in the future of commerce. With over 20 years deploying capital across stages and asset classes, Gary brings a unique combination of operational expertise and investment acumen — what he calls "operating capital."In this conversation, we cover:What "operating capital" means and why it matters more than just a checkThe pattern recognition behind picking venture-backed founders — magnetism, talent attraction, and repeat founder advantageHow Mu Ventures expanded from pure commerce enablement to any transaction that removes frictionOpenAI's instant checkout vs. Google's agent payments protocol — two completely different approaches to agentic commerceWhy Gary's AI red flag is when the AI IS the thing, rather than AI making the thing betterThe return to grassroots brand building as CAC rises and attribution breaks downTikTok Shop, experiential marketing, and why hand-to-hand combat is backWhy the next 5 years of commerce infrastructure will be defined by buyer-agent-to-buyer-agent transactionsThe real etymology of Mu Ventures (hint: it involves Yale, quarters, and beer)If you're a founder, operator, or investor trying to separate signal from noise in the AI commerce landscape, this is the investor's lens you need.

James Raybould is the former SVP and General Manager of Turing Intelligence, the enterprise consulting and AI deployment division of Turing — a company valued at $2.2 billion that partners with frontier AI labs like OpenAI to help enterprises transform AI from proof-of-concept into proprietary intelligence.Before Turing, James spent 13 years at LinkedIn, where he played a key role in two major acquisitions: the $1.6 billion Lynda.com deal that became LinkedIn Learning and the Glint acquisition that brought employee engagement tools into the platform.In this episode, Dennis and James dig into:What it actually means to be "AI forward" — not as a buzzword, but in daily practice (from kid's homework tutoring to athletic training plans)The #1 pattern that separates enterprises that succeed with AI from those that get stuckWhy picking a narrow, metrics-driven use case beats trying to "AI-ify" an entire functionHow AI is shifting from incremental efficiency gains to a complete rewrite of how companies operateThe coordination cost problem — and why removing human bottlenecks accelerates everythingWhy the gap between an idea and a functioning product is now measured in minutes, not monthsThe people side: how leaders can help their teams move past fear and embrace AI as an amplifierWhether you're a founder evaluating where to deploy AI first, or an executive trying to get your organization to move faster — this episode delivers practical, no-fluff insights from someone who's seen both sides: building AI products and deploying them inside the enterprise.Connect with James on LinkedIn: linkedin.com/in/jamesraybouldLearn more about The Other Group: www.getothergroup.com

Charlie Ninegar is the COO of DSS Games, a fast-growing tabletop card games company on a mission to get people off their phones and back around the table. In this episode, recorded live at eTail Palm Springs, we dig into how DSS Games stole market share while their category actually shrank through relentless content quality, brand discipline, and a team-first approach to AI adoption.Topics covered:Growing in a shrinking market through content-first strategyTikTok-first organic content: from 1,200 videos/year to fewer but higher-impactCustom GPTs as a practical first step for AI adoptionChange management: why some young employees resist AI (and what to do about it)The coming shift from "no AI in creative" to AI-assisted brand contentWhy the AI arms race looks different outside the tech bubbleSign up at www.getothergroup.com for early access to episodes, frameworks, and insights we don't publish anywhere else.

In this insightful interview, Iman from eTale shares how his apparel brand adapted to supply chain disruptions, leveraged AI for rapid testing and inventory management, and built customer loyalty through experimentation. Discover strategies for agility, AI integration, and maintaining innovation in a challenging market.Supply chain agility and on-demand inventoryAI-driven rapid testing and decision-makingBuilding customer loyalty and increasing LTV

In this interview, Angela Clark, VP of Digital at Patagonia, shares insights on how the brand navigates market disruptions, leverages storytelling, and integrates AI to enhance customer engagement and long-term brand loyalty.Patagonia's response to tariffs and market disruptionsThe role of storytelling in brand loyaltyAI and personalization in retail

Matt Dornfeld is the Head of Global AI Go-to-Market Strategy at Commerce (formerly BigCommerce), where he's architecting the AI GTM organization inside one of the largest open SaaS commerce platforms in the world. In this episode, we get into what it actually takes to build an AI-powered go-to-market engine from the ground up — the architecture, the people challenges, and the frameworks that separate real AI strategy from buzzword bingo.In this conversation, we cover:What "agentic commerce" actually means and why product discovery starts with a prompt, not a homepageThe centralized data architecture that makes 1+1=10 with AIMatt's build vs buy framework for enterprise AI decisionsForward deployed engineers — why they beat traditional consultantsThe rebrand from BigCommerce to Commerce and the category strategy behind itChange management and the people challenge of AI adoption inside a 500+ person orgThe "agentic seller" concept for AI-powered account managementMatt's 3 actionable recommendations for business leaders: data, budget, and the right partnersIf you're a business leader trying to figure out where AI fits in your go-to-market strategy, this is the clearest framework I've heard. Matt doesn't just talk about AI, he's building the organization that makes it work.

Only 2-3% of Manchester City fans will ever set foot in the stadium. So how do you build a business around the other 97%? Ron Li has spent his career figuring that out.Ron Li is VP of Data Intelligence & Strategic Partnerships at the Phoenix Suns, where he oversees AI and data strategy across five properties — the Suns (NBA), Mercury (WNBA), Valley Suns (G League), Footprint Center, and the team's hospitality portfolio.Before the Suns, Ron was employee #4 on the PGA Tour's international business team and helped build EA's competitive gaming division from scratch. He's also a former professional esports player.In this episode, Ron breaks down:Why sports teams can't think of themselves as an events business anymoreHow the Suns use visual AI to measure sponsorship value in real-timeAI agents handling season ticket billing, lapsed fans, and new prospect listsThe Verizon 5G practice facility partnership and what "strategic" really meansWhy a clean data foundation matters more than any AI toolHis hiring philosophy: curiosity over credentialsIf you lead a team figuring out where AI fits in your business, this conversation is a blueprint — not theory.Subscribe and follow AI for Business Leaders wherever you listen.