"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 everyone
• How 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 wind
• The 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 acceleration
• Writing 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 leaf
• Why AI Circle is bootstrapped, not VC-backed — and the fight story from sophomore year that shaped how Albert thinks about community size forever
• The deeper problem AI Circle is really solving: community, connection, and relationship as life gets harder, and friend circles get smaller

If 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 check
• The pattern recognition behind picking venture-backed founders — magnetism, talent attraction, and repeat founder advantage
• How Mu Ventures expanded from pure commerce enablement to any transaction that removes friction
• OpenAI's instant checkout vs. Google's agent payments protocol — two completely different approaches to agentic commerce
• Why Gary's AI red flag is when the AI IS the thing, rather than AI making the thing better
• The return to grassroots brand building as CAC rises and attribution breaks down
• TikTok Shop, experiential marketing, and why hand-to-hand combat is back
• Why the next 5 years of commerce infrastructure will be defined by buyer-agent-to-buyer-agent transactions
• The 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 stuck
• Why picking a narrow, metrics-driven use case beats trying to "AI-ify" an entire function
• How AI is shifting from incremental efficiency gains to a complete rewrite of how companies operate
• The coordination cost problem — and why removing human bottlenecks accelerates everything
• Why the gap between an idea and a functioning product is now measured in minutes, not months
• The people side: how leaders can help their teams move past fear and embrace AI as an amplifier

Whether 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/jamesraybould

Learn 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 strategy
• TikTok-first organic content: from 1,200 videos/year to fewer but higher-impact
• Custom GPTs as a practical first step for AI adoption
• Change 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 content
• Why the AI arms race looks different outside the tech bubble

Sign 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 inventory
• AI-driven rapid testing and decision-making
• Building 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 disruptions
• The role of storytelling in brand loyalty
• AI 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 homepage
• The centralized data architecture that makes 1+1=10 with AI
• Matt's build vs buy framework for enterprise AI decisions
• Forward deployed engineers — why they beat traditional consultants
• The rebrand from BigCommerce to Commerce and the category strategy behind it
• Change management and the people challenge of AI adoption inside a 500+ person org
• The "agentic seller" concept for AI-powered account management
• Matt's 3 actionable recommendations for business leaders: data, budget, and the right partners

If 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 anymore
• How the Suns use visual AI to measure sponsorship value in real-time
• AI agents handling season ticket billing, lapsed fans, and new prospect lists
• The Verizon 5G practice facility partnership and what "strategic" really means
• Why a clean data foundation matters more than any AI tool
• His hiring philosophy: curiosity over credentials

If you lead a team figuring out where AI fits in your business, this conversation is a blueprint — not theory.

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