
Hosted by Forum3 · EN

The media narrative around token maxing and CFO anxiety is creating confusion at the executive level, just as AI is becoming genuinely transformative. Stories about companies blowing through annual token budgets in a quarter have leaders reaching for the brakes. Adam and Andy argue this is exactly backward.The core reframe: AI isn't a line item in your tech stack. It's intelligence as a service. The cost of fully deploying AI across a 100-person company runs close to one headcount. If your employees are hitting usage limits and asking for more, that is your ROI signal, with or without a spreadsheet to prove it. When you aim AI at growth and differentiation rather than cost savings, the returns become clearer and more meaningful.Andy's unsolicited advice: stop measuring ROI altogether for now. The obsession with proving returns is impeding the experimentation that would actually teach you where to aim the AI machine. Aim it at growth. The returns will follow. And if you want to know what AI can really do, try token maxing for a week.

Most companies approach AI agents as efficiency tools, ways to do the same work faster and cheaper. This episode presents a different model. Forum3 recently deployed a managed agent for a client's independent sales force, and the results challenge that assumption.The agent, delivered entirely through email, acts as a personalized CRM, business analyst, and chief of staff for each sales rep. It prioritizes targets, customizes product recommendations using real data, drafts personalized outreach, and proactively delivers a daily action plan. The sales reps, many of whom are in their 40s and 50s with minimal AI experience, interact with it the way they'd interact with a human assistant.The key insight: this isn't an efficiency play. The workflow didn't exist before the agent. It's a revenue growth tool that gives independent workers the equivalent of a functional team they could never afford to hire, with built-in data security guardrails that protect the business from agent errors.

Clay CEO Kareem Amin joins AI First to discuss how Clay evolved from a no-code productivity platform into one of the fastest-growing AI-powered go-to-market companies. He shares the origin of the go-to-market engineer role, how AI transformed sales and customer intelligence workflows, and why Clay was uniquely positioned to capitalize on the rise of large language models.The conversation explores the future of SaaS in an AI-driven world, including the growing build-versus-buy debate, the impact of AI on software development, and why proprietary data, customer insights, and network effects remain critical competitive advantages. Kareem also explains why AI has been overwhelmingly positive for Clay’s business and how AI enables teams to turn unstructured data into actionable growth opportunities.The discussion concludes with a thoughtful debate on AI leadership. While Kareem embraces AI throughout Clay’s products and operations, he takes a more measured approach to using AI for executive decision-making, arguing that CEOs must remain close to customers, employees, and strategic context. The episode offers valuable insights for executives navigating AI adoption, organizational design, and the future of growth.

Across industries, job postings increasingly require AI experience, but a fundamental mismatch exists between what employers are asking for and how they evaluate it. Adam and Andy tackle this head-on, starting with the hiring manager who knows AI matters but isn't deeply fluent themselves. How do you assess a skill you don't fully possess?The answer, they argue, comes down to asking candidates about real projects, not tool lists. Can they explain what they built, why AI was the unlock, and what they struggled with? The level of someone's challenges reveals their level of sophistication. For candidates, the advice is equally direct: build something with AI before you walk into the interview. A prompt workflow, a research project, a personal tool. The ability to narrate that process, including what failed, is what separates genuine fluency from buzzword familiarity.For managers still unsure, Andy offers a practical hack: transcribe the interview and ask an LLM to assess the candidate's AI proficiency. Let the technology help evaluate the technology skills.

As AI investments accelerate across the enterprise, many organizations are simultaneously pursuing workforce reductions and operational restructuring. In this episode of AI First with Adam and Andy, Adam Brotman and Andy Sack examine recent layoffs at major companies including Meta, Coinbase, Oracle, and Block, and discuss what separates strategic AI transformation from simple cost-cutting.The conversation introduces the concept of AI “scaffolding” or an organizational “exoskeleton” the systems, workflows, governance structures, training programs, and AI-enabled processes that support meaningful business transformation. The hosts argue that organizations must build these capabilities before making significant structural changes if they want to preserve institutional knowledge and maintain operational effectiveness.Using Meta’s creation of new roles such as AI-focused organizational leaders and builders as an example, the discussion highlights the importance of redesigned workflows, workforce retraining, agentic systems, and AI proficiency programs. The episode offers practical insight for executives navigating AI adoption, organizational redesign, and the evolving relationship between technology investment and workforce strategy.

Restaurant leaders have moved past curiosity and into something more unsettling: they understand enough to know AI is powerful, but not enough to know where to start. That fear, shared openly by CEOs at industry conferences, is driving a new wave of urgency around AI strategy.Adam Brotman and Andy Sack break down this understanding gap with real conversations from restaurant C-suites. They introduce Forum3's Speed, Order, Aim methodology: build proficiency quickly, stack rank your opportunities, then identify the one or two unlocks that were impossible before this technology existed.From drive-through voice AI versus in-app ordering to store manager empowerment and P&L optimization, this episode maps the restaurant industry's highest-value AI opportunities and makes the case that getting started matters more than getting it perfect.

In this episode, Red Robin’s VP and Head of Technology, Deena DePhilips, outlines a pragmatic approach to enterprise AI adoption grounded in leadership alignment and real-world application. Framing AI as a transformative force akin to the internet, she emphasizes that organizations must “lean in and lead,” ensuring AI happens with them, not to them.DePhilips details a “crawl, walk, run” journey, where Red Robin currently operates as a “wobbly walker”, encouraging experimentation while implementing necessary guardrails. She highlights the importance of executive sponsorship, cross-functional ownership, and structured governance, including policy development, employee training, and legal oversight in an increasingly AI-driven vendor landscape.The conversation also explores where AI delivers the most value in hospitality: improving labor efficiency, optimizing cost of goods, and freeing frontline operators to focus on human connection. With a focus on practical use cases over hype, DePhilips underscores a key insight for executives, AI success depends less on immediate ROI and more on building capability, curiosity, and organizational readiness at scale.

Adam Brotman put his OpenClaw agent to work on a real task: identifying small restaurant and cafe concepts for sale, evaluating options, and reaching out to business brokers. The agent moved fast, surfacing viable opportunities and drafting outreach within minutes. It also emailed the wrong person with unapproved information, a concrete example of the autonomy that makes agents powerful and the oversight gaps that make them risky.The episode traces the full arc of the experience: the initial task, the agent's mistake, the correction, and the recovery. By the time Adam returned from dropping his daughter at school, the agent had found strong leads and connected him with a broker. The entire cycle, from mess to productive outcome, took less than 45 minutes.For leaders exploring agentic AI, the takeaway is practical. Agents can accomplish real work autonomously, but they require clear instructions, defined guardrails, and human review at each step. The only way to build that judgment is through direct, hands-on use.

In this episode of AI First, Adam Brotman and Andy Sack sit down with Inflection CEO Aaron Bird to unpack the rise of agentic marketing and what it means for business leaders. The conversation explores how AI is evolving from simple Q&A tools into autonomous agents capable of executing complex marketing workflows—from campaign planning to execution—at scale.The discussion introduces a two-phase framework: first, agents performing tasks humans could do faster and more efficiently; second, agents enabling entirely new capabilities through scale, personalization, and continuous optimization. This shift reframes marketing roles, moving professionals away from execution and toward planning, orchestration, and outcome management.Looking ahead to 2028, the group examines how organizations may transform as agent-driven customer experiences replace traditional functional silos. Marketing, sales, and support roles converge into unified, AI-powered interactions, challenging existing org structures and redefining leadership priorities. The episode closes with practical guidance for executives on accelerating adoption and building agent-first teams.

Andy Sack spent a full day managing a complex writing project through Claude Cowork's dispatch feature, directing his AI agent from his phone between coffee meetings. The result: roughly ten times the output he could have produced working alone. Then at step five of six, the agent told him his files didn't exist.This mini episode captures the full arc of working with AI agents: the invigoration of real-time delegation, the gut punch when things break, and the 90-minute recovery that still left Andy ahead of where he'd have been without agents. Adam Brotman contextualizes the experience, explaining how agents differ from chatbots and why the failures are instructive, not just frustrating.The conversation also covers Andy's rapid skill-building, going from 5 saved skills to 28 in two weeks, and what that signals about how individuals and organizations will work with AI agents going forward.