Elevate Your AIQ

Bob Pulver sits down with David Arnoux, co-founder of AI-native venture studio Humanoidz, fractional GTM strategist at HeyArnoux, and community leader of the Gen AI Circle, a global network of nearly 500 heavy AI adopters. David shares a clear-eyed framework for understanding where AI is actually taking work, moving from co-intelligence and augmentation through full workflow automation and into the uncomfortable reality of job category redundancy. The conversation covers responsible AI guardrails, the architecture of second brain systems, and the emerging shift from SaaS subscriptions to custom-built agent-powered tools. David draws on patterns he observes across his community, client work, and venture studio to offer practical first steps for individuals and organizations ready to move beyond the chat window.

Keywords

David Arnoux, Humanoidz, Gen AI Circle, HeyArnoux, Growth Tribe, agentic AI, augmentation, automation, redundancy, co-intelligence, responsible AI, second brain, skills files, SaaS disruption, GTM strategy, go-to-market, lethal trifecta, prompt injection, MCP integrations, Claude Code, solopreneur, workflow automation, human in the loop, agent orchestration, buy vs. build, future of work

Takeaways

The four-stage framework of co-intelligence, augmentation, automation, and redundancy offers a more honest map of where AI is taking work than the comfortable augmentation narrative most organizations have sold themselves on

Responsible AI is less a philosophy debate and more a practical checklist: confirm before acting externally, maintain audit logs, cap high-frequency tasks, and never allow destructive actions without human approval

The "lethal trifecta" of private data, untrusted content, and external communication access in a single agent creates serious prompt injection risk, and the architectural answer is isolation by capability

Heavy AI adopters are productizing every repeated workflow as a skills file, a simple markdown document that turns any process into a reusable, shareable, and transferable asset

The buy vs. build calculus is shifting fast, with community members replacing multi-tool SaaS stacks costing hundreds per month with custom-built solutions at a fraction of the cost

Distribution and audience are now the primary moat for any new venture, making community building and direct relationships more valuable than ever

Quotes

"Smart humans plus better tooling equals crazy results. That's what we see happening 10x, 100x at the moment."

"Just pretending it's all about augmentation is how you and I end up unprepared."

"Responsible AI is not a philosophy debate. It can actually be a checklist."

"Learning is a markdown file. You download their thinking directly into the system."

"I posted that I would never purchase a CRM ever again. It got the most engagement of anything I've ever written in months because people felt it."

"Distribution is everything nowadays and audience is more important than ever."

Chapters

00:03 Welcome and guest introduction

01:03 David's background, Growth Tribe, and the three-entity flywheel

04:52 Why distribution and audience matter more than ideas

09:36 Co-intelligence, augmentation, automation, and redundancy

16:38 Human centricity, responsible AI, and finding your personal line

19:59 Practical guardrails for agentic systems

23:41 How heavy adopters are actually working today

31:32 Digital literacy, learning habits, and the mindset that compounds

36:19 Bob's second brain challenges and the ethics of AI-powered outreach

41:40 The lethal trifecta and agent isolation architecture

48:11 First steps: Claude Code, MCP integrations, and skills files

51:32 SaaS disruption, buy vs. build, and the future of software pricing

58:19 Career paths, entrepreneurship, and building your audience

David Arnoux: https://www.linkedin.com/in/davidarnoux

HeyArnoux: heyarnoux.com

Humanoidz: humanoidz.ai

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Lisa Cole, Chief Marketing, Product, and AI Officer at 2X and three-time author, joins Bob to explore how AI is fundamentally reshaping the B2B marketing function. Lisa shares how 2X, a global marketing-as-a-service firm with 1,400 marketers worldwide, is navigating the shift toward generalist talent, AI-native roles, and human-centered AI adoption. The conversation covers her framework for "brand gravity," the case for keeping strategic thinking and brand voice uniquely human, and how AI enables the scale needed to be findable and chosen by buyers long before they raise their hand. Lisa also discusses her new book, The Limitless CMO, which offers a practical operating model for scaling marketing impact without skyrocketing costs.

Keywords

Lisa Cole, 2X, brand gravity, B2B marketing, marketing as a service, AI adoption, generalist marketers, AI-native roles, human centricity, prompt engineering, knowledge layer, synthetic personas, mock focus groups, omnipresence, The Limitless CMO, Brand Gravity, The Revenue RAMP, responsible AI, content at scale, buyer journey

Takeaways

AI is shifting marketing toward generalists who are adaptable, curious, and comfortable with continuous change, while also creating entirely new roles like AI automation specialists and prompt engineers

Organizations fall into three categories of AI readiness: AI-forward with clear strategy, still figuring it out, and fully resistant; 2X leads with full disclosure and follows each client's lead

The deciding of what to say and how to say it should remain uniquely human, as it is the source of competitive differentiation and brand trust

Brand gravity is built by accumulating digital mass across all the places buyers research anonymously, making a brand findable and chosen before any sales conversation begins

AI enables the scale needed to repurpose core thought leadership into derivative assets across channels, without outsourcing the underlying thinking

Synthetic personas and mock focus groups offer a faster, lower-cost path to messaging development, though high-stakes repositioning decisions still warrant real human input

Building a knowledge layer from unstructured organizational data, call transcripts, emails, and more, is the key unlock for eliminating AI slop and generating reliable, contextual output

Quotes

"Deciding what to say and how to say it, those points of view that you're putting out in the market, that should be uniquely human. That's your secret sauce."

"It's the absence of guardrails that people are so afraid of. The guardrails are what's actually unleashing it."

"We recruit about 80 to 100 marketers a month, and we now have to really focus on soft skills: are they open to an ever-changing environment?"

"I used AI when I was writing my book, not to write the book, but to interview me."

"If you actually know your workflows and can taskify it in such a way that you can explain it to an intern, then it's very easy to apply AI to accelerate it."

Chapters

00:03 Welcome and guest introduction

03:46 AI's role across a 1,400-person marketing organization

06:12 Evolving roles and the rise of the generalist marketer

10:06 Client AI readiness and 2X's full-disclosure approach

13:56 Defining what should remain uniquely human

18:21 Brand voice, storytelling, and competitive differentiation

21:21 Brand Gravity and the anonymous buyer journey

23:41 The Limitless CMO and scaling without skyrocketing costs

28:40 Building the knowledge layer from unstructured data

31:31 Synthetic personas and mock focus groups

36:13 Good enough as a framework for AI use case decisions

41:34 Voice-first workflows and AI-assisted book writing

45:43 Global operations, offshore teams, and cultural dynamics

50:28 Closing thoughts and book resources 

Lisa Cole: https://www.linkedin.com/in/lisacole01

2X: https://2x.marketing

“The Limitless CMO”: https://lisacole.ai/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠
Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Danna, physicist, naval officer, former Senior Managing Director at Deloitte Consulting and Bersin by Deloitte, and author of the memoir "My Curious Life," joins host Bob Pulver for a wide-ranging conversation about a lifetime at the frontier of science and technology. Bob traces his journey from slide rules and nuclear reactors to agentic AI, sharing how he and collaborator Joe DiDonato built "Bot-Bob," a digital twin trained on his memoir, writings, and decades of experience. The conversation explores what digital twins can mean for knowledge workers, legacy building, and collective intelligence, including a live mastermind experiment where multiple digital twins, plus a digital Mark Twain, fielded questions from a live audience. Bob closes with an urgent call to bring more diverse human voices into AI development before the decisions that shape civilization get made without them.

Keywords

Bob Danna, digital twin, agentic AI, Bot-Bob, Joe DiDonato, My Curious Life, knowledge worker, collective intelligence, co-intelligence, legacy, mastermind, ElevenLabs, nuclear warfare, responsible AI, human centricity, future of work, STEM, Deloitte, memoir, Substack

Takeaways

Curiosity is the connective tissue of Bob's entire career, from nuclear physics and naval service to Deloitte consulting and digital twins, and he positions it as the essential human quality that AI can amplify but never replicate 

A digital twin is far more than a knowledge repository; it encodes values, judgment, and personality, making it a genuine extension of a person's thinking

The "mastermind" format, where multiple digital twins deliberate together in real time, opens new possibilities for accessing cognitive diversity without scheduling constraints

When AI models are trained by a narrow group (such as military strategists), the outputs reflect that bias, making diverse human representation in AI development a matter of consequence

Knowledge workers who collaborate with their own digital twins can operate at dramatically higher capacity and quality, not by being replaced, but by being amplified

A responsibly built digital twin can preserve the wisdom, voice, and values of an individual for future generations

Quotes

"I'm just a curious guy. No matter what I'm into, I'm always looking at other things." 

"When we free up tasks that human beings were doing, I think that is very, very positive. The real question is, what does the human being step up to do that only a human being can do?"

"The definition of a knowledge worker is going to change. It's going to be that human being collaborating with the digital twin of that person."

"It's very timely right now that we really start to have human conversations before we go down the path too far."

Chapters

00:03 Welcome and introductions

01:21 Bob Danna's fascinating career journey

03:27 Early encounters with AI and neural networks

07:21 What makes us human, the evolution of calculators and computers

10:26 Joe DiDonato, soul-sinking, and the origin of Bot-Bob

14:41 Building Bot-Bob, memoir, voice, and guardrails

17:17 From chatbots to agents to digital twins, a practical framework

25:27 Brainstorming mode and collaborating with your own twin

28:16 Digital twins in consulting and the future of knowledge work

35:20 The mastermind experiment, Bot-Bob, Robo Lacey, and digital Mark Twain

41:14 AI, nuclear war scenarios, and the dangers of narrow training data

51:31 The workforce of 2030 and what it means to be a knowledge worker

58:55 Closing thoughts and how to connect with Bob Danna

Bob Danna: https://bobdanna.substack.com/

“My Curious Life”: https://mycuriouslife.net/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver sits down with Laura Maffucci, Head of HR at Globalization Partners, for a wide-ranging conversation on AI adoption, global workforce trends, and the evolving role of HR. Laura shares how G-P is deploying its agentic AI product, GIA, both externally for global employment compliance and internally as a pilot HR agent, while emphasizing the importance of grounding AI in trusted, expert-sourced data. They explore the growing disconnect between executive optimism and employee sentiment around AI, the durable human skills that matter most in an AI-augmented workplace, and why AI adoption without a clear problem to solve is a recipe for costly confusion. Laura also shares candid reflections on her own AI learning journey and what she sees ahead for the HR function.

Keywords

Laura Maffucci, Globalization Partners, GIA, employer of record, EOR, agentic AI, global employment, AI compliance, HR transformation, AI adoption, employee sentiment, AI literacy, early career roles, talent acquisition, deep fakes, AI governance, critical thinking, human skills, learning agility, shadow AI, AI Awesomeness Awards, internal mobility, cognitive diversity, compensation analytics, AI readiness, Gemini, NotebookLM

Takeaways

GIA has evolved from a compliance Q&A tool into an agentic platform that can generate contracts, audit company policies, and is now being piloted as an internal HR agent handling employee ticket inquiries

The data behind GIA is grounded in over a decade of G-P's global employment expertise, offering a trusted alternative to general-purpose LLMs drawing from unverified internet sources

A significant perception gap exists between executives who believe AI is driving efficiency and employees who feel it is actually adding to their workload or generating unreliable output they must clean up

Entry-level roles are shifting toward managing and directing AI agents rather than executing tasks directly, with "taste" (the ability to evaluate AI output) emerging as a critical early-career skill

Workforce hiring criteria must increasingly prioritize unteachable human attributes such as curiosity, learning agility, courage, and the willingness to relinquish control, because technical AI skills can be taught but these cannot

AI adoption mandates without a clearly defined problem to solve create fragmented, siloed "shadow AI" that can undermine organizational strategy rather than advance it

HR functions are being asked to lead organizational AI transformation without adequate resources, technical support, or direction, making the role both high-opportunity and genuinely demanding

Assessing real AI usage requires creative mechanisms: GP uses a Slack sharing channel, quarterly performance check-in questions, and monthly AI Awesomeness Awards to surface how people are actually applying the technology

Quotes

"I know that when these things come out, whether you like them or not, you had best learn them and learn how to work with them."

"If you have a legal or compliance question, I hope Reddit's not your first stop to get that answer."

"You can't embrace AI and be a control freak. You have to be willing to let something go and let something do something."

"The pitfall that I can see so many companies falling into is, we don't need people because we've got the AI to do this."

"Being in HR right now is not for the weak. That I will say, for sure."

"It should always be: what problem are we trying to solve? Because that's actually one of the biggest issues with AI."

Chapters

00:02 Welcome and guest introduction

01:40 Employer of record explained

03:03 GIA overview and new agentic capabilities

05:27 Responsible AI and the importance of trusted data sources

08:47 GP research findings on AI adoption and executive-employee sentiment gap

11:50 AI as added burden vs. efficiency driver

13:45 Redefining early career roles in an agentic world

15:42 The human cost of replacing workers instead of augmenting them

19:05 The problem with AI mandates that skip the "why"

22:44 Human skills that matter most when hiring for an AI-augmented workforce

26:37 The AI-versus-AI problem in talent acquisition

27:39 Deep fakes, virtual interview integrity, and human oversight in TA

31:53 The evolving role of HR as a strategic function

37:13 C-suite dynamics and running HR as a pilot for GIA

39:27 Building an AI council, sharing culture, and identifying shadow AI

42:15 Measuring AI fluency through awards, check-ins, and community

45:14 Laura's personal AI journey and closing thoughts

Laura Maffucci: https://www.linkedin.com/in/laura-maffucci

G-P: https://www.globalization-partners.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠
Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver is joined by Jerry Jao, CEO of Employ, who brings a perspective shaped by years of building AI-driven consumer personalization before turning that lens on hiring. Jerry shares how he is restructuring Employ for greater agility, how Pillar's interview and screening companions are reducing friction for job seekers and recruiters alike, and why the surge in AI-assisted applications is complicating matching on both sides. He also addresses candidate fraud and deepfakes, and explains how Employ's IBM partnership helps reduce bias and hallucinations across nearly 100 million applications processed annually.

Keywords

Jerry Jao, Employ, Lever, JazzHR, Pillar, interview intelligence, screening companion, talent acquisition, candidate experience, AI bias, responsible AI, IBM, deepfakes, candidate fraud, AI literacy, two-sided marketplace, organizational design, hiring technology

Takeaways

Jerry's background in AI-powered personalization at Retention Science informs his approach at Employ, viewing both job seekers and hiring managers as people deserving a more thoughtful, personalized process

Employ processed nearly 100 million applications last year, with some roles receiving two to three thousand submissions, making meaningful evaluation a serious operational challenge

Pillar's interview and screening companions are being integrated platform-wide to improve TA accuracy and give recruiters measurable time back in their day

Responsible AI is a strategic priority, with IBM as a thought partner on model bias, hallucinations, and protecting candidate data at scale

Candidate fraud, including deepfakes and multiple identity submissions, is an emerging risk Employ is working to detect earlier in the funnel

AI-optimized resumes are eroding the signal value of traditional screening, making interview intelligence increasingly critical

Quotes

"What I'm most excited about is creating a more effective process for people to provide for their loved ones by getting to their dream jobs."

"We want to help our TA team get home a little sooner, or take a 30-minute mental break if AI can help get that time back in their day."

"Hiring managers are telling us people sound incredibly amazing, but once they get on the call, it's a little different."

"We're all people at the end of the day, so how do we personalize the experience so no one feels overlooked?"

"It's almost as big a change as when the internet first arrived. We're in a very uncertain and unprecedented time."

Chapters

00:02 Welcome and introductions

02:03 From consumer personalization to talent acquisition

04:55 Building a human-centered hiring marketplace

07:16 AI on both sides: the cat-and-mouse dynamic in recruiting

09:24 Restructuring Employ for agility and accountability

14:12 Screening companion, talent fit, and processing 100 million applications

20:40 Candidate fraud, deepfakes, and emerging hiring risks

22:07 Responsible AI and the IBM partnership

30:38 AI literacy in job descriptions and skills assessment

34:54 Jerry's new podcast and the future of TA storytelling

39:02 Navigating workforce uncertainty in the AI era

41:12 Closing reflections and Employ research reports

Jerry Jao: https://www.linkedin.com/in/jerryjao

Employ: http://www.employinc.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠
Substack: ⁠https://elevateyouraiq.substack.com⁠

Paul Rubenstein, Chief Evangelist and Talent Strategist at Visier, brings deep expertise in people analytics and workforce strategy to this wide-ranging conversation with Bob Pulver. He introduces a three-curves framework for CHROs navigating AI: the human-machine efficiency frontier, the ROI curve, and the humanity index. The discussion explores why workforce planning is having a long-overdue resurgence, and how HR can use AI-powered analytics to reach managers proactively rather than waiting for them to come to HR. Bob and Paul also examine the courage gap in AI adoption, the governance tension between restricting data and enabling better AI answers, and the design-plan-operate mindset required to truly transform work.

Keywords 

Paul Rubenstein, Visier, people analytics, workforce planning, CHRO, human-machine efficiency frontier, ROI curve, humanity index, agentic AI, MCP server, intelligent service delivery, governance, data strategy, organizational design, courage gap, talent strategy, future of work

Takeaways 

• CHROs should track three curves: the human-machine efficiency frontier, the ROI curve on AI investments, and a humanity index covering talent density, engagement, and culture. 

• Most organizations are stuck in the "gym membership phase" — distributing AI tools without redesigning work — and real returns require intentional deconstruction and reassembly of jobs. 

• The courage gap is real: employees need to see self-disrupting behaviors modeled and rewarded before they willingly give up tacit knowledge to train agents. 

• MCP servers enable systems-to-systems intelligence that can give managers contextual, proactive insights in the flow of their work — without them ever having to engage HR directly. 

• Workforce planning is entering a golden age, requiring continuous, real-time, multi-dimensional design that mirrors how finance operates with FP&A. 

• AI governance needs to shift from restricting data by default to securing personal accountability for use — otherwise AI answers will remain narrow and biased. 

• When all companies have access to the same agents, people and culture will again be the differentiator — making the humanity index a strategic, not just a moral, priority.

Quotes 

• "The floor for the tools we expect at work has just risen. AI is one." 

• "You can't lay off a hand or an arm to recover your technology investment." 

• "I want my workforce plan to be as easy as Google Maps — give me traffic updates and help me reroute." 

• "Sameness does not yield greatness in a talent strategy." 

• "Don't rely on your company for your career. You are responsible for staying relevant." 

• "Just because you can automate something doesn't mean you should."

Chapters

00:02 Welcome and introductions

00:53 Paul's career journey and obsession with HR's untapped potential

05:05 How AI is changing the analyst role and collapsing distance to insight

06:50 The three curves framework for CHROs navigating AI adoption

10:46 Strategic work planning vs. workforce planning and the agentic org chart

14:11 Manager evolution in a human-agent workforce

16:33 The gym membership phase and why job redesign is the real unlock

19:39 The courage gap and cultural conditions for AI adoption

23:29 Protecting durable human skills and doing the hard things

26:50 AI governance and the tension between data restriction and answer quality

31:38 MCP servers and the future of intelligent HR service delivery

38:54 Orchestration layers and proactive manager engagement

45:50 How analytics builds HR's strategic credibility

47:03 AI as first mate and the case for continuous workforce planning

51:52 Closing thoughts on staying human-centric and owning your career

Paul Rubenstein: https://www.linkedin.com/in/paulrubensteinhr

Visier: https://visier.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Charlene Li, analyst, author, and disruptive leadership expert, returns to Elevate Your AIQ to discuss with Bob her newly released book Winning with AI, co-authored with Dr. Katia Walsh. Charlene makes the case that most organizations are failing with AI because they treat it as a technology initiative rather than a strategic one — and lays out a 90-day, 12-step framework for building a foundation that creates real enterprise value. The conversation revisits themes from her Fall 2024 appearance, including responsible AI and the human-AI partnership, and explores how the landscape has evolved. Key topics include AI fluency as an organizational imperative, workforce reinvestment over workforce reduction, and the emerging concept of integrated intelligence — where human and AI capabilities combine to create something genuinely superhuman.

Keywords

Charlene Li, Winning with AI, Katia Walsh, AI strategy, AI fluency, AI literacy, integrated intelligence, superhuman worker, workforce planning, reskilling, pilot purgatory, responsible AI, ethical AI, governance, human centricity, talent transformation, future of work, organizational disruption, values-based AI, co-intelligence

Takeaways

Lead with business strategy, not AI technology — the question is never "what can we do with AI?" but "how can AI help us accomplish what we're already trying to do?"

AI fluency, not just literacy, is the goal — fluency means reaching for AI naturally, trusting it, and using it to learn how to use it better, like chopsticks becoming second nature

Organizations stuck in pilot purgatory are procrastinating real decisions — pilots give everyone an excuse not to commit, and that dooms projects from the start

Successful examples show a better path: use AI to raise workforce quality first, then expand customer value, then reinvent the business entirely

Reskilling requires both organizational imagination and honest values — the IKEA story turned 8,500 displaced service reps into a $1B design business

Integrated intelligence combines AI's speed and scale with uniquely human traits — empathy, judgment, intuition, self-reflection, and wisdom — to create superhuman capability

AI fluency in hiring is shifting from a red flag to a baseline expectation — how candidates use AI reveals curiosity, creativity, and adaptability far better than traditional interviews

Responsible AI governance done right isn't a compliance burden — a gold-standard internal policy means regulation becomes a checkbox, not a crisis

Quotes

"You don't need an AI strategy — you already have a business strategy. Figure out what of your business strategy could really be impacted with AI."

"Automating a broken process is the definition of madness. Because of AI, could we do this in a completely different way?"

"AI can only be as creative as your questions are. It can only be as empathetic as you are."

"We should stop doing pilots. It's just another way to procrastinate having to say yes or no."

"The first thing they said was, we are not going to use AI to cut people. That is not the intent going in."

"You aim for a higher level than any regulation would ever want. You go for the gold standard and whatever they ask of you, of course you do those things."

Chapters

00:03 Welcome and guest introduction

01:27 Catching up since Fall 2024 and the impetus for Winning with AI

02:45 The 90-day framework and leading with business strategy

05:46 Reimagining work versus automating broken processes

09:22 AI fluency as an organizational imperative

14:06 Making AI practice habitual and learning in community

17:54 Embedding AI in the flow of work and escaping pilot purgatory

20:07 Workforce reinvestment and a recent case study

26:35 Reskilling, redeployment, and the IKEA story

29:54 Getting C-suite and boards to embrace a human-centric approach

33:38 Starting with customers and thinking beyond efficiency

38:30 Building AI fluency fast and making the investment

41:38 AI fluency in recruiting and hiring for AI capability

47:52 Integrated intelligence and the rise of the superhuman worker

50:42 From individual productivity to team and organizational impact

52:14 Values-based AI and imbuing organizational values into AI systems

55:53 Responsible and ethical AI as a strategic advantage

59:38 Goldilocks governance and the 90-day blueprint

01:00:21 Closing thoughts and book information

Charlene Li: https://www.linkedin.com/in/charleneli

“Winning With AI”: https://winningwithaibook.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver reconnects with former IBM colleague Oded Dubovsky, founder of STRAIX (Strategy for AI Execution), an advisory practice helping organizations adopt AI thoughtfully and effectively. Oded shares a career journey spanning over two decades at IBM Research's Haifa Lab — where he led pioneering cognitive computing and computer vision projects — through applied AI work at Intel, and into independent consulting. The conversation explores why 95% of organizations struggle to move beyond AI aspiration to real execution, and what it takes to build a solid foundation before layering in AI. Bob and Oded also reflect on the enduring value of human ingenuity, originality, and orchestration in an increasingly AI-assisted world.

Keywords

Oded Dubovsky, STRAIX, AI strategy, AI execution, AI adoption, cognitive computing, computer vision, IBM Research, Haifa Lab, Watson, automation, generative AI, vibe coding, AI-assisted coding, responsible AI, human centricity, AI readiness, orchestration, innovation, shadow AI

Takeaways

Only about 5% of companies successfully adopt AI — most struggle with where to start, what tools to use, and how to build the right foundation before scaling

AI is the "penthouse" built on top of decades of IT, software engineering, and automation experience — that foundational knowledge remains critical

The human role is shifting from execution to orchestration and architecture — developers and knowledge workers are becoming "team leads" directing AI agents

Responsible AI development means thinking through security, data, scalability, and governance from the start — not as an afterthought

Slowing down to think carefully before prompting or building — echoing Einstein's 55/5 rule — leads to better, more scalable outcomes

Early cognitive computing projects at IBM (food recognition, augmented reality for remote guidance) were ahead of their time, foreshadowing capabilities now taken for granted

Human originality and the ability to generate truly novel ideas remain a distinctly human trait that AI has not replicated

Quotes

"AI is kind of the top level, like the penthouse on top of all of that."

"95% are just saying we need AI — they kind of don't know how to absorb that, how to start using it."

"Once I crossed the line, I couldn't go back."

"Think about it — you just got a promotion. You're a team lead now. You don't micromanage. You give them the bigger picture."

"If I had an hour to solve a problem, I'd spend 55 minutes thinking about the problem and five minutes thinking about the solution." — Einstein, as quoted by Oded

"Slow down to speed up."

Chapters

00:02 Welcome and introductions

01:04 Oded's background and career journey from IBM to Intel to STRAIX

08:08 Early cognitive computing at IBM — the Watson era and the "What Did I Eat?" project

13:01 From research to product — augmented reality, 3D cameras, and lessons learned

17:54 How AI adoption is accelerating and compressing what once took a decade

20:14 Why 95% of organizations struggle to execute on AI

24:54 How STRAIX works — mapping pain points, building a heat map, and guiding implementation

29:47 Automation tools, vibe coding, and the value of foundational experience

33:13 Human readiness and the mindset shift required to embrace AI

37:22 AI agents, social networks, and the human as orchestrator

44:20 Responsible AI development — building with guardrails from the start

51:26 Asking better questions and thinking architecturally before building

53:31 Closing thoughts and how to connect with Oded

Oded Dubovsky: https://www.linkedin.com/in/odeddubovsky

STRAIX: www.straix.biz

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver sits down with Jacob Bank, Co-founder and CEO of Relay.app, whose career arc — from Stanford's Multi-Agent Systems Lab to founding Timeful (acquired by Google in 2015) to leading Gmail and Google Calendar product teams — represents one of the most continuous threads in AI agent development. Jacob frames AI agents not as software to configure, but as employees to hire, coach, and manage, arguing that great people managers are naturally suited to the AI era. He maps out a three-tier AI stack everyone should adopt and explores how knowledge work will be restructured, why AI literacy is non-negotiable, and how small businesses can now compete at scales once unimaginable.

Keywords

Jacob Bank, Relay.app, AI agents, agentic workflows, autonomous workers, workflow automation, small business, AI literacy, people management, Timeful, Google Calendar, Gmail, knowledge work, G&A, go-to-market, responsible AI, human-in-the-loop, SaaS evolution

Takeaways

The right mental model for AI agents is employee management: give them a job description, set expectations, provide feedback, and apply the same code of conduct as any team member

Everyone needs three AI tools: a chatbot for conversation, a copilot for real-time task delegation, and an autonomous agent platform for proactive, repeatable work

Relay runs on 9 humans and ~60 AI agents — and Jacob sees a path to serving 100x more customers with roughly the same team size

AI levels the playing field for small businesses, enabling work at a scale previously only achievable by much larger organizations

Jacob's three-level delegation progression: tasks you already do, tasks you're capable of but never have time for, and tasks you'd otherwise hire an expert for

AI literacy is not optional — it's becoming a baseline requirement for effective work, equivalent to basic computer literacy

Quotes

"We're all managers now — that is the skill set we need."

"If you have a job that is just to write the blog post about X, that job is not going to exist anymore."

"It's not optional. This is going to be a requirement of being an effective worker in the future."

"Whenever I have an AI agent doing a classification task, I always ask the AI to explain its rationale — because then you can correct it for next time."

"At some point you'll cross this tipping point where you don't have to tell yourself to go use AI — it'll suck you in."

Chapters

00:02 Welcome and introductions

00:56 Jacob's origin story and agent-oriented programming

02:54 From Timeful to Google

04:41 Pre-LLM AI features in Gmail and Calendar

06:15 AI coworkers vs. productivity tool nudges

07:39 Early agent research and org disruption

09:24 Restructuring knowledge work

11:45 Evolving human roles and AI literacy

13:32 The social complexity of scheduling

15:16 Credentialed jobs at risk

17:24 AI leveling the playing field for small business

18:17 Inside Relay — 9 humans and 60 agents

19:41 The three-tier AI stack

22:38 Relay as intelligent workflow automation

23:42 SaaS selection in the agent era

26:47 Platform consolidation and SaaS business models

28:13 Deploying agents across G&A, GTM, and R&D

33:16 Agent collaboration and human oversight

34:21 When to build vs. buy

37:56 Three levels of AI delegation

39:50 Scaling AI readiness across organizations

42:22 Responsible AI and the employee management lens

44:14 Evaluating agents vs. testing software

45:51 The blast radius problem

48:09 Bias, coachability, and correcting agents

49:29 Closing advice — go one step further

50:45 What's next for Relay

Jacob Bank: https://www.linkedin.com/in/jacobbank

https://relay.app

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠
Substack: ⁠https://elevateyouraiq.substack.com⁠

Bob Pulver and Melissa Reeve explore AI transformation and organizational design through the lens of Melissa's Hyperadaptive framework. They unpack what it means to become AI native, why most enterprises stumble by neglecting human support structures, and how governance, AI activation hubs, and AI leads create always-on learning organizations. The conversation tackles the reinvestment dilemma — what to do with capacity freed by AI — and makes the case for durable skills, systems thinking, and career lattices over ladders. Both Bob and Melissa draw on their non-linear careers and share the belief that humans remain essential connective tissue in any AI-powered future.

Keywords

Hyperadaptive, AI native, AI transformation, support structures, AI activation hubs, AI leads, dynamic governance, systems thinking, durable skills, adjacent competencies, agentic workflows, responsible AI, triple bottom line, career lattice, organizational design, value streams, Melissa Reeve, Elevate Your AIQ

Takeaways

Most AI transformations fail not because of technology, but because organizations underinvest in support structures — from AI councils to activation hubs to frontline AI leads

Becoming AI native is a gradual five-stage journey: foundation, workflow integration, agentic AI, scaling agents, and full hyper-adaptivity

The bifurcation problem is real: a small percentage self-direct their AI learning while the majority are left behind without programmatic support

Individual productivity gains are a vanity metric — what matters is whether AI unlocks new organizational capabilities and a more ambitious mission

The shift for workers is from doing the task to building, monitoring, and maintaining the AI that does it — durable skills like systems thinking are central to that transition

Adjacent competencies unlocked by AI are where breakthrough innovation happens, especially at the intersection of previously siloed domains

Responsible AI and the triple bottom line — people, profit, and planet — must be woven into AI native organizations from the start

Quotes

"A piano is easy to use — you can dink around on the keys all day, but it's not really easy to learn."

"You can't get 21st century results with the 20th century operating system."

"With great power comes great responsibility — and I don't think there's enough attention being put to the implications of AI."

"The shift is from creating to building, monitoring, or maintaining — and there will always be room for the artisans."

"AI changes who can do what — and that's where the innovation is, at the overlay of disciplines."

Chapters

00:02 Welcome and introductions 

01:17 Melissa's non-linear path and the origins of Hyperadaptive 

03:49 Systems thinking, transferable skills, and shared career philosophies 

05:13 Unpacking AI native and what it means for organizational design 

07:53 Why large enterprises are struggling and the aircraft carrier analogy 

09:21 AI maturity, readiness, and knowing where to draw the line 

11:14 The biggest mistake: neglecting human support structures 

13:57 AI activation hubs, AI leads, and dynamic governance 

19:14 Centralized vs. functional governance layers 

23:14 Where most organizations stand in early 2026 

26:16 Individual productivity as a vanity metric 

28:02 Unlocking organizational potential beyond current capabilities 

31:22 Adjacent competencies, durable skills, and the future of careers 

37:48 Systems thinking and redesigning work 

40:05 Career lattices, value streams, and Unilever's talent model 

43:10 AI governance, responsible AI, and the triple bottom line 

50:48 Melissa's book release details

Melissa Reeve: https://www.linkedin.com/in/melissamreeve

Hyperadaptive Solutions: https://hyperadaptive.solutions

For advisory and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠