Page de couverture de Elevate Your AIQ

Elevate Your AIQ

Elevate Your AIQ

Auteur(s): WRKdefined
Écouter gratuitement

À propos de cet audio

 Bob Pulver is helping each of us navigate our respective journeys with artificial intelligence (AI) effectively and responsibly. Bob chats with AI and Future of Work experts, talent and transformation leaders, and practitioners who provide diverse perspectives on how AI is solving real-world challenges and driving responsible innovation.All rights reserved by WRKdefined Développement commercial et entrepreneuriat Entrepreneurship Gestion et leadership Économie
Épisodes
  • Ep 111: Building and Managing AI Agents to Shape the Future of Work with Jacob Bank

    Ep 111: Building and Managing AI Agents to Shape the Future of Work with Jacob Bank
    Mar 27 2026
    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.com⁠⁠⁠Substack: ⁠https://elevateyouraiq.substack.com⁠
    Voir plus Voir moins
    53 min
  • Ep 110: Rewiring Organizations for Human-Centric AI Transformation with Melissa Reeve

    Ep 110: Rewiring Organizations for Human-Centric AI Transformation with Melissa Reeve
    Mar 20 2026
    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
    Voir plus Voir moins
    52 min
  • Ep 109: Championing Human Originality to Accelerate AI Transformation with Jonathan Aberman

    Ep 109: Championing Human Originality to Accelerate AI Transformation with Jonathan Aberman
    Mar 13 2026
    Jonathan Aberman — venture capitalist, entrepreneur, educator, and CEO of Hupside — joins Bob Pulver to explore why AI readiness is fundamentally a human potential problem. Hupside's Original Intelligence Quotient (OIQ) provides an objective measurement of human originality relative to AI output, giving organizations a clear signal of who can thrive in an AI-augmented environment, who needs development, and how to compose teams for transformation. Jonathan and Bob dig into the dangerous feedback loop that AI can create when misused, and why originality is the true competitive differentiator. The conversation spans higher education, venture capital, workforce design, and the future of digital credentials, all through the lens of keeping humans central to value creation. Keywords Jonathan Aberman, Hupside, OIQ, Original Intelligence Quotient, AI readiness, human originality, talent transformation, workforce design, higher education, venture capital, AI augmentation, digital credentials, collective intelligence, responsible AI, human-AI symbiosis Takeaways Hupside's OIQ objectively measures human originality against AI output, helping organizations identify who to develop, elevate, or support through AI transformation AI creates a self-reinforcing feedback loop that debilitates when misused — but as a tool, it can powerfully accelerate human creativity Originality equals novelty plus salience; AI can generate novelty, but humans remain essential for determining what's meaningful Higher education's real challenge isn't cheating prevention — it's teaching students to reason well with AI, then measuring output quality Misaligning high-OIQ talent with constrained roles leaves value on the table; matching autonomy to originality profiles is a key workforce design opportunity The greatest long-term AI risk may be whether rising capability gradually excludes people from competing as knowledge workers OIQ and AIQ scores are dynamic and improvable — making them well-suited for portable digital credential profiles Quotes "AI has a couple of limitations that make it different from every tool humans ever invented — it creates a self-reinforcing loop that can cause debilitation if not used properly." "We're the umpire in a baseball game. We're not the players — you and your listeners are the players." "AI is not a cheating problem, it's an education problem." "Originality is novelty plus salience. As long as humans are the ones consuming, AI will always be at best a lieutenant." "The more we [flood] society with sameness, the more people who stand out are going to be important." "I'm not worried about whether AI becomes sentient. I'm more worried about whether it raises the bar and starts to exclude people." Chapters 00:02 Welcome and introductions 02:58 The founding of Hupside and the OIQ origin story 05:35 AI readiness as a human potential problem 07:53 OIQ in higher education and rethinking assessment 09:11 K-12 considerations and bias mitigation 11:20 VC and portfolio applications of OIQ 15:11 Embedding OIQ into the talent lifecycle 19:56 Autonomy, role design, and workforce orchestration 24:42 Higher education, authenticity, and the value of originality 27:04 Innovation management and organizational barriers to AI adoption 34:52 Short-termism, Silicon Valley monoculture, and pushing back 39:25 Can LLMs become truly original? Shared novelty vs. human originality 43:20 Collective intelligence and the wisdom of crowds 48:53 Digital credentials, OIQ in talent profiles, and data ownership 54:43 What's next for Hupside and closing thoughts Jonathan Aberman: https://www.linkedin.com/in/jonathanaberman Hupside: hupside.com For advisory work and marketing inquiries: Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠Substack: ⁠https://elevateyouraiq.substack.com⁠
    Voir plus Voir moins
    56 min
Pas encore de commentaire