Humans of AI: Presented by WRITER

Companies spend years building dashboards that told them what to know. Now they’re building AI that tells them what to think.But what companies actually need is AI that takes action on their best ideas.Bruno Aziza, VP, Enterprise Software at IBM, shares why so many AI deployments fail — and the frameworks that separate successful implementations from expensive pilot programs.His insight: one customer now has "50 humans and 150 agents" on their team . The question isn't whether agents will reshape work. It's whether we're building agents that actually do the work.Key frameworks from this conversation:→ Agent Minus: The essential pre-agent infrastructure (rules, tools, workflows) that make agents work → Agent Plus: Orchestrating hundreds of agents across vendors and systems → FOMO vs. FOMU: The psychological traps killing AI adoptionThe rule Bruno lives by: "Process useful: automate. Process not useful: eliminate."Most organizations skip step two.Subscribe to Humans of AI for more stories from people navigating the intersection of business and artificial intelligence.Watch the full video interview on the WRITER YouTube channel for bonus content and deeper insights.Learn more about WRITER at writer.com. 

What happens when marketing AI stops finding the right customer and starts finding the right moment of weakness? Nicole Alexander, former Global Head of Marketing at Meta and author of "Ethical AI in Marketing," takes us inside one of the most uncomfortable truths about modern marketing technology.Nicole reveals how optimization algorithms don't just target demographics anymore — they identify emotional vulnerability. We explore the distinction between growth as a physics problem and responsibility as a human problem, and why the assumption that efficiency equals ethics is fundamentally broken.Nicole shares her framework for building AI systems that scale without exploitation, explaining why the question isn't "Is this ethical?" but rather "What constraints would make this sustainable?" She offers a provocative reframe: the conversion that destroys trust isn't a win — it's technical debt on your customer lifetime value.This conversation challenges marketers to rethink how they measure success, engineers to redesign how they optimize, and leaders to consider what it means to build AI that serves people rather than simply converting them.Key Takeaways:Why AI-driven systems ask "What vulnerability is the most profitable lever to pull?"How algorithms engineered for time spent inevitably reward outrageThe business case for treating trust as a technical constraint, not a review stepWhy guardrails should be part of optimization itself, not added laterNicole Alexander is a Professor at NYU, author of "Ethical AI in Marketing," and former Global Head of Marketing at Meta, where she led teams building some of the world's most sophisticated marketing systems.Subscribe to Humans of AI for more stories from people navigating the intersection of business and artificial intelligence.Watch the full video interview on the WRITER YouTube channel for bonus content and deeper insights.Learn more about WRITER at writer.com. 

What does it take to reinvent a 10-year-old company when AI changes everything overnight? Dan O'Connell, CEO of Front, knows the answer‌ — ‌and it's not what most boards want to hear.Dan shares the framework he's using to lead Front through an existential transformation from legacy player to AI-first platform. Drawing on lessons from building TalkIQ, scaling through Google's hypergrowth, and growing Dialpad from dozens to over a thousand employees, Dan reveals how pattern recognition becomes your superpower when navigating change at scale.Dan's framework isn't just about AI‌ — ‌it's about building the kind of organization where everyone knows their role, understands the mission, and can move fast without losing control. Whether you're leading a startup or transforming an enterprise, this conversation will change how you think about structure, transparency, and what it really takes to build AI-first.In this episode, you'll discover:The three-part diagnostic for determining if your company needs AI-first reinvention (Spoiler: If you're asking, you probably do)Why structure and process don't slow innovation—bad structure does The leadership mistake Dan made in his first 90 days that became his most valuable lesson • How transparency drives decision velocity and distributed decision-making at scale Why Front is betting that human touch becomes the competitive advantage when automation becomes table stakes The paradox of alignment: Why being explicit about what you're NOT doing matters as much as what you areSubscribe and Listen:🎧 Apple Podcasts | Spotify | YouTubeLearn more at writer.com Subscribe to Humans of AI for more stories from people navigating the intersection of business and artificial intelligence.Watch the full video interview on the WRITER YouTube channel for bonus content and deeper insights.Learn more about WRITER at writer.com. 

Late 2024, Logitech surveyed their entire workforce about AI usage. Seven thousand employees. 46 countries. When Eric Porres saw the results, he stopped calling it an adoption problem.Eric had spent the year running AI training sessions across Logitech—not as his official job, but as a second shift while leading innovation and software teams. 827 people over eight months. And in those sessions, he kept hearing the same story: people approached generative AI like they approached Google. Ask a question. Get an answer. Walk away unsatisfied. They didn't realize they could iterate, refine, and improve.Then Eric discovered something remarkable: hidden in the survey data were 112 people doing exceptional work with AI. He started asking them to walk him through their process—not what they were building, but how they were thinking. And a pattern emerged around six elements.In this episode of Humans of AI, Eric shares the framework that transformed Logitech's AI adoption—and why the biggest barriers to enterprise AI aren't technical. They're human.In This Episode, You'll Learn:• Why most people treat AI like a vending machine—and how to break that habit• The 6-element DNA strand of effective AI prompting: role, context, task, output, boundaries, and reasoning• How to identify and activate AI champions already hiding in your organization• The two barriers that kill AI adoption: friction and institutional amnesia• Why leadership modeling matters more than training programs• How one question at every leadership meeting can transform your AI culture• The discipline required to make AI transformation permanent—not just another pilot programAbout Eric Porres:Eric Porres is the Head of AI at Logitech, where he leads enterprise AI strategy and adoption. A fifth-degree black belt with 20 years of ninjutsu training, Eric brings the same discipline and pattern recognition to AI transformation that he learned in the dojo. Before joining Logitech full-time, he founded a company to fix broken meeting culture—analyzing how organizations burn payroll dollars on ineffective collaboration—and sold it to Logitech in 2022. When Logitech created the Head of AI role in 2025, Eric had already done the groundwork: he had the data, the champions, and a framework that scaled.🎧 Listen now and discover how to move from 1% adoption to organization-wide AI transformation.Learn more about Writer at writer.comSubscribe to Humans of AI for more stories from people navigating the intersection of business and artificial intelligence.Watch the full video interview on the WRITER YouTube channel for bonus content and deeper insights.Learn more about WRITER at writer.com. 

What's the difference between a $10 billion company and one that fails? The technology? The timing? The IP?According to Jevan Lenox, Chief People Officer at WRITER, it comes down to culture. And in the age of AI, that gap is about to get much wider.In this episode of Humans of AI, Jevan shares why AI doesn't just change your processes—it amplifies everything, including your cultural dysfunction. From his experience leading people teams at Insitro and Stitch Fix, he's learned that the companies that win aren't the ones with the best AI—they're the ones with cultures built for what's coming.You'll learn:• Why AI adoption is fundamentally a cultural problem, not a technical one• How to shift from efficiency culture to resilience culture• Why everyone in your organization now needs strategic thinking skills that used to be management-only• How to help employees navigate identity shifts as AI changes their roles• The difference between AI as replacement versus AI as amplificationThis isn't about rolling out another tool. It's about building the invisible architecture that determines whether your AI transformation succeeds or fails.Subscribe to Humans of AI on your favorite podcast platform and check out the video version on YouTube.Learn more about WRITER at writer.com.**Download the Agentic Compact:** WRITER's framework for building AI-ready organizations at https://go.writer.com/the-agentic-compactSubscribe to Humans of AI for more stories from people navigating the intersection of business and artificial intelligence.Watch the full video interview on the WRITER YouTube channel for bonus content and deeper insights.Learn more about WRITER at writer.com. 

Matan-Paul Shetrit, Director of Product Management at WRITER, has a background in public policy and product design. He discusses how regulated industries like healthcare are surprising leaders in AI transformation. Matan-Paul emphasizes that the real challenge lies in managing a hybrid workforce of humans and AI agents, which he likens to unpredictable interns. As everyone will need to adopt managerial skills, he calls for a focus on iterative work and critical thinking over mere reliance on AI outputs, warning against treating AI as infallible.

What does accountability mean when AI can make thousands of decisions before a human even notices? That’s the question Rowan Reynolds, General Counsel at Writer, is tackling. Rowan shares how his background in philosophy and law taught him that legal frameworks aren't just about what's legal—they're about what's right. And in the age of agentic AI, building those frameworks before disasters happen means treating AI agents like privileged users who work at far greater speed and scale than any employee.Rowan discusses the three core principles that make AI trustworthy (transparency, human-centricity, and security), and why companies are worried about the wrong things when the real challenge is organizational change. From the difference between "Big G" enterprise-wide governance and "little g" day-to-day deployment, to why we're building this in real time with no established playbook, Rowan offers a framework for building AI systems right instead of just asking what could go wrong.Subscribe now so you don't miss an episode! Check out our YouTube channel to watch the full interviews. Learn more about WRITER at writer.com. Subscribe to Humans of AI for more stories from people navigating the intersection of business and artificial intelligence.Watch the full video interview on the WRITER YouTube channel for bonus content and deeper insights.Learn more about WRITER at writer.com. 

Why are organizations throwing money at AI without investing in the people who use it? And where is the disconnect between technology adoption and real business results?On this episode, we hear from guest speaker J.P. Gownder, one of the world's leading analysts on the future of work. With a background in history and political science and as VP and principal analyst for Forrester’s Furture of Work team, J.P. brings a unique, human-centric perspective to the world of technology. For over a decade, he has guided leaders at billion-dollar corporations through immense change, urging them to focus on the human side of AI and automation.Listen to learn about Forrester’s concept of "AIQ" (Artificial Intelligence Quotient) as a measure of an organization's readiness for AI. He explains why the old rulebooks for technology rollouts don't work for generative AI and provides a masterclass in effective training‌ — ‌from social learning and champions programs to creating proprietary content that reflects your company's context. He also debunks the myth of mass job replacement, arguing that AI is far more often an augmentation technology than a replacement one.Subscribe now so you don't miss an episode! Check out our YouTube channel to watch the full interviews. Learn more about WRITER at writer.com. Subscribe to Humans of AI for more stories from people navigating the intersection of business and artificial intelligence.Watch the full video interview on the WRITER YouTube channel for bonus content and deeper insights.Learn more about WRITER at writer.com. 

Kavitta Ghai, co-founder and CEO of Nectir, shares her journey from student frustrations to launching an AI-powered edtech startup while at UC Santa Barbara. She reveals how her experience with Slack inspired a classroom communication tool and how her no-code approach allowed her to prototype without a technical background. Kavitta discusses the advantages of starting young, transforming a simple MVP into a business, and building relationships over features. She also emphasizes the importance of resilience, customer discovery, and navigating the venture capital landscape as a first-generation founder.

Dan Bikel, Writer's Head of AI and a veteran in the field with three decades at leading labs, discusses the shift from model obsession to building reliable AI systems. He argues for focusing on business needs before diving into research and outlines his strategy of 'Scale, Speed, Specificity.' Bikel highlights the dangers of model unpredictability for enterprises and promotes the idea of an 'agentic age' where AI systems can act autonomously. He also shares insights on hiring and investment for successful AI operations.