Feedforward Member Podcast

Today, we’re talking with Josh Saxe, an AI security engineer and founder, about what AI actually changes in cybersecurity and what it doesn’t. Josh breaks down who is really behind most attacks, from scam and fraud operations to ransomware groups and nation states, and why even criminals run into the same hiring and adoption hurdles as any other business. He and Adam explore why security has always been a trade-off between protection and friction, and how AI could make strong security far cheaper for defenders. We also get practical about the AI agents already running inside most large companies, including why every agent should have only the access it needs and why letting agents read and act on content from the open web is a decision for the C-suite. So, let’s get into it!

Takeaways:

• Attackers have been slower to adopt AI than many experts predicted, and that gives defenders a window to prepare.
• The groups doing the most damage today are scam and fraud operations, ransomware groups, and nation states. They all hit the same talent and adoption bottlenecks as any other business.
• AI raises the overall level of risk rather than pushing us off a cliff. Security budgets and urgency should go up, but there’s no need to panic.
• Defenders benefit from cheap, widely available AI, because protecting a network takes an enormous amount of AI work, from scanning code to monitoring every device.
• Companies running AI agents need to know which agents they have, give each one only the access it needs, and monitor what they do.
• Security comes down to how much friction an organization is willing to accept. That makes choices like what your agents can read and run a decision for the C-suite and the board.

Today, we’re diving into the world of agentic commerce with Jason Goldberg, who’s been riding the digital commerce wave since way before Amazon was even a blip on the radar. The big takeaway from our chat? Agentic commerce is rolling in faster than any previous disruption we’ve seen, and the tools we’ve got to navigate this shift are still figuring themselves out. But here’s the kicker: even if they’re not perfect, we’ve got to start using them to keep up. Jason breaks down why it’s crucial to lean into these changes now instead of waiting for everything to be fully polished. We also explore how this evolution is reshaping not just the retail landscape but the very way we think about buying and selling. So grab your headphones, and let’s get into it!

Takeaways:

• Agentic commerce is moving faster than previous disruptions, so businesses need to adapt quickly.
• Understanding the tools for agentic commerce is crucial, even if they aren't perfect yet.
• Companies risk falling behind if they wait for perfect conditions to adopt new technologies.
• The importance of leadership in guiding organizations through the transition to new commerce models is paramount.

We're diving deep into the wild world of AI and its exponential growth in this episode. Alex Imas, an economist from the University of Chicago, breaks down how traditional economic models, which are all about diminishing returns, might not hold up in the face of AI's rapid advancements. We chat about how the pace of change isn't just fast; it's accelerating in ways we’ve never seen before, raising big questions about what that means for our economy and businesses. If AI can improve itself quickly, it challenges everything we thought we knew about growth and productivity. We also tackle the potential for AI to completely reshape industries, forcing us to rethink job roles and how companies operate. So, if you're curious about the future of work and the economic landscape, stick around—this conversation is packed with insights!

Takeaways:

• The concept of exponential growth in AI is crucial, as it challenges conventional economic models that are typically based on diminishing returns.
• Understanding that AI's growth could fundamentally alter economic models is essential for adapting to new realities in business and technology.
• The discussion emphasizes that AI's recursive self-improvement could lead to unprecedented advancements, but it also poses risks and uncertainties for the economy.
• To prepare for the future, organizations must embrace AI's capabilities while being aware of the potential constraints and political dynamics that could affect growth.
• The importance of viewing AI not just as a tool for efficiency but as a transformative force that can reshape markets and consumer preferences is highlighted.
• Companies should rethink their structures to leverage AI effectively, moving from traditional roles to more technology-centered approaches for maximizing productivity.

Today, we dive deep into the world of AI development with a legendary figure, Kent Beck, who’s been a game-changer in software development. Kent emphasizes that building software, especially with AI, is all about embracing change and iterating over time. Forget the old-school mindset of getting everything perfect upfront; instead, we should focus on small, manageable cycles of development that allow for continuous learning and adaptation. Kent's insights on Test Driven Development and refactoring are not just relevant—they're crucial for anyone looking to harness the power of AI effectively. We also chat about the importance of fostering collaboration between developers and non-developers, making technology more accessible and less intimidating for everyone. So, whether you’re coding in your spare time or leading a team, there’s something here for you to take away and apply to your own projects.

Takeaways:

• Building with AI requires us to embrace change and adapt as we learn, much like software development.
• Key principles from software development, like Test Driven Development and Agile, are crucial for AI tool creation.
• Understanding that development is an iterative process helps demystify coding and encourages experimentation.
• Embracing a beginner's mindset allows us to explore new possibilities in software and AI with excitement rather than fear.

Today’s chat dives deep into the evolving landscape of work in the age of AI. We’re checking in with Daniel Rock, a Wharton professor and Expert here at Feedforward, to reflect on how our understanding of AI’s impact has shifted over the past year. It’s all about grappling with the reality of what AI means for jobs and organizations—are we headed toward a future where work is fundamentally transformed, or are there still plenty of opportunities for humans? Daniel’s got some fresh insights, examining whether the nature of jobs will change or if the fear of widespread job loss is overstated. We’ll also unpack the implications of these changes, not just for individuals, but for society at large. So, let’s get into it!

Takeaways:

• In this episode, we reflect on how AI is reshaping jobs and organizations, emphasizing that while job structures may shift, work itself will persist in various forms.
• The conversation highlights Daniel Rock's evolving insights on AI's impact, revealing a complex landscape where automation alters the nature of tasks rather than eliminating jobs entirely.
• We discuss the growing reliance on AI agents within workflows, marking a transition from single-task automation to the deployment of multiple agents in various roles.
• The episode underscores the importance of adaptability in the workforce as AI technologies evolve, suggesting that continuous learning will be crucial for future job security.
• A key takeaway is the idea that while AI can enhance productivity, it also raises questions about the future of work and the societal implications of reduced job availability.
• We explore the tension between optimism and concern regarding AI, noting that successful integration of these technologies hinges on thoughtful organizational strategies and employee engagement.

Today, we’re diving deep into vibe coding, a concept that’s really shaking things up in the software world. I’m chatting with Steve Yegge, a well-known software engineer and co-author of the book "Vibe Coding." Even if you're not a coder, the ideas we discuss are super relevant, especially as vibe coding makes software development more accessible to everyone. We’re all about exploring how this shift allows folks to create their own software solutions without needing to be full-on developers. We’ll break down the challenges and opportunities that vibe coding presents, and how it can help us all feel more in control of our tech. Whether you're a seasoned pro or just curious, there's something here for you.

Takeaways:

• Vibe coding is a new approach to software development, making it more accessible to non-developers and those returning to coding after a break.
• The podcast highlights the importance of engaging with AI tools to enhance coding skills and streamline the development process effectively.
• There's a growing shift in software development where non-engineers are becoming more involved, leading to a collaborative environment between tech and business teams.
• Effective communication between developers and business folks is facilitated by AI, reducing misunderstandings and fostering a more productive work atmosphere.
• The concept of 'vibe coding' lets people create software more intuitively, focusing on their ideas rather than getting bogged down by technical specifics.
• Using tools like Beads helps keep track of tasks and enhances project organization, ensuring nothing falls through the cracks during the coding process.

In this episode, Adam Davidson goes inside Google’s AI teams with Logan Kilpatrick, who leads developer products including the Gemini API and AI Studio. Logan shares how Google is moving from AI experimentation to real-world deployment—and what’s changed as these tools start to work at scale.

They discuss how AI Studio has evolved into a builder-first platform, the rise of “vibe coding” across teams like product, sales, and legal, and why recent Gemini models have crossed a threshold from demos to practical use. The conversation also explores how Google approaches deploying probabilistic systems, and what enterprises need to rethink as they move from pilots into production.

Looking ahead, Logan outlines where Google’s AI teams are focusing next—from more capable agents to proactive AI systems that support decision-making rather than simply responding to prompts.

Takeaways:

1. AI Studio is a powerful platform for developers, providing useful tools like the Gemini API that streamline the integration of AI models into products.
2. Logan Kilpatrick highlights the significance of Vibe coding, which transforms how people within Google approach their work and enhances productivity.
3. The conversation emphasizes the need for enterprises to shift from deterministic thinking about AI to understanding its probabilistic nature for better deployment outcomes.
4. One key takeaway is the evolving landscape of AI, with models like Gemini 3 showcasing significant advancements that can change how organizations operate.
5. The podcast discusses the importance of a proactive AI that can assist users in making decisions rather than being solely reactive to user prompts.
6. Listeners are encouraged to explore AI Studio for building AI tools, as it now offers a more accessible entry point for developers looking to innovate.

Today's chat dives deep into the ever-evolving landscape of AI with none other than Tim O'Reilly, a titan in tech publishing and an insightful thinker. Tim emphasizes that the future of AI isn’t a solo act; instead, it’s an ongoing jam session where everyone contributes to the melody. We explore how our perceptions of technology need to shift, much like the transitions from IBM to Microsoft and the birth of Web 2.0, highlighting that nimble thinkers who adapt quickly will hold the keys to new opportunities. Tim also shares his vision of a multipolar AI world, where collaboration and shared innovation drive progress rather than monopolistic control. It's a compelling conversation that challenges us to rethink how we engage with and shape the future of AI.

Takeaways:

• Tim O'Reilly emphasizes the importance of creating new frameworks to understand rapidly evolving technologies like AI and their societal impacts.
• The conversation highlights how historical shifts in technology often result in new mental models that broaden our understanding of possibilities.
• O'Reilly believes that the future of AI isn't predetermined by a single entity but shaped collectively by various players exploring new ideas and applications.
• A key takeaway is that organizations should focus on how AI can expand their capabilities rather than just increasing efficiency or replacing jobs.
• The episode discusses the necessity for diverse competition in AI to foster innovation and prevent monopolistic practices that stifle new ideas.
• Tim argues that the true value in AI is derived from enabling new forms of collaboration and participation across industries, rather than simply optimizing existing processes.

Nicolai Tangen, the CEO of the Norwegian Sovereign Wealth Fund, dives deep into his radical approach to integrating AI in asset management, claiming to be the “Madman in Chief” of AI. He shares how he achieved 100% AI usage across the fund, focusing on relentless internal communication and education to drive acceptance and implementation. We explore the transformative impact of AI on productivity, with Tangen citing impressive gains in efficiency that would keep the fund competitive in a rapidly evolving landscape. He also addresses common resistance points, emphasizing the importance of understanding and overcoming compliance concerns to harness AI’s full potential. Whether you’re leading an organization or just trying to keep up with the AI wave, Tangen’s insights are invaluable for navigating this new frontier.

Takeaways:

• Nicolai Tangen, CEO of the Norwegian Sovereign Wealth Fund, emphasizes the need for relentless advocacy for AI within organizations.
• He believes that companies must embrace AI fully or risk falling behind their competition, as compliance can kill innovation.
• Incorporating AI successfully requires a mix of technical knowledge and a willingness to adapt, which can lead to a culture shift in organizations.
• Tangen highlights the importance of continuous upskilling for employees, indicating that mandatory training sessions have been effective in boosting AI usage.

Companies mentioned in this episode:

• Norwegian Sovereign Wealth Fund
• ChatGPT
• Claude
• Cursor
• Morgan Stanley
• Goldman Sachs
• JP Morgan
• Anthropic
• OpenAI
• Google

The future of work is a hot topic, especially with AI shaking things up in ways we can't ignore. This episode dives deep into this question with Rebecca Hinds—not just any guest, she’s got a PhD in how AI transforms work and leads the Work Transformation Lab at Glean. We discuss how organizations are currently using AI and what that means for the structure of work in the future. Rebecca shares her insights from research showing that it’s not just about individuals adopting AI, but how teams and entire organizations can leverage it to improve workflows and collaboration. We explore the challenges companies face in scaling AI and how a more integrated approach can change the game for everyone involved.

Alongside her research, Rebecca also brings a practical lens to collaboration as the author of Your Best Meeting Ever, a blueprint for transforming meetings from time-wasters into powerful tools for teamwork and innovation.

Takeaways:

• The future of work is heavily influenced by AI, but there's still much uncertainty about its impact on jobs and organizations.
• Organizations struggle with AI adoption as many employees remain skeptical and are fearful of being replaced by technology.
• Successful deployment of AI requires understanding workflows and empowering the right influencers within organizations to drive change.
• The transformation of work is not just about individual tasks but rethinking entire work streams and team dynamics in a collaborative manner.
• AI has the potential to automate busy work, allowing employees to focus on more strategic and creative tasks, leading to a more engaged workforce.
• Creating a psychologically safe environment is crucial for employees to share their experiences and ideas about using AI without fear of negative repercussions.

Links referenced in this episode:

• Your Best Meeting Ever, by Rebecca Hinds

Companies mentioned in this episode:

• Feedforward
• Asana
• Glean