Rewiring the American Edge

About Rewiring the American Edge

Global conversations on innovation, automation, and the future of competitive cities. Rewiring the American Edge is a podcast that explores building economies that are sustainable and inclusive in the era of automation and innovation. While rooted in the challenges and opportunities of the U.S. economy, the podcast invites voices from around the world—policymakers, technologists, labor leaders, and entrepreneurs—to share bold ideas and real-world strategies that transcend borders. Each episode explores trends such as: technologies reshaping work and urban life; global trends opportunities and challenges; specific investments, ideas, partnerships and policies to build a future-ready economy and workforce. This is a podcast for anyone committed to building smarter systems and stronger communities. Big ideas. Bold policies. Real impact. Rewired.

Publisher

Dr. Billy Riggs, Vipul Vyas

Category

business · news

Language

en

Explicit

No

First episode

2 May 2025

Latest episode

5 Nov 2026

Latest episodes

26 episodes in the feed.

1. 

   5 Nov 2026

   S2E6 | Nov 4, 2026 - Physical AI Part 1 - Who Builds It?

   Who builds the AI future? The answer reaches far beyond Silicon Valley. In the first installment of a three-part series on physical AI, Billy Riggs (https://www.linkedin.com/in/billyriggs/)  explores the people, infrastructure, and institutions that turn digital intelligence into real-world systems. From autonomous vehicles and robotic ports to factories and public transportation, the challenge extends beyond developing better models. It involves installing, operating, maintaining, and governing technology where people live and work.  Drawing on his research in autonomous mobility and city planning, Billy examines why curb management, public procurement, workforce training, and reliable infrastructure deserve a central place in the AI conversation. He makes the case that national competitiveness will depend on the capacity to build—and that cities can become essential partners in that effort. Takeaways and Key Themes From invention to deployment: Why advances in AI depend on physical infrastructure and institutional capacity to reach everyday life. Lessons from autonomous vehicles: What curb access, pickup and drop-off space, power, and communications reveal about integration. Connecting AVs and public transit: How station-area partnerships could support first- and last-mile travel while aligning public and private interests. The physical AI workforce: The role of electricians, technicians, construction crews, surveyors, fleet operators, educators, and public servants. Planning beyond the model: Why firsthand observation and local knowledge remain essential as AI enters planning practice. Cities as innovation partners: How permitting, procurement, workforce development, and management of public space can help turn inventions into useful services. The physical AI economy will be built by a much broader workforce than the technology conversation usually recognizes. The opportunity is to connect software expertise with skilled trades, public institutions, and the practical work of making systems function in the real world. Soundbites “AI doesn't change society when someone trains a model. It changes society when it gets deployed on society.” — Billy Riggs “The limiting factor are the issues of integration. They're the issues where the digital world touches the physical world.” — Billy Riggs “If we want to do autonomous transit or autonomous logistics in ports, who's going to actually do the physical work? Who's going to build it?” — Billy Riggs “How do local governments … become innovation partners instead of just regulators with the police power?” — Billy Riggs “The future of physical AI is bigger than computer science.” — Billy Riggs Chapters 00:00 The AI race is really a deployment race 04:08 The people and institutions missing from the AI picture 05:18 Why autonomous vehicle integration is harder than the technology 07:22 How AVs could support public transit through procurement 10:44 What past infrastructure revolutions teach us about AI 12:47 Physical AI needs a broader workforce than coders 15:49 Why city planning still needs human observation Reseources Riggs, W., & Cornet, H. (2026). Autonomous vehicles and public transit incentives: A Case study of Waymo’s pilot transit credit program in the San Francisco Bay Area. Transportation Research Interdisciplinary Perspectives, 38, 102045. https://doi.org/10.1016/j.trip.2026.102045 (https://doi.org/10.1016/j.trip.2026.102045) The Planner’s Use of Information, edited by Hemalata C. Dandekar (https://www.amazon.com/dp/1138487260?plpRedirect=mhFallback&ref=clp_cat_book-author_p_4) — referenced in the discussion of site reconnaissance and the importance of observing communities firsthand.

2. 

   10 Jun 2026

   S2E5 | June 10, 2026 - Agents are Amoung Us

   Artificial intelligence is no longer just a tool that answers questions—it is increasingly becoming a participant in the workplace. In this episode co-hosts Billy Riggs (https://www.linkedin.com/in/billyriggs/) and Vipul Vyas (https://www.linkedin.com/in/vipulnvyas/) explore the emergence of AI agents, the changing nature of work, and what happens when organizations can deploy digital workers capable of performing research, analysis, content creation, and operational tasks at scale. The conversation examines whether AI agents represent a fundamentally new technological revolution or simply the next step in a long continuum of automation. From farm equipment to factory robots, from websites to software automation, Billy and Vipul discuss how today’s agents are reducing cognitive drudgery and enabling organizations to focus on higher-value work. Drawing on examples from education, software development, autonomous vehicles, and organizational management, the hosts explore how AI is changing productivity, experimentation, and innovation. They also tackle the challenges that come with technological transformation, including workforce dislocation, organizational adaptation, and the need for critical thinking in an increasingly automated world. Ultimately, this episode argues that the future belongs not to organizations that resist these technologies, but to those that learn how to integrate them effectively and empower employees to experiment, adapt, and innovate. Takeaways and Key Themes AI Agents Are Different From AI Assistants: rather than simply responding to prompts, agents pursue goals, execute tasks, coordinate workflows, and generate outcomes through a sequence of actions. While previous technological revolutions focused primarily on physical labor, AI agents increasingly automate portions of cognitive work—including research, synthesis, organization, and analysis. Rather than replacing expertise, agents may amplify expertise by reducing low-value work. Researchers spend less time searching. Developers spend less time coding. Managers spend less time organizing. Professionals spend more time interpreting, deciding, and creating. As information becomes easier to access and process, the ability to evaluate, question, and synthesize becomes increasingly important. Education must adapt to models that prioritize procedural knowledge over problem-solving. AI dramatically lowers the cost of prototyping ideas, testing concepts, and launching products. Organizations should empower employees to solve their own problems with AI tools. While productivity gains are significant, the challenge for leaders is managing dislocation while enabling innovation and adaptation. Soundbites “We’re moving from talking about AI as a tool to talking about AI as a worker... We’re not automating physical labor. We’re automating portions of cognitive labor.” — Billy Riggs “I don’t think there’s a lack of problems to solve. The question is how quickly organizations can absorb these tools.”  — Vipul Vyas “A human bases decisions on one lived experience. An agent can draw on millions.” — Vipul Vyas “In education, critical thinking is going to become even more important... The combination of philosophy and engineering may become more valuable than either one alone.” — Vipul Vyas “You’ve never been able to fail faster. And you’ve never been able to move faster toward product-market fit.”  — Billy Riggs “If you can think it, you can probably build it.” — Vipul Vyas Chapters 00:00 - The Evolution of Work and Technology 04:07 - Understanding AI Agents in the Workplace 06:47 - The Impact of Automation on Employment 09:12 - The Role of Critical Thinking in the Age of AI 11:56 - Transforming Education for Future Work 14:27 - Experimentation and Agility in Organizations 17:00 - The Future of Work: Embracing Digital Minions 19:45 - Navigating Risks in Technological Advancements 29:09 - The Innovator's Dilemma and Organizational Management 34:36 - The Risk of Dislocation and the Reward of Experimentation

3. 

   19 May 2026

   S2E4 | Apr 03, 2026 -The Great Platform Race

   On this episode of Rewiring the American Edge, co-hosts Billy Riggs (https://www.linkedin.com/in/billyriggs/) and Vipul Vyas (https://www.linkedin.com/in/vipulnvyas/) unpack the emerging “platform race” reshaping mobility, automation, and the future of transportation systems. What begins as a conversation about autonomous vehicles quickly expands into a deeper discussion about platform economics, capital strategy, infrastructure dependency, and the growing era of “coopetition” — where companies simultaneously compete and collaborate. The discussion centers heavily on the strategic evolution of Uber Technologies and how the company has repositioned itself not as the definitive winner of the autonomous vehicle race, but as a platform layer sitting above the race itself. Rather than carrying the enormous burden of developing full self-driving systems internally, Uber has pursued partnerships across AV developers, OEMs, logistics providers, and delivery companies — effectively spreading risk while maintaining ownership of the customer relationship. Billy frames this as a textbook business strategy case: vertically integrated companies like Waymo, Tesla, and Zoox control the full stack — vehicle, software, operations, and data — but in doing so absorb massive capital costs, regulatory uncertainty, and technological risk. Uber, by contrast, is pursuing a diversified and capital-light strategy built around optionality, flexibility, and interoperability. Vipul expands the discussion by comparing Uber’s position to companies like Amazon and even the airline industry. The conversation explores how transportation may increasingly resemble a service marketplace rather than an ownership model, especially among younger generations who are less interested in owning private vehicles. Instead of owning the underlying assets, future mobility companies may focus on orchestrating access, logistics, and multimodal transportation experiences. The episode also tackles broader questions around latent transportation demand, congestion, environmental tradeoffs, and shared mobility economics. Billy argues that rideshare and autonomous mobility services are not necessarily “creating” transportation demand, but instead unlocking previously unmet mobility needs for seniors, younger users, and people with disabilities. In the final segment, the conversation pivots toward what Billy argues is the most overlooked factor in automation: infrastructure and governance. Autonomous systems do not operate in isolation. They depend on curb management, charging infrastructure, transit integration, pickup/dropoff logistics, communications systems, and city governance. The companies most likely to succeed may not simply be the ones with the best AI or vehicles, but the ones that learn to collaborate effectively with cities and navigate systems complexity.  Ultimately, the episode argues that the future of mobility will not be defined solely by who builds the best self-driving car. It will be shaped by who best understands platforms, partnerships, infrastructure, governance, and the evolving relationship between technology and cities. Takeaways and Key Themes Autonomous mobility is increasingly shifting from pure competition toward strategic ecosystem partnerships. Platform ownership and customer relationships may become more valuable than owning the physical vehicles themselves. Transportation systems are evolving toward flexible, multimodal access rather than private ownership. Infrastructure and governance remain the hidden bottlenecks of AV deployment. Cities are not passive regulators — they are active participants shaping the operational success of automation. The future winners in mobility may be the companies best able to manage uncertainty, partnerships, and systems integration simultaneously. Soundbites “Automation is uncertain… companies like Uber are saying: we’ll work with whoever wins.”  — Billy Riggs “Most cars sit around… they’re trapped assets. They’re poorly utilized assets.”  — Vipul Vyas “The companies that understand cities first are the ones that are going to win.”  — Billy Riggs

Who has been a guest on Rewiring the American Edge

Names identified in recent episode analyses. Showing up to five guests.

• Lee Riggs
• Dr Henriette Cornet
• Ruth Whittaker
• Seneca Scott

Reach and audience

Public platform figures. Ratings count people who left a rating, not total listeners.

YouTube views

913,970

Score snapshot 15 Sept 2025

Apple Podcasts (US)

5.0 / 5

1 ratings

Podcast Authority Score: 62 / 100

A composite of feed quality, social presence, YouTube performance and engagement. Read the methodology.

Quality

89

Social presence

0

YouTube

86

Engagement

0

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Guest appearances

Does not typically book guests

Based on episode analysis; this does not confirm that the show is currently accepting guests.

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