The Road to Accountable AI

Kevin Werbach speaks with Brett Levenson, co-founder and CEO of Moonbounce, about building real-time controls that make AI systems follow the policies companies write for them. Drawing on his years leading integrity work at Meta after the Cambridge Analytica scandal, Levenson explains why content moderation policies there could not be enforced consistently. His team shifted from a decision-first approach to what he calls info-first enforcement, breaking complex policies into simple yes-or-no questions organized in a decision tree. Reviewer consistency jumped dramatically. That atomized approach now underlies Moonbounce, which acts as a semantic firewall that evaluates every input, output, and action an AI takes.
Levenson argues that AI made the application layer non-deterministic, breaking security models that assume predictable software. He describes the challenge of making decisions within a few hundred milliseconds, and a decision memory system that keeps policies adaptive by incorporating customer corrections without hidden state. He also explains Moonbounce's move beyond simple allow-or-block choices to escalating to humans and rewriting outputs. Werbach and Levenson discuss the legal tension around audit trails, payment providers acting as de facto regulators, and why Levenson believes the industry needs measurable, falsifiable standards.
Brett Levenson is co-founder and CEO of Moonbounce. He left Apple in 2019 to lead business integrity at Facebook during the Cambridge Analytica fallout, and later headed Meta's Integrity unit. He co-founded Moonbounce with CTO Ash Bhardwaj, a former Apple engineering leader who built large-scale cloud and AI infrastructure. Moonbounce has raised $12 million in funding co-led by Amplify Partners and StepStone Group. 
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The Facebook insider building content moderation for the AI era

Kevin Werbach speaks with AI journalist Sharon Goldman about her new venture, Ground Level AI. Goldman describes taking on the AI beat at VentureBeat in 2022, months before ChatGPT launched, and then learning to translate technical developments for Fortune's broad business audience. She explains why she left to launch her own newsletter and podcast, focused on infrastructure, security, governance, policy, and the communities absorbing AI's effects.
Goldman shares her reporting from data center sites, and weighs how much of the data center backlash reflects local impacts versus broader anxieties about AI. The conversation turns to cybersecurity, where the speed and scale of AI-enabled attacks may outpace defenders. Goldman argues that the AI safety and cybersecurity communities, long divided by culture, must now work together. She closes on what she thinks is underappreciated: how quickly things are changing.
Sharon Goldman is the founder of Ground Level AI. She spent four years covering the AI boom, most recently at Fortune and before that at VentureBeat, and has more than 15 years of experience covering technology and business for publications including Business Insider, Forbes, and CIO. She launched Ground Level AI in June 2026 as a newsletter and podcast on Substack.
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Ground Level AI
Who gets a seat at the table to decide if frontier AI is safe?
AI safety and cybersecurity have long been two different worlds. In the age of AI agents, they're colliding

Kevin Werbach speaks with Robert Levitan, Chair of the Ethical Tech Project, about what the early internet can teach companies deploying AI today. Levitan, who helped build iVillage and Flooz.com in the dot-com era, argues that the central lesson of those years is that new technologies always carry unintended consequences. Moving fast and breaking things is untenable, he says, now that AI sits on top of the internet and mobile. Levitan explains his essay comparing a coming AI disaster to the 1911 Triangle Shirtwaist Factory fire, which spurred workplace safety laws and helped shape the New Deal. He expects a comparable AI catastrophe to trigger regulation, and urges executives not to wait for it. Trust is a competitive advantage, he argues, and litigation will arrive much faster than it did for the internet. The conversation closes with why Levitan remains an optimist despite the risks, pointing to healthcare's ethical framework and guardrails as a model for other industries.
Disclosure: Kevin Werbach is an advisor to the Ethical Tech Project.
Over thirty years, Robert Levitan has founded, scaled, and advised companies including iVillage, Flooz.com, and Pando Networks, and his recent work focuses on the societal impacts of AI. He studied history and public policy in college and describes himself as a serial entrepreneur whose ventures have ranged from a high-profile IPO to a high-profile bankruptcy to a private sale to Microsoft.
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Our AI Triangle Shirtwaist Moment Is Coming. Don't Be the Factory Owner (LinkedIn)
Pulse 2.0 interview with Levitan

In the final episode of our series on governing AI agents, Kevin Werbach speaks with Harish Peri, SVP and General Manager for AI Security at Okta. Peri frames agent governance as the natural next chapter of what Okta has done for two decades: standing in the middle of people accessing technology. The twist is that the new "software" is a non-deterministic agent with a brain, which imposes a much higher security bar. He argues that agents live at the application layer, where the real question is one of authorization: is this agent allowed to take this action or access this data, at this moment, on behalf of this user, given all available signals? Much of the conversation explores why a neutral, independent control plane separate from the frontier models and agent runtimes matters from a cybersecurity standpoint, spreading risk across multiple layers rather than concentrating it in one place.
Peri notes that while awareness of rogue AI is universal, roughly 20% of agents carry about 80% of the risk. He distinguishes security threats like prompt injection and poisoned skill files from "intent mismatch," where an under-specified instruction such as "clean this up" gets read as "delete," and explains how coarse-grained limits, fine-grained context-based authorization, and selectively applied human-in-the-loop checks each play a role in agent governance.
Harish Peri is the SVP and General Manager for AI Security at Okta, where he leads product, go-to-market, and commercial strategy for securing agentic AI. He has more than 20 years of experience across engineering, product management, marketing, and general management, spanning financial services, technology, and human capital management, with prior roles at Salesforce, ADP, and Proxyclick. He holds an MBA from the Haas School of Business at UC Berkeley.
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The Future of AI Security: The Right Architecture for Agents
Secure Your Business Against AI Agents

Logan Kelly never set out to build an AI governance solution. Waxell spun out of CallSine, an AI-native sales engagement platform, when the team realized that agents that could act on their own produced a cascade of problems: burning through tokens, accessing databases, creating data-quality issues, and generally doing things no one had explicitly approved. Unable to find existing tooling that addressed the problems effectively, the team built a control plane for agents, which became the foundation of Waxell. 

In this episode in our series on governing AI agents, CEO Logan Kelly emphasizes that governance should be legible to finance, legal, and compliance teams, not just developers. As he explains, agent governance is less about exotic AI risks than about visibility and control over things companies already care about, such as cost, data access, and who's allowed to do what. Kelly makes the case that the worst outcome isn't an agent misbehaving but companies losing trust in agents altogether and missing their value—arguing that every major technology, from cloud computing onward, arrived with new risks that good governance ultimately made manageable. Looking ahead, he bets that flexible, general-purpose governance will win out over locked-in "walled garden" platforms, as the pace of change in AI keeps accelerating..
Logan Kelly is the Co-Founder and CEO of Waxell, an AI governance and agent observability company that provides a control plane for operating autonomous AI agents in production. The company entered public beta in early 2026.

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