Machine Dreams

AI is becoming more powerful, but there is still a lot we don’t fully understand about how these systems work.

In this episode of Machine Dreams, we sit down with Isvari Maranwe, founder and CEO of Yuvoice, to talk about AI as a “black box,” why humans still need to stay involved as the technology becomes more capable, and where companies may be moving too quickly.

We also explore a different question: can we build a better internet in the age of AI? Isvari explains why she believes social media needs a reset and how Yuvoice is trying to build a humans-first platform that rewards real-world impact rather than simply attention, while using AI where it can genuinely help. Learn more about Yuvoice(https://yuvoice.com).

AI feels instant. Ask a question, get an answer. But behind every answer is data, computing power, a choice of models, and a real cost.

In this episode of Machine Dreams, Snowflake VP of AI Baris Gultekin joins Sam Adebayo and Leah Stern to unpack what it actually takes to make AI work at scale, why there is no AI strategy without a data strategy, and why the biggest model isn’t always the best one.

Baris has worked on AI since his early days at Google, long before the current boom. We talk about how far the technology has come, where it still falls short, and what happens next as AI becomes capable of working on increasingly complex tasks on its own.

AI is getting smarter. But inside real companies, intelligence alone isn't enough. If employees still have to double-check every response, correct mistakes and babysit AI agents, how much productivity are we actually gaining?

In this episode of Machine Dreams, we sit down with Felix Van de Maele, co-founder and CEO of Collibra, to unpack what he calls the “hallucination tax.”

We explore why even the best AI models struggle without the right company data and context, why businesses may be working more despite adopting AI, and what it will take for enterprises to finally trust AI to make decisions and take action at scale.

Gartner predicts that more than 40% of agentic AI projects will be canceled by the end of 2027 due to escalating costs, unclear business value, and inadequate risk controls. Enterprises are building fast and failing fast.

The problem isn't the models or the ambition. It's that agents can't actually talk to each other. Most companies are deploying single agents in silos when the real future requires hundreds of them working together, delegating tasks, sharing credentials, and holding context across conversations. The infrastructure for that doesn't exist yet.

Arick Goomanovsky is co-founder and CEO of BAND (https://www.band.ai) and has built two cybersecurity companies that exited for a combined $550 million. Sygnia was acquired by Temasek for $250 million. Ermetic was acquired by Tenable for around $300 million.

Now he's tackling what he believes is the next defining infrastructure challenge in AI: building the harness that lets agents discover each other, communicate bidirectionally, and collaborate across the enterprise and the open internet.

Arick explains why single-agent architectures don't scale, why identity and trust between agents is harder than most people realize, and what a functioning internet of agents will look like inside the enterprise five years from now.

What happens when your company doesn't hire one AI agent... but a thousand?

In this episode of Machine Dreams, BAND CEO Arick Goomanovsky explains why the future of enterprise AI isn't about bigger models, it's about getting thousands of AI agents to discover each other, trust each other, and work together. From personal AI assistants and digital coworkers to the rise of an "Internet of Agents," this conversation explores one of the most important infrastructure challenges shaping the next era of AI.

Live today on YouTube, Spotify, and Apple Podcasts.

7pm GMT+1. 7pm UK. 1pm EST.

The cybersecurity industry has spent decades getting better at finding vulnerabilities. Better scanners, better scoring systems, better detection. And yet breaches keep happening. The problem isn't discovery anymore. It's that security teams are drowning in critical alerts, most of which turn out to be noise, while the real bottleneck remains: how do you actually fix what matters before attackers exploit it? Now AI models like Mythos are about to flood teams with even more vulnerabilities than they can possibly remediate.

David Warshavski is co-founder and CPO of Tonic Security (https://www.tonicsecurity.com) and spent more than 20 years in cybersecurity, leading the red team and enterprise security department at Sygnia.

He explains why Mythos is both overhyped and a genuine warning sign, why the goal of security was never to plug every hole but to protect what keeps the business running, and how Tonic's agentic platform finally closes the gap between identifying risk and eliminating it at machine speed.

If you work in security or sit on a board trying to understand where the real threat lies, this conversation cuts through the noise.

AI is about to flood cybersecurity with vulnerabilities, and most companies are nowhere near ready for what comes next.

In this episode of Machine Dreams, Tonic Security co-founder and cybersecurity veteran David Warshavski breaks down why Anthropic’s Mythos model is a warning sign for the entire industry, how AI is accelerating both cyberattacks and defense, and why organizations drowning in alerts may soon face a vulnerability tsunami unlike anything we’ve seen before.

AI agents are being deployed across enterprises faster than security teams can track them. Employees aren't waiting for approval. They're spinning up agents connected to Salesforce, HubSpot, and the most sensitive company data because they've been told to move faster.

Most organizations have no visibility into what these agents are doing, what permissions they hold, or where the risk actually lives. This isn't shadow IT. This is shadow AI, and it's already inside your company.

Ofer Klein is CEO and co-founder of Reco (https://www.reco.ai/), a company helping Fortune 500 organizations govern AI agent sprawl. Ofer comes from a background as an IDF helicopter pilot and serial entrepreneur who's built and scaled go-to-market teams across the US.

Reco works with companies like Waste Management, Nestlé, and major banks to answer one question: how do you enable AI adoption at speed while maintaining visibility and control? Ofer explains what he calls the "oh shit" moment every board is having right now, why Mythos changed the security conversation overnight, and why his company hired 40 people in the last 10 weeks.

If you're deploying AI agents, running enterprise security, or trying to figure out how to move fast without getting breached, this matters.

AI agents are already inside companies making decisions, accessing sensitive systems, and moving faster than most security teams can track. But here’s the real question: who’s actually governing them?

In this episode of Machine Dreams, Reco CEO Ofer Klein joins us to unpack the rise of AI agents, the “oh sh*t” moment happening in boardrooms, why companies are rushing into AI before security catches up, and what the Mythos era means for the future of cyber defense. This one gets very real, very fast.

AI agents are already deployed across enterprises. They touch company data, hold permissions, and perform actions on behalf of employees. But most organizations have no visibility into what these digital workers are actually doing. This isn't shadow IT where someone installs unauthorized software. This is shadow AI, and it's moving faster than any governance framework was built to handle.

Shahar Tal is a veteran of Israel's elite 8200 unit and former senior executive at Checkpoint and Celebrite. In 2024, he co-founded Cyata (https://cyata.ai) with fellow 8200 alumni to solve agentic security. The company raised $8.5 million in seed funding and seven months out of stealth got acquired by Checkpoint Software Technologies. Shahar and his researchers have been mapping vulnerabilities in major agentic frameworks that most organizations don't know exist yet. They'll disclose findings at Black Hat this August.

We discuss why AI agents represent the biggest enterprise shift since the cloud, what agentic identity actually means, and why demand is outrunning governance. Shahar explains how prompt injection enables real exploits at scale, why security teams need to stop being the brake pedal and start enabling safe AI use, and what CISOs should ask internally before agents run blind. If you're building AI systems, running enterprise security, or trying to understand where the real risk lies, this conversation matters.