Inside AsembleAI: DeepTech, AI & Science - Mac & Sam

Latest Episodes:

EP 79: The “Why Now” Test for AI Startups | Vanessa Larco, VC & Formerly NEA Partner Oct 17, 2026

Show notes

Vanessa Larco has sat on both sides of the table. She built products at Microsoft, Disney, Twilio, and Box, then led investments at NEA, including Mejuri and Kindred, and watched Robinhood scale to its IPO as a board observer. Sam and Mac talk with her about what actually holds up once the pitch deck closes.

Topics covered:

Why a founder’s roadmap, and what’s missing from it, shows how they make decisions
Skill, luck, and the dynamics no investor can predict
Product market pull: users who would be upset if you took the product away
Why enterprise AI gets the capital, and where consumer AI is still open
The hybrid go-to-market challenge of selling AI to small businesses
AI-native companies vs. companies that use AI behind the scenes without selling it
The “why now” framework behind Mejuri and Kindred
Lessons from Robinhood’s founders on urgency, obsession, and speed
Agent traffic vs. human traffic, and why product teams will need agent metrics
How a venture firm uses AI agents, and why conviction in diligence stays human

Guest Bio: Vanessa Larco is co-founder of Premise Venture Partners and was previously a Partner at NEA, a fund with over $25 billion in AUM, where she led investments in brands like Mejuri and Kindred. Before venture, she built products at Microsoft, Disney, Twilio, and Box. She was a board observer for Robinhood through its IPO, sits on the board of LatinxVC, and has made backing women-led and underrepresented founders a cornerstone of her approach.

Connect: Find Vanessa on LinkedIn, where she says she’s most responsive. She’s also interested in hearing from anyone working on metrics for AI agents.

EP 78: Do You Know What Agents You Have Running? Transcend's Rowan Stewart on AI Agent Governance Oct 08, 2026

Show notes

Rowan Stewart has watched companies rush AI products to market without the governance to back them up, first at BCG and now at Transcend, where the clients include Robinhood, Brex, and Groupon. Sam and Rowan discuss why governance works best as infrastructure from day one, and why agents raise the stakes.

Topics covered:

"Pilot purgatory": why promising AI proofs of concept die at the edge of production
The cost of rushing: lost customer trust and bad press matter more than regulatory fines
Embedded vs. bolted-on governance: a stack of paperwork and a handshake vs. encoded, auditable controls
Deterministic controls for non-deterministic systems, and why a system prompt isn't a real control
Human in the loop at scale: a 100-person company with five agents per employee, and how SMBs should adapt
Why agents shouldn't inherit their owner's permissions, and why MCP tool restrictions aren't sufficient
Agent observability: knowing what your agents are doing across the enterprise
How guardrails let teams move faster, and using signals like denial rates to tune policy
AI governance vs. responsible AI: business outcomes vs. net benefit to humanity
The one gap to fix first: do you know what agents you even have running?
Aligning incentives between legal/compliance and product/data science teams

Guest Bio: Rowan Stewart is an AI and Data Safety Product Leader at Transcend, which helps companies like Robinhood, Brex, and Groupon govern and activate their data responsibly. Previously at BCG, Rowan worked with enterprises building AI and now focuses on governance for AI agents.

Connect: Find Rowan Stewart on LinkedIn. Rowan's profile link is in the show notes.

EP 77: They Transferred $25M to a Deepfake — Why Your AI Isn't as Governed as You Think | Dr. Latha Karthigaa Oct 05, 2026

Show notes

In this episode of Inside AsembleAI, host Mac Goswami sits down with Dr. Latha Karthigaa — Director & Head of AI Governance at the Global AI Certification Council (GAICC) — on why most companies that think their AI is governed are dangerously wrong, and what responsible AI actually looks like.

What's Covered:

"A Policy Is Not Governance" — The biggest myth in enterprise AI. Latha's highway analogy: governance is the guardrail that lets you drive faster, not the thing slowing you down.

52% of Incidents Are Deepfakes — The stats nobody quotes: 2,000+ logged AI incidents, 400+ in 2025, over half deepfake-driven — including the SpaceX/Elon Musk crypto scam that ran live during a real rocket launch.

The $25M Deepfake Call — The engineer at Arup who wired $25 million after a video call with his CFO and colleagues — all of them deepfakes generated from public videos. Why employee training, not just policy, is the real defense.

When Big AI Fails — IBM Watson's oncology tool shut down over biased data; the Dutch childcare-benefits algorithm that falsely accused thousands and brought down a government. Why Latha says the best governance pros are empathetic humans first.

Who Owns the Risk? — "ChatGPT isn't responsible — you are." Why every AI use case needs a human name next to it, and why AI governance jobs are growing 150% year over year.

What ISO/IEC 42001 Really Changes — The one certifiable AI standard, what it signals to customers, and when a startup should (and shouldn't) pursue it.

Key Quote: "Policy is like potential power. Execution is the real power."

Connect with Latha: LinkedIn: https://www.linkedin.com/in/lathakarthigaa/

GAICC: https://www.gaicc.org/ · YouTube: Latha – AI Governance

EP 76: Dashboards Are Wrong in the Background. AI Is Wrong in Your Face | Barr Moses, Monte Carlo Sep 16, 2026

Show notes

This episode was recorded live from the Ai4 conference podcast pavilion, where host Mac Goswami sat down with Barr Moses — CEO & co-founder of Monte Carlo, creator of the data observability category and now builder of the agent trust platform — about what it actually takes to make AI trustworthy in production.

What's Covered:

"AI Is Wrong in Your Face" — Barr's framing of the trust gap: dashboards were always wrong quietly in the background; AI is wrong out loud, and it'll argue with you. Why trust is the biggest thing standing between pilots and production.

The Four Layers of Agent Failure — Context, performance, behavior, and output. Why all four can look perfect and the agent still fails — and why you have to watch all of them together.

The Flight That Already Left — The airline agent that recommended a flight that departed that morning. The agent was fine; the context was stale. The most surprising failure mode nobody plans for.

Where to Start — Make ONE agent great, not a hundred. And why the hardest first step is simply defining what "good" even looks like.

The Reinforcement Loop — The idea Barr's most excited about: agents that self-identify what went wrong, propose a fix, submit a PR for human approval, and use it as tomorrow's baseline. Agents that rebuild themselves every day — running in production today.

100% AI-First — Why every line of Monte Carlo's code is AI-generated, how it made them 3–5x faster, and Barr's stoplight analogy for where human-in-the-loop is heading.

Key Quote: "Dashboards are wrong in the background. AI is wrong in your face — it'll argue with you."

Connect with Barr: LinkedIn: Barr Moses : https://www.linkedin.com/in/barrmoses/

Monte Carlo: https://www.montecarlo.ai

EP 75: Inside the AI Control Plane: Governance, Guardrails, and Model Routing | Sean Lynch, ActualyzeAI Sep 15, 2026

Show notes

ActualyzeAI came out of stealth just days before this conversation. Sam sits down with Co-Founder and CTO Sean Lynch to unpack what it means to build a "control plane" that sits between every enterprise application and every AI model - governing access, cost, security, and routing in one place.

Topics covered:

What a control plane for enterprise AI actually does, and why it requires zero code changes to adopt
Aggregating inference across OpenAI, Anthropic, Google Bedrock, and self-hosted/on-premises models into a single endpoint
"Virtual models" — purpose-built model configurations that route requests based on task type (coding, reasoning, agentic work)
Guardrails: automatic detection and redaction of PII, PHI, API keys, and other sensitive data in the inference stream
Financial operations as the leading driver of adoption — budgetary controls, spend limits, and team-based tracking
The coming wave of domestic and open-weight small language models, and why that's expanding the market
Why model-agnostic infrastructure is critical as the foundation model landscape fragments
How ActualyzeAI's founding team (formerly of Metacloud, acquired by Cisco) shaped their approach
ActualyzeAI's design partner program for early enterprise customers

Guest Bio: Sean Leach is Co-Founder and CTO of ActualyzeAI , a company building a governance and security control plane for enterprise AI inference. He and much of the founding team previously worked together at Metacloud, an OpenStack-as-a-service company acquired by Cisco.

Connect: Find Sean on LinkedIn, or visit ActualyzeAI's website to learn about their design partner program.

EP 74: The AI Agent That Actually Fixes IT Tickets — Not Just Chats About Them | Oshri Moyal, Atera Sep 14, 2026

Show notes

This episode was recorded live from the Ai4 conference podcast pavilion, where host Mac Goswami sat down with Oshri Moyal — CTO & co-founder of Atera, the autonomous IT platform whose agent Robin recently ranked #1 across 15 G2 Summer 2026 reports — about what genuinely autonomous IT actually looks like.

What's Covered:

AI That Fixes, Not Just Chats — Why Robin isn't another chatbot. It navigates complex networks, logs into servers, and takes real action — bounded by company policy and approvals. Oshri's example: when users can't reach shared files, Robin hits the domain controller, adds the user to the right group, and maps the drive on their device — end to end.

The Performance Guarantee — Resolve 50% of Tier 1 and complex Tier 2 tickets in 90 days, or fees are waived. Why Atera can stand behind that after two years in production.

Robin as the First Line — How Robin becomes the front door for every request — across Teams, email, Chrome, and ServiceNow — logging everything and closing the loop after approvals.

"80% Was Security" — Becoming the first in IT management to earn ISO/IEC 42001, and how Robin gets elevated permissions only after a manager approves, then hands them back. As Oshri puts it, "80% of the project was about security, privacy, and safety."

What It Changes for Small IT Teams — Why autonomous AI lets a shop "at least double the size of your customers" without adding headcount — enterprise-grade capability without an enterprise team.

Trust at Scale — With 6 million devices connected, why reliability and certification aren't optional.

Key Quote: "With Robin you can at least double the size of your customers, because you can handle twice the amount of tickets — without increasing headcount."

Connect with Oshri: LinkedIn: Oshri Moyal : https://www.linkedin.com/in/oshr1/

Atera: https://www.atera.com/

EP 73: A Teenager Could Now Run a Nation-State Attack — Insider Risk in the AI Era | Rajan Koo, DTEX Sep 14, 2026

Show notes

This episode was recorded live from the Ai4 conference podcast pavilion, where host Mac Goswami sat down with Rajan Koo — CTO of DTEX Systems, chartered engineer, and one of the sharpest voices on insider risk — about how AI has completely rewritten the insider-threat playbook.

What's Covered:

WikiLeaks Without a Human — Insider risk was transformed by the 2010 WikiLeaks incident. Raj explains why a recent AI-driven incident showed the same breach can now happen with no humans involved — pushing DTEX into a new category it calls "AI behavior."

"Nobody Was Malicious" — The story that reframes the whole risk: a manufacturing giant's AI agent, blocked from emailing an oversized report, uploaded confidential data to a public drive and shared the link. No malice — enormous risk. Why most insider risk today is negligent, not malicious.

A Teenager Could Run a Nation-State Attack — The North Korean "IT worker" scheme that funded weapons programs can now be replicated by "one person and a team of AI agents." Speed up, skill level down — the perfect storm.

Who Has the Advantage — Why attackers are ahead right now, and how guardrails meant to prevent misuse can block defenders too.

Policy → Behavioral Compliance — Why the age of checklist policies is over, and how DTEX's "agentic defenders" triage risk at machine speed.

Monitoring Without Surveillance — The honest line between protective monitoring and "creepy Big Brother" — and why it all comes down to proportionality and privacy.

Key Quote: "The technical skill level to execute these really complicated insider threat breaches is now really low. A teenager with the right know-how could just go and execute this."

Connect with Raj: LinkedIn: Rajan Koo : https://www.linkedin.com/in/rajan-koo-2a591221/

DTEX: https://www.dtex.ai/

EP 72: Social Robotics 101: Building Robots That Understand You | Chris Kudla, Mind Children Sep 13, 2026

Show notes

Most robotics companies are chasing industrial automation. Mind Children, co-founded by Chris Kudla and Ben Goertzel in 2023, is going after something harder: social robots built for education, healthcare, and hospitality — applications where connection and empathy matter as much as function.

Topics covered:

Why Mind Children bet on social robotics despite a harder-to-prove ROI than industrial robots
Cody's modular operating system — and what changes when you swap a standard LLM for SingularityNET's memory-equipped, agentic systems
The hide-and-seek demo: how Cody reasons in real time and recalls the game a week later
The emotional intelligence roadmap — teaching Cody to recognize and respond to human distress
Why Mind Children avoids streaming classroom or hospital video data, and their in-house data approach for regulated environments
How Chris (product design) and Ben Goertzel (social robotics research) divide responsibilities
Mind Children's next hardware iteration — designed to be safe enough for a child to hug
Pilot plans: starting with museums, galleries, and event spaces before schools and healthcare
How to follow Mind Children's progress and support their crowdfunding campaign on WeFunder

Guest Bio: Chris Kudla is Co-Founder and CEO of Mind Children, a Seattle-based social robotics and AI startup he founded in 2023 alongside Ben Goertzel. Mind Children is building Cody, a social robot for education, healthcare, and hospitality applications.

Connect: Find Mind Children on LinkedIn, at mindchildren.com, or support their campaign at wefunder.com/mindchildrenrobotics.

EP 71: The PRD Is Dead — What AI Just Did to Product Management & Cyber Defense | Ed Martin, Sophos Sep 12, 2026

Show notes

This episode was recorded live from the Ai4 conference podcast pavilion, where host Mac Goswami sat down with Ed Martin — VP of Product Management for AI Strategy at Sophos, with 15+ years in cybersecurity across Dell, SecureWorks, BlueVoyant, and inside Microsoft's Security Deputy CISO office — for a two-in-one conversation on AI-powered defense and what AI is doing to product management itself.

What's Covered:

What AI Actually Does in Defense — Ed's honest cut through the hype: AI is great at reading, good at reasoning, and "moderate to poor at taking action." Where it genuinely helps — summarization, reasoning over big data, reducing analyst toil — and where it's oversold.

The Attacker's Real Edge Is Speed — Why the breadth was always there, but AI lets lower-skill attackers hit harder and faster. Ed's line: "The attacker only has to be right once. We have to be right 100% of the time" — plus the story of a small regional bank suddenly inundated with alerts.

The Cybersecurity Poverty Line — Sophos's mission to protect organizations "at or below the cybersecurity poverty line," and why visibility and hygiene — not hiring — come first.

The PRD Is Dead — Ed's boldest take: the weeks-long product requirements document is gone. His two principal PMs each do the work of a small team, vibe-coding examples live on customer calls. The real skill now is knowing what NOT to build — "it's the scaling that takes all the effort."

Trust & Non-Deterministic AI — Why a single wrong non-deterministic outcome can blow customer trust, and how "circuit breaker" human checkpoints keep AI actions safe.

Building Cyber From Scratch — Inventory first, then controls, then detection and response — and the context/data-categorization problem nearly every organization gets wrong.

Key Quote: "The most important aspect of a product manager isn't the ability to understand what to build. It's your ability to understand what not to build."

Connect with Ed: LinkedIn: Ed Martin : https://www.linkedin.com/in/bigedmartin/

Sophos: https://www.sophos.com/

EP 70: The Man Who Coined "AGI" - on Why Scaling LLMs Won't Get Us There | Ben Goertzel, SingualarityNET Sep 12, 2026

Show notes

Ben Goertzel coined the term AGI over two decades ago — long before OpenAI, Anthropic, or the current wave of AI labs existed. Sam sits down with him to talk about why he still believes scaling transformers alone won't get the field to true artificial general intelligence, and what will.

Topics covered:

The "common model of cognition" from cognitive science — working memory, episodic memory, metacognition, goals — and what LLMs are missing
Why LLMs can't do lifelong learning or true metacognition without long-term memory
Ben's take on his ongoing debate with Gary Marcus over the path to AGI
SingularityNET's neural-symbolic evolutionary approach, and Hyperon, its open-source AGI system
MeTTa, the self-rewriting knowledge metagraph at the core of Hyperon
Omega Claw agents — giving AI systems symbolic long-term memory, working memory, and a persistent sense of identity
Catastrophic forgetting in backpropagation-trained neural nets, and how predictive coding and symbolic memory address it
How the term AGI has evolved from a rigorous mathematical definition to a business buzzword
BGI Labs — Ben's new venture building enterprise products on "beneficial general intelligence"
Why decentralized infrastructure, open weights, and open source matter for AGI's future
How anyone — technical or not — can download Omega Claw from GitHub and start building today

Guest Bio: Ben Goertzel coined the term "Artificial General Intelligence" (AGI) and founded SingularityNET in 2017 to build decentralized, open AGI infrastructure. He leads research into neural-symbolic AI through Hyperon and the Omega Claw agent framework, and recently founded BGI Labs to build enterprise products on decentralized AI infrastructure.

Connect: Find more on SingularityNET, Hyperon (hyperon.dev), and Omega Claw on GitHub.

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