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Inside AsembleAI: DeepTech, AI & Science: Daily Summaries Delivered
by Mac & Sam
AsembleAI brings you thought-provoking conversations at the nexus of artificial intelligence, innovation, and leadership. In each episode, hosts Mac and Sam, veterans in data and tech world, sit down with AI researchers, fast‑scaling founders, Fortune 500 executives, and pioneering technologists to reveal how AI is reshaping business strategy, sparking breakthrough product development, and guiding executive decisions. Tune in for actionable insights, compelling case studies, and forward‑looking perspectives on the promises and pitfalls of AI‑driven innovation.
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- 1 weeks ago42 min
EP 79: The “Why Now” Test for AI Startups | Vanessa Larco, VC & Formerly NEA Partner
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 decisionsSkill, luck, and the dynamics no investor can predictProduct market pull: users who would be upset if you took the product awayWhy enterprise AI gets the capital, and where consumer AI is still openThe hybrid go-to-market challenge of selling AI to small businessesAI-native companies vs. companies that use AI behind the scenes without selling itThe “why now” framework behind Mejuri and KindredLessons from Robinhood’s founders on urgency, obsession, and speedAgent traffic vs. human traffic, and why product teams will need agent metricsHow a venture firm uses AI agents, and why conviction in diligence stays humanGuest 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.
- 3 weeks ago31 min
EP 78: Do You Know What Agents You Have Running? Transcend's Rowan Stewart on AI Agent Governance
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 productionThe cost of rushing: lost customer trust and bad press matter more than regulatory finesEmbedded vs. bolted-on governance: a stack of paperwork and a handshake vs. encoded, auditable controlsDeterministic controls for non-deterministic systems, and why a system prompt isn't a real controlHuman in the loop at scale: a 100-person company with five agents per employee, and how SMBs should adaptWhy agents shouldn't inherit their owner's permissions, and why MCP tool restrictions aren't sufficientAgent observability: knowing what your agents are doing across the enterpriseHow guardrails let teams move faster, and using signals like denial rates to tune policyAI governance vs. responsible AI: business outcomes vs. net benefit to humanityThe one gap to fix first: do you know what agents you even have running?Aligning incentives between legal/compliance and product/data science teamsGuest 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.
- 3 weeks ago33 min
They Transferred $25M to a Deepfake — Why Your AI Isn't as Governed as You Think | Dr. Latha Karthigaa
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 GovernanceFollow and subscribe to AsembleAI: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack
- Sep 16, 202627 min
EP 76: Dashboards Are Wrong in the Background. AI Is Wrong in Your Face | Barr Moses, Monte Carlo
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.aiFollow and subscribe to AsembleAI: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack
- Sep 15, 202621 min
EP 75: Inside the AI Control Plane: Governance, Guardrails, and Model Routing | Sean Lynch, ActualyzeAI
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 adoptAggregating 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 streamFinancial operations as the leading driver of adoption — budgetary controls, spend limits, and team-based trackingThe coming wave of domestic and open-weight small language models, and why that's expanding the marketWhy model-agnostic infrastructure is critical as the foundation model landscape fragmentsHow ActualyzeAI's founding team (formerly of Metacloud, acquired by Cisco) shaped their approachActualyzeAI's design partner program for early enterprise customersGuest 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.
- Sep 14, 202613 min
EP 74: The AI Agent That Actually Fixes IT Tickets — Not Just Chats About Them | Oshri Moyal, Atera
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/Follow and subscribe to AsembleAI: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack
- Sep 14, 202625 min
EP 73: A Teenager Could Now Run a Nation-State Attack — Insider Risk in the AI Era | Rajan Koo, DTEX
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/Follow and subscribe to AsembleAI: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack
- Sep 13, 202616 min
EP 72: Social Robotics 101: Building Robots That Understand You | Chris Kudla, Mind Children
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 robotsCody's modular operating system — and what changes when you swap a standard LLM for SingularityNET's memory-equipped, agentic systemsThe hide-and-seek demo: how Cody reasons in real time and recalls the game a week laterThe emotional intelligence roadmap — teaching Cody to recognize and respond to human distressWhy Mind Children avoids streaming classroom or hospital video data, and their in-house data approach for regulated environmentsHow Chris (product design) and Ben Goertzel (social robotics research) divide responsibilitiesMind Children's next hardware iteration — designed to be safe enough for a child to hugPilot plans: starting with museums, galleries, and event spaces before schools and healthcareHow to follow Mind Children's progress and support their crowdfunding campaign on WeFunderGuest 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.
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About Inside AsembleAI: DeepTech, AI & Science
AsembleAI brings you thought-provoking conversations at the nexus of artificial intelligence, innovation, and leadership. In each episode, hosts Mac and Sam, veterans in data and tech world, sit down with AI researchers, fast‑scaling founders, Fortune 500 executives, and pioneering technologists to reveal how AI is reshaping business strategy, sparking breakthrough product development, and guiding executive decisions. Tune in for actionable insights, compelling case studies, and forward‑looking perspectives on the promises and pitfalls of AI‑driven innovation.
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