What if your company had a digital brain that never forgot, always knew the answer, and could instantly tap the knowledge of your best engineers, even after they left? Superintelligence can feel like a hand‑wavy pipe‑dream— yet, as Misha Laskin argues, it becomes a tractable engineering problem once you scope it to the enterprise level. Former DeepMind researcher Laskin is betting on an oracle‑like AI that grasps every repo, Jira ticket and hallway aside as deeply as your principal engineer—and he’s building it at Reflection AI.
In this wide‑ranging conversation, Misha explains why coding is the fastest on‑ramp to superintelligence, how “organizational” beats “general” when real work is on the line, and why today’s retrieval‑augmented generation (RAG) feels like “exploring a jungle with a flashlight.” He walks us through Asimov, Reflection’s newly unveiled code‑research agent that fuses long‑context search, team‑wide memory and multi‑agent planning so developers spend less time spelunking for context and more time shipping.
We also rewind his unlikely journey—from physics prodigy in a Manhattan‑Project desert town, to Berkeley’s AI crucible, to leading RLHF for Google Gemini—before he left big‑lab comfort to chase a sharper vision of enterprise super‑intelligence. Along the way: the four breakthroughs that unlocked modern AI, why capital efficiency still matters in the GPU arms‑race, and how small teams can lure top talent away from nine‑figure offers.
If you’re curious about the next phase of AI agents, the future of developer tooling, or the gritty realities of scaling a frontier‑level startup—this episode is your blueprint.
Reflection AI
Website - https://reflection.ai
LinkedIn - https://www.linkedin.com/company/reflectionai
Misha Laskin
LinkedIn - https://www.linkedin.com/in/mishalaskin
X/Twitter - https://x.com/mishalaskin
FIRSTMARK
Website - https://firstmark.com
X/Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
X/Twitter - https://twitter.com/mattturck
(00:00) Intro
(01:42) Reflection AI: Company Origins and Mission
(04:14) Making Superintelligence Concrete
(06:04) Superintelligence vs. AGI: Why the Goalposts Moved
(07:55) Organizational Superintelligence as an Oracle
(12:05) Coding as the Shortcut: Hands, Legs & Brain for AI
(16:00) Building the Context Engine
(20:55) Capturing Tribal Knowledge in Organizations
(26:31) Introducing Asimov: A Deep Code Research Agent
(28:44) Team-Wide Memory: Preserving Institutional Knowledge
(33:07) Multi-Agent Design for Deep Code Understanding
(34:48) Data Retrieval and Integration in Asimov
(38:13) Enterprise-Ready: VPC and On-Prem Deployments
(39:41) Reinforcement Learning in Asimov's Development
(41:04) Misha's Journey: From Physics to AI
(42:06) Growing Up in a Science-Driven Desert Town
(53:03) Building General Agents at DeepMind
(56:57) Founding Reflection AI After DeepMind
(58:54) Product-Driven Superintelligence: Why It Matters
(01:02:22) The State of Autonomous Coding Agents
(01:04:26) What's Next for Reflection AI
The MAD Podcast with Matt Turck 