Most of this conversation is about something Spencer built on paternity leave. Chitta, a Sanskrit and Pali term for the storehouse of memory and impressions that lead to action, is an AI memory system that distills dense sources into structured, queryable knowledge. The numbers are the interesting part: on Cockroach's Zendesk tickets, it produces a full root cause analysis 41% of the time from the customer's initial filing alone, in under a minute, for roughly $1.50. Opus without it lands around 10%. Humans almost never get there on the first pass.

The lesson Spencer draws is that generic distillation doesn't work. The same source (a Zendesk ticket, a Git log, a source repository) has to be distilled with a purpose in mind. Reading code to add a feature and reading code to find a vulnerability produce different structures, because a human reading for those two purposes would pay attention to different things.

We also get into MICA, the internal tool a departing engineer left behind that has produced thousands of applications in a few months; why Spencer thinks the cheapest database at scale wins the market; the dirty secret that operational databases run at 5–15% utilization; and what Cockroach is building to fix it.

And because this is the base-layer, we spend time on the part nobody demos: governance. Pools of distilled intelligence inherit the permissions of their sources, or they should. Spencer's answer, that "governance is the ultimate blocker to AI adoption", is the reason this show exists.

She joins Jake Moshenko to talk about what AI adoption actually looks like on the ground. Not the discourse, the practice.

The conversation starts somewhere unexpected: a hair-care app she built for herself after her third kid, used for months, then threw away. She calls it selfieware: software with no users, no tracking, and no authorization, built because the cost of building finally dropped below the cost of caring. The best thing she ever built with AI was a thing she was able to discard.

From there: why multi-model is inevitable (a chef doesn't use one knife for every task), what happens when benchmarks become training data, and why tying your tooling to a single lab's models is a bet you don't need to make.

Then the part that lands closest to home for anyone thinking about authorization. Emilie runs two agents (Chad, personal; Snivel, for work) and holds a hard line between them: an agent gets internal data or external comms, never both. She arrives at agent identity, audit trails, and code provenance on her own terms, from the practitioner's side rather than the vendor's.

Also discussed: whether AI spend is even the right metric (she proposes spend divided by PRs merged), the financial institution budgeting $13 per engineer per month, and why the biggest gap right now isn't capability. It's the long tail of people who haven't started yet.

His argument is that the internet needs an upgrade, for three reasons. Policy is fragmenting: the splinternet is real, and increasingly you need to control who you exchange traffic with and where. Data has stopped being centralized; we spent 25 years with smart servers and dumb clients, and now the clients are smart and the data is everywhere. And infrastructure has fragmented across dozens of providers, which makes your perimeter enormous.

His answer is a private backbone for every application, built on SRv6, segment routing over IPv6, which lets you put policy into the header of the packet itself rather than letting the public internet decide where your traffic goes.

The part that should make you uncomfortable is his answer to what AI is about to invalidate: the assumption that the computer your software runs on is safe. "I think you just can't trust pretty much any of your infrastructure." Design from there.

We also get into a soccer club in Denmark he helped crowdfund out of bankruptcy and the open source media system he built for it; why the data center industry's instinct to hide behind a fence is a mistake; the security asymmetry where defenders are refused the AI tools attackers use freely; what happened to Intel and why Jensen Huang is determined not to repeat it; and what the Luddites were really fighting for, which was not the machines.

Learn more about what Zac’s building at Datum: https://www.datum.net/

Want to contribute? Join Datum on Github: https://github.com/datum-cloud

Check out AB Copenhagen on Github: https://github.com/AB-Copenhagen