AI:AM — AI Memory Chips, Agent Rankings and AI-Powered Networking · October 28, 2026

Kepler Computing CEO Debo Olaosebikan explains how ferroelectric memory could increase cache density and improve high-bandwidth memory using standard fab equipment. Arena CEO Anastasios Angelopoulos discusses agent evaluation, alignment failures and model rankings, while Union CEO Samvit Ramadurgam explores AI-assisted brokering, startup hiring and the continuing importance of human relationships.

Chapters

(0:00) Memory, rankings and human connections

(1:27) Claude Duet gets it done, for a price

(3:21) Meet Debo Olaosebikan, Kepler Computing CEO

(4:30) Why AI is rationed and where energy goes

(6:54) Stack the bits instead of shrinking the transistor

(10:02) Finding a material that flips cheaply yet stays stable

(13:29) The winning material is a stack, not one recipe

(16:03) Materials AI is bottlenecked by experiment data

(17:32) Two products: denser cache and efficient HBM

(19:45) Can standard fab tools make Kepler's memory?

(22:12) Could cheaper fabs add tenfold more compute?

(24:25) Three-dimensional silicon comes before leaving silicon

(25:25) Production next year, then a gigawatt ramp

(26:32) Meet Anastasios Angelopoulos from Arena

(27:38) Arena measures work, not multiple-choice answers

(28:43) User satisfaction is only one quality signal

(30:12) Models know when they are being tested

(31:05) Long agent sessions reveal hidden violations

(32:35) Three ways an agent betrays its user

(34:32) Paid evaluations fund Arena's free inference

(35:42) A thank-you message can cost forty dollars

(37:11) Overall rankings can hide language-specific performance

(38:39) Private benchmarks do not prevent repeated-test gaming

(40:32) Coding agents change what evaluators can measure

(42:08) OpenAI leads, but alignment failures persist

(44:18) Production failures must feed agent training

(46:15) Meet Samvit Ramadurgam, Union founder

(47:34) Humans still broker most of the economy

(49:17) Union hires for ideas, not execution

(50:16) A target of two billion tokens per person

(51:43) Cheap models first, heavy models for the hardest cases

(52:36) Why people recoil from AI outreach

(55:27) The long tail is already very long

(57:16) Friendly fees earn more referrals than hard bargaining

(58:50) Humans hold the call, AI holds the memory

(1:00:11) The moat is the network, not the software

(1:02:37) Act two is coordinating humanity itself

(1:04:26) The same tool could organize ethnic hatred

(1:06:44) Humans keep a monopoly on their own perspective

(1:08:14) Cheaper AI startups threaten conventional SaaS

(1:09:20) Can growth absorb the jobs AI replaces?

(1:10:17) Could AI deliver a company in a box?

(1:12:13) Robot kitchens cannot make us eat more

(1:13:22) Can philanthropy make AI status games useful?

Guests

Anastasios Angelopoulos — Cofounder and CEO, Arena (𝕏 | LinkedIn)

Debo Olaosebikan — CEO, Kepler Computing (𝕏 | LinkedIn)

Samvit Ramadurgam — Founder, CEO, Union (𝕏 | LinkedIn)

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