Oct 20, 2026

Should You Trust ChatGPT With Your Health?

Karan Singhal, who leads health AI research at OpenAI, joins a16z's Jay Rughani to discuss how OpenAI is building trustworthy health intelligence into general-purpose frontier models. The conversation covers expert-driven evaluation and disagreement handling, the role of AI as a complement to doctors, integrations with Epic and clinician copilots, personal agents navigating fragmented healthcare, the distinction between medical information and medical care, and how falling costs of medical intelligence could compress the lag in clinical consensus and accelerate treatment discovery.

Oct 20, 2026

Shipping AI Into 5 Major Banks Without a 12-Month Compliance Wait — Al Chen, Cisco

Al Chen explains what it takes to get AI observability software through the security and compliance reviews of major banks. He covers build pipelines, agent-driven CVE remediation with verifiable exploit tests, ClickHouse backup and restore verification, PII and MNPI leakage through LLM judges, and the tradeoffs of zero leakage and data sovereignty, with an emphasis on showing evidence to shorten time to production.

Oct 20, 2026

Why AI Agents Will Need Their Own Bank Accounts — Lincoln Murr, Coinbase

Lincoln Murr, head of AI product at Coinbase, explains agentic finance, covering agents that pay and agents that grow money. He traces the path from AgentKit, an early experiment giving an AI a wallet, to x402, an open payment standard built on the long-unused HTTP 402 code. He also discusses microtransactions as a replacement for the ad economy, agents executing trades from simple instructions, the trust-building lessons from two years of development, and the vision of agents that can pay for their own upkeep.

Oct 19, 2026

How to Know When an AI Agent Can Work Unsupervised — Evan Kormos, Coinbase

Evan Kormos of Coinbase presents a practical framework for bringing AI agents into policy-driven, regulated workflows. He models processes as DAGs with loops inside each node, argues that a loop is only as trustworthy as its check, and shows how evals and traces create a new confidence mechanism. Agents then move through supervised, sampled, and exception-only stages.

Oct 19, 2026

Aegon: Self-Auditable Key Transparency

This talk presents Aegon, a self-auditable key transparency scheme designed for global-scale encrypted messaging. It builds on Iron Dict's polynomial commitment approach to remove per-epoch global work, shards the dictionary for horizontal scaling, and uses proof caching to bound storage. The result is constant-size audit proofs that a lightweight client can verify itself over an entire history, rather than relying on external auditors.

Oct 19, 2026

Why a $1M Startup Wasn’t Worth Building in the Age of AI

Jean-Denis Greze, Town's CEO and former Plaid CTO, explains why he shut down a nearly $1M-revenue AI tax business for SMBs and pivoted to Town, an AI assistant that works from email and calendar. The conversation with a16z's Alex Rampell covers founder decision-making under time pressure, product-market fit, the consumer-grade enterprise thesis, token allocation as a business model, neutrality versus frontier labs, horizontal versus vertical strategy, uneven AI diffusion, and how agents may reshape commerce and advertising.