Oct 23, 2026

Don't Trust Your AI Agents. Test Them Like a Scientist — Stephanie Jarmak, Omni Analytics

Stephanie Jarmak, who moved from astronomy into building coding benchmarks and agent evals, argues that most agent evaluations are easy to misread. She covers how harness choice can swamp model differences, why public benchmarks serve shortlisting rather than decisions, how to design experiment-style evals with realistic tasks, repeated runs, and full traces, and how to set quality gates, manage human review load, verify agent records, and treat production as the final test.

Oct 22, 2026

Why AI Startups Will Disappear Without Compute Markets — Evan Conrad, San Francisco Compute

Evan Conrad explains how San Francisco Compute went from an AI lab forced to sublease its own GPU cluster to an operator of supercomputers and a market for compute. He lays out the chain of risks facing new labs and inference companies, from sold-out capacity and oversized deposits to late, broken clusters and unpredictable demand, and argues that these form one credit-driven risk problem that a working compute market must solve.

Oct 22, 2026

Better AI Models Won't Fix Your Engineering Team — Nicholas Arcolano, Jellyfish

Nicholas Arcolano of Jellyfish uses data from about 50,000 engineers across 447 companies to test what really drives AI coding output. A natural experiment forcing users onto Grok barely moved merged PRs. The analysis breaks throughput into tool, skill use, token consumption, company and team, and individual engineer, finding the individual and organization matter far more than the model.

Oct 22, 2026

The Frontier Ideas a16z Wants to Fund Now | Marc Andreessen, Ben Horowitz & Chris Dixon

Chris Dixon, Marc Andreessen, Ben Horowitz, and Erik Torenberg discuss the expansion of a16z crypto into a16z Frontier, a mandate for founders building at the edges of technology. They explore why AI could pull decades of progress forward across hardware, robotics, entertainment, and science, the coming internet of AI agents, why open source matters for a decentralized AI future, and what the breakdown of the internet's traffic economy means for creators and businesses.

Oct 22, 2026

Why AI Compute Comes in Rectangles — Erik Bernhardsson, Modal

Erik Bernhardsson, CEO of Modal, traces his path from building Spotify's recommendation system to founding a serverless GPU cloud, and explains how Modal aggregates demand, secures GPU capacity, weighs renting against owning, and sees agent sandboxes becoming a major product line.

Oct 22, 2026

What will computer chips look like in 2045?

Intel's leadership walks through how advanced process nodes are brought to volume, from yield learning and the lessons of 10nm to the shift from planar transistors to gate-all-around, High-NA EUV, backside power, and CFET. The discussion widens to the chip-to-chip bottleneck that hybrid bonding targets, the supply limits on EUV tooling as AI compute demand grows, and the economics that make foundry scale decisive.