Sep 17, 2026

Databricks’ Ali Ghodsi Never Wanted to Be CEO. Now He’s Among the Best

Ali Ghodsi, CEO of Databricks, shares his unconventional rise to leadership, his unique CEO playbook centered on extreme focus on bottlenecks, and how he built Databricks' commercial engine. He details the strategy against Snowflake, the controversial creation of the Lakehouse category, and his views on conflict-averse leadership. Ghodsi also discusses AI's impact on enterprise and organizational design, offering insights from his personal coding experience and operating system.

Sep 17, 2026

OpenAI Built Its Own Chip in 9 Months

Richard Ho, VP of Hardware at OpenAI, details the development of 'Jalapeño,' OpenAI's first custom AI accelerator. The chip aims to drastically lower inference costs and empower full stack control, achieving a remarkable 9-month tape-out by leveraging AI in chip design. Jalapeño's blank-slate architecture brings memory and compute closer, delivering both high throughput and low latency, outperforming competitors even without speculative decoding, and proving that AI can supercharge expert productivity in complex engineering fields.

Sep 16, 2026

The Watchdogs of AGI — Rune Kvist of AI Underwriting Company

AIUC co-founder Rune Kvist discusses their $40M Series A, emphasizing that AI adoption's biggest constraint is trust, not capability. He details AIUC-1, their quarterly-updated standard for agent security and reliability, and their expansion into model certification to bridge the trust gap between frontier labs and governments. Kvist highlights the critical role of standards and insurance (partnering with Lloyds of London) in quantifying and mitigating AI risks, from agent liability to national security concerns, and preparing for future challenges in robotics and multi-agent systems.

Sep 16, 2026

Stop Chunking Like It's 2022 — Yuval Belfer, AI21 Labs

Yuval Belfer addresses the fundamental challenge in Retrieval Augmented Generation (RAG): the optimal chunk size is query-dependent, but chunking decisions are fixed during indexing. This "information problem" leads to significant recall loss, as shown by experiments demonstrating a 20-40% gap between fixed chunking and an oracle. His proposed solution, multiscale indexing, involves creating multiple document copies with different chunk sizes, querying all of them, retrieving whole documents, and merging results using Reciprocal Rank Fusion, yielding substantial recall improvements with minimal latency increase.

Sep 16, 2026

Your Agreements Are a Database You Can't Query — Hiral Shah, Docusign & Sean Sodha, NVIDIA

The talk by Hiral Shah (DocuSign) and Sean Sodha (NVIDIA) addresses the critical challenge of extracting valuable, negotiated data from unstructured agreements, highlighting how generic AI models fail at complex tables. They introduce DocuSign's Intelligent Agreement Manager powered by NVIDIA's purpose-built, small-parameter NeMo Parse VLM, designed specifically for efficient and accurate table extraction, demonstrating 20x faster processing, lower cost, and its impact on unlocking billions in trapped enterprise data.

Sep 16, 2026

If we want them to do Knowledge Work, design them as Knowledge Agents — Benjamin Clavié, Mixedbread

Benjamin Clavié argues that the industry has mistakenly generalized from the "easy case" of coding agents to the much harder domain of general knowledge work. He highlights that code offers durable, explicit cues and narrow tasks, while knowledge work involves implicit meaning, contextual understanding, and agents needing to reconstruct intent. Clavié traces human solutions through "tool loops" and "organization loops," demonstrating how optimized tools and hierarchical agentic structures (like searcher agents generating memos) are essential to overcome performance ceilings and significantly bridge the "oracle gap" between AI and human knowledge workers.