Oct 19, 2026

Smarter Models Killed the Harness. Here's What's Left — Jediah Katz, SpaceXAI

Jedidiah Katz, longtime agent-harness engineer at Cursor and now at SpaceX, argues that fancy harnesses no longer add coding intelligence because models absorb those skills through a data flywheel. He contends the harness matters more than ever: it unlocks new frontiers like Grokbot and owns infrastructure, trust and security, and efficiency. He closes with predictions, including that 90% of agent work will run off the laptop within six months.

Oct 08, 2026

Beyond the Benchmark: How Parallel Web Systems Builds Reliable Web Agents

Parallel Web Systems engineer explains how the company moved beyond academic web-research benchmarks to a fully automated evaluation flywheel that samples production questions, generates reference answers with an oracle agent, judges with tool-equipped agents, and masks components to diagnose failures, along with the open challenges of evaluating subjective and infrastructure-dependent quality.

Oct 08, 2026

Rapidly Deploying Useful General-Purpose Robots at Walden Robotics

A talk from Walden on deployment-first physical AI: getting general-purpose robots into real manufacturing production, using remote assistance as a human-in-the-loop safety and learning mechanism, and building a data flywheel in which operational data drives continuous improvement of large behavior models.

Sep 10, 2026

AI Is Missing This Data

David Fattal, CTO of Leia Inc., explains why stereo data is crucial for developing robust AI world models that can accurately understand 3D geometry and interact with the physical world. He contrasts it with monocular data, highlighting stereo's superior ability to ground AI in reality. Fattal introduces Leia's technology for glasses-free 3D displays on standard devices, predicting a "device-data flywheel" where accessible 3D hardware drives user-generated stereo content, providing essential data for AI advancement, a crucial differentiator for future AI companies.

Aug 13, 2026

When to Build Your Own Agent Harness | Harrison Chase, LangChain

Harrison Chase, co-founder of LangChain, delves into the critical role of the 'harness' in LLM agents, explaining how it orchestrates models and context. He covers customizing harnesses with middleware and sub-agents, the trade-offs between off-the-shelf and custom solutions for in- and out-of-distribution tasks, and the importance of evaluations and observability for continuous agent improvement. The discussion culminates in the 'data flywheel' concept and the `LangSmith Engine` for automating agent intelligence through iterative refinement.

Jul 14, 2026

Why the Best AI Stories Aren't About AI (with Steve Mock)

Steve Mock, investor and entrepreneur, discusses aisavedme.org, a platform born from his father's question, "How does one use AI?". The site gathers real-world stories of AI's positive impact, revealing surprising human outcomes in healthcare, education, and personal fulfillment, often less about technology and more about connection. He also shares his unique no-code journey in building the site and his venture capital insights into the "data flywheel" and "vertical AI" as key to successful investments.