Claude

How a Meta PM ships products without ever writing code | Zevi Arnovitz

How a Meta PM ships products without ever writing code | Zevi Arnovitz

Zevi Arnovitz, a non-technical Product Manager at Meta, shares his complete workflow for building and shipping sophisticated applications using AI tools like Cursor. He details a structured, multi-step process that leverages different AI models for specific tasks, including a novel "peer review" technique where models critique each other's code.

CES 2026 AI highlights: NVIDIA Rubin & wild gadgets

CES 2026 AI highlights: NVIDIA Rubin & wild gadgets

This episode explores the strategic implications of the Disney-OpenAI licensing deal, critiques Time Magazine's "Architects of AI" focus on business over research, analyzes NVIDIA's full-stack ambitions with the Neotron 3 model release, and delves into Anthropic's unique approach to AI safety with the "Claude Soul Document".

CES 2026 AI highlights: NVIDIA Rubin & wild gadgets

CES 2026 AI highlights: NVIDIA Rubin & wild gadgets

The panel discusses the implications of the Disney-OpenAI licensing deal, arguing it represents a strategic platform play by Disney to control fan-generated content. They also analyze Time Magazine's 'Architects of AI', the business strategy behind Nvidia's Neotron 3 launch, and the unique fine-tuning approach revealed in Anthropic's Claude 'soul document'.

AI Code Generation: Wins, Fails and the Future

AI Code Generation: Wins, Fails and the Future

A panel of experts discusses the future of AI in software engineering, focusing on the "barbell effect" where AI excels at hyper-complex tasks but fails at simple ones. The conversation explores whether performance is driven by the model or the agent orchestration, the evolving role of the engineer as an architect, and the significant challenges open-source tools face against vertically integrated proprietary systems, particularly the high cost of inference.

Continual System Prompt Learning for Code Agents – Aparna Dhinakaran, Arize

Continual System Prompt Learning for Code Agents – Aparna Dhinakaran, Arize

The talk by Aparna Dhinakaran introduces "system prompt learning" as an efficient alternative to traditional Reinforcement Learning for improving large language model-based coding agents. By leveraging LLM-as-a-judge evaluations to generate English feedback and explanations for code failures, agents can automatically refine their system prompts and rules. This method, demonstrated on Claude and Klein, significantly boosts performance on benchmarks like SWEBench with minimal data, highlighting the critical role of high-quality evaluation prompts.

Disney's AI bet: USD 1B OpenAI content deal explained

Disney's AI bet: USD 1B OpenAI content deal explained

Experts Tim Hwang, Marina Danilevsky, Martin Keen, and Kush Varshney discuss Disney's partnership with OpenAI, Time Magazine's 'Architects of AI' Person of the Year, NVIDIA's Nemotron 3 model release, and the implications of Anthropic's leaked 'Soul Document' for model alignment and the future of prompting.