AI videos, nothing else.

Claude Skills: Storage and Context Limits

The alexkerss channel demonstrates how skill files, references and context limits can affect Claude workflows.

Parv Mahajan on Measuring AI Research Acceleration

Parv Mahajan discusses uncertain evidence about AI’s contribution to research acceleration.

Claude Code Updates for Background Work and Compaction

AICodeKing reviews recent Claude Code features and their implications for coding workflows.

Pratyusha Duvvuri on the Cost of AI Tokens

Pratyusha Duvvuri explains why AI token costs are difficult to track across providers, teams and finance structures.

Jason Mancuso on Scaling Agent Reinforcement Learning

Jason Mancuso explains how Modal approaches reinforcement learning for agents across distributed GPU infrastructure.

Richard Feldman on Sharing Agent Work and Context

Richard Feldman explores how teams can retain context when collaborating on agent-driven code changes.

Angela McNeal on Controlled Autonomy in Enterprise AI

Angela McNeal explains why enterprise AI workflows need clear decision logic, oversight and records.

Riley Brown Connects Claude Duet to Local Coding Sessions

Riley Brown demonstrates sending requests from Claude Duet to local Claude Code sessions.

Ryan Stevens on Evaluating an AI Bookkeeping Agent

Ryan Stevens explains how Ramp tests a bookkeeping agent using synthetic businesses and end-to-end evaluations.

Natalia Connolly and Kevin Madura on AI Procurement Analysis

Natalia Connolly and Kevin Madura explain how structured data and verification improve AI procurement analysis.

Nate B Jones on Data Center Opposition and AI Demand

Nate B Jones examines possible consequences of data center opposition while demand for AI computing continues to grow.

Brandon Basso on Validating Autonomous Driving AI

Brandon Basso discusses data, simulation and safety validation for autonomous driving systems.

The Debate Over Limits on Superintelligence and AI Self-Improvement

TheAIGRID examines proposed AI restrictions and weighs arguments about closed-loop self-improvement and international coordination.

Nick Saraev and Jack Roberts on Local Video Models and AI Research

Nick Saraev and Jack Roberts discuss local AI video generation, model post-training and speculation about AI research acceleration.

Dan Lee on AI Sales Agents and Persuasion

Dan Lee describes how AI agents can assist sales teams and why he sees persuasion as a difficult problem for models.

Open Models, Data Centers and Weight-Space Research

Pierce Freeman and Richard Diehl Martinez assess an open model, data center politics and research on editing neural-network weights.

Herdr Updates for Running Coding Agents

AICodeKing reviews Herdr updates for managing coding agents across machines and preserving sessions.

How Financial Planners Build Their Own AI Agents - Matt Ragone

Matt Ragone explains how financial planners build and maintain AI agent skills while keeping human review of financial advice.

Joao Wenzel on Building a Company World Model with AI Agents

Joao Wenzel describes an agentic system that maintains and updates a company world model from workplace evidence.

AI Search on New Models and AI Research

AI Search reviews model releases and research across image, video, robotics and agent systems.