Paperclip: Run a Small AI Agent Team (Claude Code + Codex) Without the Chaos
Paperclip organizes AI agents around tasks, review handoffs and budgets, but useful goals, runtime permissions and human verification still matter.
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Thomas Wolf on Open Models, NVIDIA and AI Alignment
Thomas Wolf discusses Hugging Face's relationship with NVIDIA, enterprise adoption of open-weight models and the need for transparent alignment research.
How AI Is Changing Game Modding and Reverse Engineering
AI Search surveys AI-assisted game modding, contrasting bridge layers, engine rewrites and transfers of individual game mechanics.
Six Codex Workflows for Context, Agents and Automation
Charlie Guo and Gabriel Chua demonstrate six Codex workflows, from supplying context and building applications to agent collaboration and recurring work.
Videos in our catalogue by publication date
How AI Agents Handle Checkout and Payments
Sam Parsons compares three ways merchants can accept payments from AI agents, explaining tokenization, checkout integration and user-experience trade-offs.
Building an AI Observability and Evaluation Workflow
Doug Guthrie demonstrates how production traces, evaluators and topic clustering can feed a tested improvement cycle for AI agents.
Why AI Agents Should Not Hold Their Own Credentials
Jim Clark argues for task-specific agent capabilities, keeping credentials outside sandboxes and using MCP gateways to control access.
How Inference Engines Schedule, Cache and Serve AI Models
Charles Frye explains how inference engines schedule model execution, manage cached state and balance latency, throughput and correctness.
How to Choose a Personal AI Agent
Nathaniel Whittemore presents a framework for choosing a personal AI agent based on work or personal needs, model control, ease of use, data handling and existing integrations.
Building Reliable Verifiers for Browser Agents
Browserbase and Microsoft researchers explain how task-specific rubrics and selected visual evidence can make web-agent verifiers more reliable than judges that trust an agent's claimed success.
Wes Roth sees promising early signs in Gemini 4 Argon while arguing that OpenAI's DevDay announcements focus on persistent assistants and broader workplace adoption rather than a single breakthrough.
The Biggest AI Announcements from OpenAI Dev Day
Nathaniel Whittemore argues that OpenAI DevDay reinforces three shifts: cheaper useful intelligence, persistent agents and shared workspaces for people and AI.
Grok, Gemini and AI in US Government Services
Jack Roberts and Nick Saraev examine how AI could simplify access to government services while raising questions about provider dependence and accountability.
AI Interaction Is Replacing Pure Intelligence - Ashley Kramer
Theo Jaffee interviews Ashley Kramer about turning voice-model capabilities into useful, evaluated enterprise agents.
Opus 5.5 vs The Rest: Is this the new industry standard?
Nate B Jones argues that Opus 5.5's value lies in completing and revising whole tasks efficiently, which users should test against their own work rather than token prices alone.
The State of AI in Software Development: Data from 400+ Orgs - Justin Reock, DX
Justin Reock argues that AI coding adoption produces uneven quality and modest delivery gains unless organizations measure outcomes and address bottlenecks beyond code generation.
OpenAI Just Gave ChatGPT a MASSIVE Upgrade…
AI Copium reviews OpenAI's DevDay announcements as a shift toward persistent agents and a shared software platform, while questioning pricing and real-world reliability.
AI Must Now Be Called SI - From AI to SI: What Does It All Mean?
Brent A. Anders examines how a reported shift from AI to SI terminology could influence perceptions, investment and academic communication without changing the technology itself.
The Chief AI Officer: Scientist, Architect, Coach - Rania Khalaf, WSO2
Rania Khalaf frames the chief AI officer role as a changing balance of scientist, architect and coach that should fit the company, its maturity and the leader's strengths.
The Death of the Code Review: What the Data Actually Says - Laurie Voss, Arize AI
Laurie Voss argues that AI code review shifts human judgment into review harnesses, mergeability standards and production monitoring rather than eliminating it.