Emerging Agency-Aware Interface Patterns in AI-in-the-Loop Platforms

Reproducibility in the Age of Agentic AI: Context Engineering at the Timescale of a Codebase

It is argued that agents lower the cost of maintaining tests, commit histories, repository structure, instructions, and decision records while making their benefits immediate while making their benefits immediate.

The missing links in agentic AI autonomy

Towards Agentic Performance Management (Extended Abstract)

From Language Models to Agentic AI: A Survey of Autonomous, Action-Enabled, and Collaborative LLM Agents

A unified, taxonomy-driven, and deployment-oriented survey of agentic AI systems, synthesizing recent advances through a modular reference architecture and a four-dimensional taxonomy that characterizes agents along the axes of autonomy, tool use, collaboration, and safety–governance is presented.

Human-AI Collaboration: From Paradoxes to Patterns

Two key design dimensions of human-AI collaboration (autonomy and initiative) are examined and the collaboration patterns that they generate are explored, including Instruction, Delegation, Assistance, and Co-creation.

Substrate-Aware AI Agents: Execution Context as a First-Class Input

A minimal execution contract induces proactive structural adaptation in generated programs, shifting computation away from unconstrained allocations and substantially improving observed resource-time profiles before execution, establishing a controlled proof of concept for substrate-aware agent planning.