AI agent harnesses

A developer has released Television, an open source graphical interface for managing AI agent harnesses. The project, available at television.run, aims to give users a visual front end for running and overseeing coding or task agents. Early reactions on Hacker News are modest but curious, with commenters interested in how a GUI can simplify working with terminal-based agent tooling.

A GitHub project by michael-denyer, pstack-claude, adapts Poteto's pstack — rigorous agent workflows built on Cursor primitives — for other AI coding harnesses, including Claude Code, Codex, Copilot, Pi, OpenCode, Gemini and Prime Agent. It is gaining traction among developers who want structured, disciplined agent workflows outside Cursor, reflecting growing interest in porting agent tooling across platforms.

The United Nations University has introduced KITA AI, described as an agentic artificial intelligence tool aimed at building inclusive and intelligent societies. The announcement positions the tool as part of UNU's work on harnessing AI for social good, with a focus on accessibility and broad public benefit rather than purely commercial applications.

Soket AI has released Loop, an open-source harness designed to run AI agents over long periods. The tool is aimed at developers building autonomous agents that need to operate reliably across extended, multi-step tasks, addressing a common weakness in current agent frameworks. Details on features and adoption remain limited, but the open-source release is being covered in AI industry media.

Soket AI has unveiled LOOP, an open-source agentic harness designed to support AI agents running over long periods. The framework, announced through the company's enterprise AI channels, is aimed at developers building autonomous agents that must sustain tasks, state and reliability beyond short interactive sessions. By open-sourcing the tool, Soket AI is positioning itself within the growing ecosystem of infrastructure for agent development.

Orbi, an AI coding agent, reportedly takes a GitHub issue and returns a reviewed, merged pull request, with one agent writing the fix and another handling review. A follow-up post examining the system's harness asks what its reviewer missed, suggesting developers are scrutinising how reliable the automated pipeline is. The discussion is drawing interest from the open-source and AI engineering communities.

A discussion on spec-driven development (SDD), Harness deployment tooling, AI agents and security in multicloud environments is circulating among software engineering communities. The central question raised: your agent may be able to deploy code, but should it? The topic touches on AI-assisted programming, cloud architecture and the risks of granting autonomous agents production access.