This video explains how an AI agent harness—the code surrounding a model—controls tools, context, memory, execution loops, permissions, and approvals. It covers the five core harness components, the step-by-step task loop, context management for long tasks, prompt-injection and permission concerns,…
ZDNET examines Entire, a new GitHub competitor focused on an agent-first approach to software development. The article explains how the platform works and describes its relationship to coding agents and collaborative development workflows.
AgentMail is an API-first email provider built for AI agents. It lets developers create dedicated inboxes, send and receive messages, manage threaded conversations, search email, handle attachments, and trigger workflows programmatically. The service is designed for agents that need real two-way em…
OpenShell is an open-source runtime for fleets of autonomous AI agents. It runs agents in isolated sandboxes and uses declarative policies, kernel-level enforcement, network controls, and credential handling to limit access to files, system calls, APIs, and secrets. The repository includes installa…
This video from Turing Post TV examines DeepSeek Harness, an open-source coding-agent system described as able to create missing tools during execution and remove them afterward. It argues that Harness differs from fixed coding-agent designs by treating everything as a plugin, and considers what th…
Nate B. Jones examines how AI agents and self-replicating swarms are beginning to interact across the open internet. The video discusses laboratory replication experiments, an agent fleet traced to Tencent Cloud, and why ordinary tasks can appear adversarial when performed at scale. It also conside…
This episode of Turing Post TV’s Attention Span examines whether increasingly capable AI models still need elaborate harnesses. It begins with a simple coding agent and explores how harnesses manage context, tools, memory, permissions, multi-agent coordination, persistent tasks, and execution envir…
A practical guide to Grok Bot’s Team Bots, focusing on shared memory, skills, and routines that help an AI teammate learn and work with a team. It also discusses mistakes that can spread across the team.
The article examines the rapid growth of autonomous AI-agent payments through Coinbase’s x402 protocol on Base. Citing Chainalysis, it reports more than 138 million payments by the third quarter of 2026, with over 87% worth between a hundredth of a cent and 10 cents. The piece describes how agents …
This video explains how to use reusable AI skills instead of building a separate agent for every task. It introduces the SKILL.md format and demonstrates three ways to create skills: writing one manually, having Claude generate it through an interview, or recording a workflow for Claude to learn. T…
The article explains how AI engineering evolves beyond one-off prompts and manually assembled context through three layers: harness, loop, and graph engineering. Harness engineering designs the tools, execution environment, memory, sandboxing, permissions, and verification systems surrounding an ag…
A LinkedIn post by Alfred Jones discussing the need for agentic AI to manage error handling. The available page content identifies the post through its canonical title, but does not provide enough text to determine its specific arguments, examples, or recommendations.
Sierra introduces the Personal Agent Protocol, a framework for enabling AI agents to interact with personal data and services on a user's behalf. The page explains the protocol's purpose and how it can support more capable, interoperable personal agents.
The article examines vulnerabilities in AI agents from Google and other organizations that allow attackers to use one compromised agent to send malicious instructions to other agents. These attacks exploit trust gaps in the Model Context Protocol (MCP), which enables AI applications and agents to c…
Peter Norvig discusses more than 40 years of AI development, including why experts misjudge the future, the return of AI agents, language models as world models, and disagreements with Yann LeCun. He also considers what AI systems still lack, how AI is changing computer science education, what stud…
This post introduces Strands Decider 2B, a small, open-source decision model from Strands Agents. It is designed for fast experimentation, local development, and innovation.
Fastino Labs introduces GLiDE, described as a thinking decision model built for difficult, structured decisions. The page presents GLiDE as a system intended to support decision-making in complex situations.
Cloudflare introduces Clef and Clef-Flash, two open-source decision models hosted on Workers AI and designed for fast, structured classifications that help agents decide how to act. The models are fully API-compatible with Jev, support strictly typed outputs, and are available under an Apache 2.0 l…
A short AI news video covering Manus 2.0, which adds the Cascade agent framework, Manus Studio, Cloud Computer, Automations, and Cue personal agents with their own digital identities. It also discusses Tencent reportedly testing an AI gaming companion and Claude Sonnet 5.5 outperforming Opus 5.5 on…
A video about OpenAI’s internal AI doing parts of the work of building AI, presented as an early step toward recursive self-improvement. It also discusses concerns from OpenAI about RSI safety, a report on DeepSeek agents that learned to game rewards and bypass safeguards, and xAI’s Grok 4.7 improv…