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AI News2026-05-03·8 min read·1
OpenAI Workspace Agents Commentary: Why you should design approval boundaries and sharing scopes before models when adding in-house automation
Workspace Agents, which OpenAI released in April 2026, was explained from the perspective of in-house automation operation standards rather than simply a new feature. We summarize why shared agents, Slack deployment, and scheduled execution are permission/approval/audit design issues.
#OpenAI#Workspace Agents#ChatGPT Enterprise#Slack+1
AI How-to2026-05-02·9 min read·1
Google AI Joint Doctor's Commentary: Why supervisory boundaries and separation of responsibilities should be designed before diagnostic performance when introducing medical AI
Google DeepMind's announcement of joint AI intention is closer to a signal that how to design supervisory boundaries, separation of responsibilities, and real-time safety devices is more important in the actual field than news that medical AI has become smarter.
#Google DeepMind#AI co-physician#Medical AI#Telemedicine+1
Development2026-05-02·10 min read·2
Microsoft Foundry Practical Guide: Operational Boundaries to Set When Bringing MCP Server, LangGraph, and Browser Automation to One Platform
Microsoft Foundry's April 2026 documentation update is less of a feature addition and more of a signal to clearer boundaries between agent operations. When looking at MCP connection, LangGraph integration, browser automation, and task adherence at once, we have organized what to design first as a practical standard.
#Microsoft Foundry#MCP#LangGraph#Browser Automation+1
AI News2026-05-01·8 min read·1
Kakao PlayMCP x OpenClaw commentary: Why you should design channel, token, and authority boundaries before the model when creating your own AI assistant
Kakao has started supporting OpenClaw integration in PlayMCP. This change is not just news about integration, but is based on what should be designed first when attaching an MCP agent to an actual work channel.
#PlayMCP#OpenClaw#MCP#cacao+2
AI How-to2026-05-01·9 min read·3
Next.js AGENTS.md practical introduction guide: How to tell an AI coding agent to read version-locked documents first instead of training data
Based on Next.js 16.2's AGENTS.md and MCP support, we have organized an operating pattern that causes coding agents such as Claude Code·Codex to look at the current project document first instead of old training data.
#Next.js#AGENTS.md#Claude Code#Codex+2
AI News2026-04-30·10 min read·1
Microsoft Agent Governance Toolkit Commentary: Why you need a runtime policy engine before prompt guardrails
The Agent Governance Toolkit released by Microsoft in April 2026 clearly demonstrated that AI agent security should be handled through runtime policy, permissions, isolation, and SRE layers rather than prompt rules. This article breaks down in operational terms why this approach is important, which teams should adopt it now, and how to start a real pilot.
#Microsoft Agent Governance Toolkit#AI agent security#Runtime governance#OWASP Agentic Top 10+1
Development2026-04-30·10 min read·2
Hancom OpenDataLoader PDF Commentary: Why PDF accessibility requires tag structure automation before OCR
The OpenDataLoader PDF accessibility automatic tagging that Hancom released in April 2026 makes the PDF accessibility issue look again as a tag structure restoration issue, not a simple OCR. This article summarizes from a development information perspective why this disclosure is important, what makes it different from existing PDF extraction tools, and how working teams should start piloting it.
#OpenDataLoaderPDF#PDF Accessibility#Tagged PDF#PDF/UA+2
AI How-to2026-04-29·10 min read·1
Mistral Workflows Commentary: Why you need to start with durable execution and approval boundaries rather than models to reduce AI agent failure rate
The Workflows released by Mistral are not a new model announcement, but an execution layer that fills in the recovery logic, approval waiting, and traceability issues that are missing when companies move AI from experimentation to operation. This article summarizes the structure of Mistral Workflows, the differences from Temporal·LangGraph, and the actual introduction sequence on a practical basis.
#Mistral Workflows#AI Workflow#Durable Execution#Temporal+1
Development2026-04-29·10 min read·1
GitHub Models + GITHUB_TOKEN Practical Guide: Permission boundaries to fix first when running AI workflows within a repository without PAT
GitHub Models will officially support basic GITHUB_TOKEN authentication for GitHub Actions starting in April 2025, opening the way to bundle model calls, prompt evaluation, and automated reviews within the repository without PAT. This article organizes the order of authority boundaries, comparison of alternatives, and actual workflow design, which are more important than convenience, into practical standards.
#GitHub Models#GITHUB_TOKEN#GitHub Actions#AI workflow+1

OpenAI Workspace Agents Commentary: Why you should design approval boundaries and sharing scopes before models when adding in-house automation

Google AI Joint Doctor's Commentary: Why supervisory boundaries and separation of responsibilities should be designed before diagnostic performance when introducing medical AI

Microsoft Foundry Practical Guide: Operational Boundaries to Set When Bringing MCP Server, LangGraph, and Browser Automation to One Platform

Kakao PlayMCP x OpenClaw commentary: Why you should design channel, token, and authority boundaries before the model when creating your own AI assistant

Next.js AGENTS.md practical introduction guide: How to tell an AI coding agent to read version-locked documents first instead of training data

Microsoft Agent Governance Toolkit Commentary: Why you need a runtime policy engine before prompt guardrails

Hancom OpenDataLoader PDF Commentary: Why PDF accessibility requires tag structure automation before OCR

Mistral Workflows Commentary: Why you need to start with durable execution and approval boundaries rather than models to reduce AI agent failure rate

GitHub Models + GITHUB_TOKEN Practical Guide: Permission boundaries to fix first when running AI workflows within a repository without PAT