Auto-review offers a safer default for deploying coding agents, using a separate agent to approve or deny boundary-crossing actions.
Agentic autofix for code scanning alerts in public preview - GitHub Changelog
Fix code scanning alerts faster with agentic autofix.
Agents Done Right: A Framework Vision for 2026
Agents choke on context, loop on failures, and dump walls of code for review. It's time to rethink the architecture.
MI9: An Integrated Runtime Governance Framework for Agentic AI
Agentic AI systems capable of reasoning, planning, and executing actions present fundamentally distinct governance challenges compared to traditional AI models. Unlike conventional AI, these systems exhibit emergent and unexpected behaviors during runtime, introducing novel agent-related risks that cannot be fully anticipated through pre-deployment governance alone. To address this critical gap, we introduce MI9, the first fully integrated runtime governance framework designed specifically for safety and alignment of agentic AI systems. MI9 introduces real-time controls through six integrated components: agency-risk index, agent-semantic telemetry capture, continuous authorization monitoring, Finite-State-Machine (FSM)-based conformance engines, goal-conditioned drift detection, and graduated containment strategies. Operating transparently across heterogeneous agent architectures, MI9 enables the systematic, safe, and responsible deployment of agentic systems in production environments where conventional governance approaches fall short, providing the foundational infrastructure for safe agentic AI deployment at scale. Detailed analysis through a diverse set of scenarios demonstrates MI9's systematic coverage of governance challenges that existing approaches fail to address, establishing the technical foundation for comprehensive agentic AI oversight.
AI Code Reviews | CodeRabbit | Try for Free.
AI-first pull request reviewer with context-aware feedback, line-by-line code suggestions, and real-time chat.
Agent Skills
AI coding agents take the shortest path to done, which usually means skipping the specs, tests, and reviews that make software reliable at scale. Agent Skill...
Under the hood: Security architecture of GitHub Agentic Workflows
Learn how our threat model and security architecture help teams run agents safely in GitHub Actions.
Agentic AI Governance: Securing Autonomous AI Agents in Enterprise
When AI agents start making decisions, calling tools, and coordinating with other agents without waiting for human approval, the governance playbook most...
Microsoft offers devs a better way to control AI agent behavior | TechCrunch
The specification lets developer, compliance, and security teams define their own policies for agents to follow in portable policy files.
Git AI - Track AI Code all the way to production
Cross-agent observability from prompt to production. Track AI-generated code from Cursor, Claude Code, GitHub Copilot, Gemini, and more through the entire SDLC.
Agent Interaction Guidelines (AIG) – Linear Developers
Foundational principles and practices for designing agent interactions that integrate more naturally into human workflows.
AgentScan - GitHub Automation Detector
An open experiment in detecting automation patterns on GitHub
Better tools made Copilot code review worse. Here's how we actually improved it.
How migrating Copilot code review to shared Unix-style code exploration tools reduced review cost by reshaping agent workflows around pull request evidence.
How to Deploy AI Agents for Safety
AI-assisted Reviewing is Necessary and Should be Open
Peer review is facing a death spiral. AI production tools are speeding it up. AI-assisted reviewing is necessary and should be open.
AI-assisted Reviewing is Necessary and Should be Open
Peer review is facing a death spiral. AI production tools are speeding it up. AI-assisted reviewing is necessary and should be open.
