This story was originally published on HackerNoon at: https://hackernoon.com/no-ai-agent-without-identity-part-2-building-the-layered-identity-model.
AI agent identity must be layered: stable principals for governance, runtime identities for attribution, and audit records for accountability.
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This story was written by: @sebastianmartinez. Learn more about this writer by checking @sebastianmartinez's about page, and for more stories, please visit hackernoon.com.

Part 2 of a 5-part series on agentic AI governance. This article explains why AI agent identity needs a layered model: stable agent principals for governance, temporal runtime or context identities for attribution, roles and policies for access control, and linked execution and audit records for accountability.

This story was originally published on HackerNoon at: https://hackernoon.com/the-ai-doom-loop-why-your-autonomous-coding-agent-is-making-things-worse-and-how-to-fix-it.
Stop your AI coding agents from getting stuck in 'doom loops'. Discover how Agent Rigor enforces software engineering discipline for true AI autonomy.
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This story was written by: @meherbhaskar. Learn more about this writer by checking @meherbhaskar's about page, and for more stories, please visit hackernoon.com.

AI coding assistants like Claude Code often lack engineering discipline, resulting in broken code and endless fix-forward hallucination loops. Agent Rigor is an open-source, markdown-based harnesses that consolidates years of software engineering best practices into rules that force your AI to plan, execute, and empirically verify its work before committing code.

This story was originally published on HackerNoon at: https://hackernoon.com/the-real-bottleneck-isnt-writing-code-its-trusting-it.
AI coding is faster than ever, but trust is the new bottleneck. Learn why verification, ownership, and guardrails matter.
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This story was written by: @swapneswarsundarray. Learn more about this writer by checking @swapneswarsundarray's about page, and for more stories, please visit hackernoon.com.

AI coding tools make code generation faster. But faster code does not always mean safer software. The real challenge is verifying and trusting generated code. Teams need stronger testing, review, ownership, and guardrails. The future belongs to teams that build trustworthy delivery systems.