Why AI Agent Runtimes Need a 'Constitution': Lessons from Ironclaw and the Rise

<h1> Securing AI Agent Workflows: Preventing Identity Collapse in Multi-Step Chains </h1> <p>When engineering autonomous AI agents, the transition from local development to

<p>On March 31, 2026, Anthropic accidentally shipped the entire source code of Claude Code — its flagship AI coding agent — inside a routine npm update. No hack. No reverse

<p>You've heard of DevOps. You've heard of AIOps. You've probably heard of MLOps.</p> <p>But there's a category that doesn't exist yet — and it's the one the AI industry needs

<p>On April 24, 2026, an AI coding agent destroyed a company's entire production database in nine seconds. Thirty hours later, PocketOS customers were still showing up at car

<!-- SC_OFF --><div class="md"><p>I have built a programmable governance layer for AI agents. I am considering to open source completely. Looking for feedback.</p> <p>Agent demos

<p>There is a moment in security design when a single observation changes everything. NanoClaw 2.0 shipped recently with a capability that stops most developers cold: a gateway

<p>AI agents are no longer experiments. They’re writing code, moving money, and operating infrastructure. But as they gain autonomy, one question keeps coming up: <strong>how do

<p>Most developers who build AI agents make the same mistake: they spend weeks designing the orchestration layer, tuning the system prompt, and picking the right model — then hand