The agent boom is turning mistakes into “liability laundering,” where vendors blame prompts, users blame models, and no one can be meaningfully held to account. The fix is not another safety slogan. It is standardizing proof at the moment of action, so agents cannot become blameless proxies.
When intelligence learns to upgrade itself, progress turns into a feedback loop. From a Skyrim glitch to real-world AI, the lesson is clear: without alignment and governance, optimisation can spiral beyond control. The question is whether we forge wisdom before we forge gods.
Without a red button to halt a runaway model, AI labs risk crossing dangerous boundaries. This feature proposes an abort doctrine, echoing mission rules and market circuit breakers, to define thresholds, assign independent authority and mandate learning. It calls for balancing innovation with safety
Belief is no longer built—it’s brokered by networks. This piece dissects the algorithmic supply chains that curate our feeds and introduces an Information Audit Kit to measure, audit, and restore epistemic health and trust in digital ecosystems, offering a blueprint for audited platforms & fairness.
Executive Summary
Artificial intelligence (AI) is often marketed as a technology that reduces labour: chatbots replace customer‑service agents, machine‑learning models sort résumés and computer vision powers driverless cars. However, every breakthrough
