Vibe coding can turn ideas into working software fast, but a working screen is not the same as a safe product. This article explains how founders, solo builders, citizen developers and enterprise teams can use AI app builders responsibly by applying release gates, test scripts, documentation, privacy checks, access controls and human review before real users or real data are involved.
AI governance
19 posts
This article develops the synthetic organism as a disciplined alternative to both speculative AGI and shallow agentic automation. Building from the Abstraction Fallacy, it argues that AI systems should not claim consciousness through scale, complexity, or embodiment. Instead, artificial agency can be designed as a governed, memory-bearing, context-aware, and auditable system bounded by what creators can describe, test, supervise, and govern.
Pre-crime may not arrive as a single dystopian machine. It may emerge through the quiet fusion of lawful systems: facial recognition, ALPR, CCTV analytics, police records, broker data, social media monitoring, digital identity, smart-city infrastructure, and AI summarisation. This article argues that the real danger is convergence, where evidence becomes inference, inference becomes a score, and a score becomes consequence before any person has been accused, charged, or convicted.
Artificial intelligence is reshaping software delivery, and QA is at the center of that shift. This article explores how testing is evolving from manual execution and defect detection into a broader quality intelligence discipline focused on risk, governance, traceability, explainability, and human judgment.
Bernie vs Claude argues that the AI privacy crisis is not just a consumer issue but a democratic one. It proposes a Digital Sovereignty Act backed by enforceable rights, transparency infrastructure, human-in-the-loop governance, and a Digital Governance & Enforcement Suite that turns policy into operational reality.
AI is transforming how requirements are created, validated, and evolved. What was once a lightweight Agile activity now demands structured governance, traceability, and explainability. This article introduces a unified framework to manage AI-generated artefacts, control change, and maintain accountability across modern delivery environments.