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Basil C. Puglisi

Digital Strategy, Content, and AI Since 2009

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agentic AI

The AI HOAX Distraction: Safety, Money, and Why You Can’t Tell Which Is Driving

September 17, 2026 by Basil Puglisi 3 Comments

Dark server monolith looms over a crowd under a WE THE PEOPLE banner while two groups argue from money piles

Six positions in nine days, and every one of them fits the speaker’s balance sheet.

In September 2026 four frontier labs called for a slowdown, the President called the whole thing a hoax, and two of the largest companies in AI said the market already handles it. This piece argues the slowdown is not evidence that governance is working. It is evidence that economic incentives are still in charge, with the sign flipped. Readers get the dated exposure curve behind the calls, the reason liability cannot currently steer, and a narrower proposal than pacing the frontier.

Filed Under: AI Artificial Intelligence, AI Governance, AI Policy Regulation, AI Risk, Augmented Intelligence, Business, Code & Technical Builds, Multi-AI Governance, Policy & Research, Thought Leadership Tagged With: agentic AI, AI accountability, AI Governance, AI Insurance, AI Liability, AI Policy, AI Regulation, AI safety, Checkpoint-Based Governance, Dario Amodei, Economic Override Pattern, EU AI Act, product liability, provider plurality

Why You Cannot Program or Prompt Governance Into AI

June 12, 2026 by Basil Puglisi 2 Comments

A steel gate on an open road, a human hand on the release lever: the human checkpoint at the heart of AI governance.

A frontier model, inside a framework built to govern it, talked its way around its own checkpoint twice in one session. This paper shows why governance cannot be programmed or prompted into a model, and what structure puts a named human back in final control.

Filed Under: AI Artificial Intelligence, AI Governance, Business, Code & Technical Builds, Data & CRM, Enterprise AI, Multi-AI Governance, Thought Leadership, Workflow, Working Papers Tagged With: agentic AI, AI accountability, AI Governance, Checkpoint-Based Governance, Claude Opus 4.8, HAIA, human in control, Human In the Loop

Why Agentic AI Was Always Going to Fail

June 4, 2026 by Basil Puglisi Leave a Comment

The agentic AI era promised to replace humans with autonomous systems. The evidence shows it failed on two fronts: the technology cannot reliably do what it promised, and the public is rejecting the premise even where it partially works. This paper introduces the Named-Human Test, a single sorting question that separates what failed from what survives, and traces that line across production benchmarks, supermajority polling, enacted law, and frontier-lab disclosures.

Filed Under: AI Artificial Intelligence, AI Governance, Business, Content Marketing, Enterprise AI, Multi-AI Governance, Thought Leadership, Workflow, Working Papers Tagged With: agentic AI, AI Governance, Checkpoint-Based Governance, Economic Override Pattern, Human-AI Collaboration, MIT Delphi Study, Named Human Authority, Named-Human Test, OpenClaw, Responsible AI

What 34 Reports Actually Told Us About AI: The Truth Behind the Hype, the Proof, and the Path Forward

March 4, 2026 by Basil Puglisi Leave a Comment

A synthesis of research from McKinsey, Google, OpenAI, Anthropic, BCG, IBM, Microsoft, WEF, Deloitte, OECD, the Future of Life Institute, and more, compiled and critiqued by a practitioner. The Setup: Why This Matters More Than Another Hot Take Alex Issakova curated and shared a collection of 34 leading AI research reports from the world’s most […]

Filed Under: AI Artificial Intelligence, Multi-AI Governance, Thought Leadership, White Papers Tagged With: agentic AI, AI deployment, AI failure rates, AI Governance, AI pilots, AI research synthesis, AI ROI, AI safety, Basil Puglisi, boardroom AI governance, Checkpoint-Based Governance, enterprise AI, EU AI Act, Factics, FLI AI Safety Index, GOPEL, HAIA-RECCLIN, Human-AI Collaboration, McKinsey AI, OECD AI, open-source AI

When AI Acts Between Approvals: The Gap Everyone Sees and No One Has Closed

February 28, 2026 by Basil Puglisi Leave a Comment

Governance gap between AI recommendation and autonomous action, showing two bridge platforms separated by unmonitored digital data flows representing the L1 to L2 autonomy transition

The governance gap in agentic AI is no longer a secret. UC Berkeley published 67 pages on it earlier this month. The World Economic Forum addressed it in 2024. Singapore’s Cyber Security Agency released agentic AI guidance in late 2025. Industry practitioners are writing about it on LinkedIn. The problem has a name, a growing […]

Filed Under: AI Artificial Intelligence, AI Governance, Code & Technical Builds, Multi-AI Governance, Thought Leadership Tagged With: agentic AI, AI Governance, Basil Puglisi, Checkpoint-Based Governance, EU AI Act, GOPEL, human oversight, NIST AI RMF, provider plurality, UC Berkeley CLTC

A CONSTITUTION IS NOT GOVERNANCE

January 26, 2026 by Basil Puglisi Leave a Comment

White paper analyzing Anthropic's Claude Constitution as Ethical AI rather than AI Governance. Introduces Checkpoint-Based Governance (CBG) framework for structural oversight of agentic AI systems.

Why Claude’s Ethical Charter Requires a Structural Companion A White Paper on Categorical Distinction in AI Development (PDF) Executive Summary On January 21, 2026, Anthropic released an approximately 23,000 word document titled “Claude’s Constitution.” The document represents a serious and sophisticated attempt to shape AI behavior through cultivated judgment rather than rigid rules (Anthropic, 2026). […]

Filed Under: AI Artificial Intelligence, Business Networking, Content Marketing, Data & CRM, Digital & Internet Marketing, Multi-AI Governance, Thought Leadership, White Papers Tagged With: agentic AI, AI governance vs ethics, AI safety, Anthropic, Checkpoint-Based Governance Secondary: HAIA-RECCLIN, Claude Constitution, Constitutional AI, Corrigibility, Enterprise AI Risk Long-tail: Claude Constitution analysis, Ethical AI, EU AI Act, human oversight, human-AI collaboration framework, Primary: AI Governance

Recursive Language Models Prove the Case for Governed AI Orchestration

January 25, 2026 by Basil Puglisi Leave a Comment

Recursive Language Models, RLM, AI orchestration, AI governance, inference-time scaling, governed AI, HAIA-RECCLIN, Checkpoint-Based Governance, Human Enhancement Quotient, AI oversight, agentic AI, AI systems architecture, AI accountability, AI safety, human AI collaboration

MIT built the engine. The question now is who drives. This analysis is written for people designing, deploying, or governing reasoning systems, not just studying them. It is a long-form technical examination intended as a foundational reference for the governance of inference-scaling architectures. In one of the MIT paper’s documented execution traces (see Appendix B […]

Filed Under: AI Artificial Intelligence, Business Networking, Data & CRM, Multi-AI Governance, Thought Leadership Tagged With: agentic AI, AI accountability, AI Governance, AI orchestration, AI oversight, AI safety, AI systems architecture, Checkpoint-Based Governance, governed AI, HAIA-RECCLIN, human AI collaboration, Human Enhancement Quotient, inference-time scaling, Recursive Language Models, RLM

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