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Essays, posts & field notes
Longer essays and short observations on AI agents, governance, and what's working in production.
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You can't copyright most of what your AI makes, and that's your smaller problem
Prompt-only AI output gets no US copyright, and the training-data cases set your liability. What marketers should know as of mid-2026, indemnities included.
The EU AI Act is a 2026 problem for marketers, not a 2027 one
The EU AI Act's high-risk rules slipped to 2027. Article 50 disclosure still applies August 2, 2026, and it covers AI avatars, voiceovers, and chatbots.
What actually governs your feed in 2026
The filter-bubble story took empirical hits, but feeds now shift specific attitudes, carry mostly AI slop, and face binding rules only in the EU.
Responsible AI Needs Architects, Not Just Advocates
Responsible AI has its principles and almost none of the runtime that enforces them. The next credible RAI leaders will ship evals and middleware.
MCP and the new agent supply chain
Every MCP server you connect is third-party code your model trusts by reading. A pragmatic threat model and the controls that work.
Evals over vibes
If you can't say whether the new prompt beats the old one, you're vibing, not iterating. Here's a 30-minute eval that fixes it.
Three orchestration patterns that aren't 'just call the LLM in a loop'
When to use routing, parallel fan-out, or orchestrator-workers, and the tradeoffs of each, drawn from the subagents I run every day.
The agent stack, top to bottom
Tools, skills, and agents: the three-layer mental model that explains every multi-agent system I've reviewed.
Protocols of Power: The Hidden Politics of Enterprise Multi-Agent Systems
My Cambridge dissertation on Google's Agent2Agent (A2A) protocol, the dominant standard for enterprise AI agents, and a Foucauldian reading of why moving A2A to the Linux Foundation was a political act.
The Data Dilemma: Reconciling Privacy and Fairness in AI
AI governance often treats privacy and fairness as opposing values. This essay tests that binary against GDPR's special-category rules, US self-regulation, Amazon's hiring algorithm, the Apple Card, and IBM's facial-recognition exit.
Beyond Principles: Examining the Conflicts in Implementing Responsible AI in Enterprise Structures
AI ethics has produced many principles and few mechanisms for enforcing them. A critical reading of Rakova et al. (2021) and Marchant (2021), with lessons from the FLA and IAB on where industry self-regulation falls short.
Beyond the Hype: Navigating the Ethics of AI-Driven Marketing
Microtargeting and hypernudging raise valid autonomy concerns, but much of the public debate rests on simple narratives that overstate AI's persuasive power. The essay proposes an ethical framework grounded in the evidence.
ESG Echoes in AI Ethics: Drawing Lessons from Corporate Sustainability's Missteps for Effective Algorithmic Accountability
ESG promised to align corporate behavior with social welfare and largely failed. The essay argues that AI ethics is repeating the pattern and needs enforceable regulation in place of voluntary frameworks.