Welcome to my AI Lab Notebook

This is where I study AI not as a product, but as a system shaping human life.

Over time, three themes have defined my work:

1. AI Governance as Architecture: I build frameworks like the AI OSI Stack, persona architecture, and semantic version control because AI needs scaffolding, not slogans.

2. The Human Meaning Crisis in Machine Time: I explore how AI destabilizes identity, trust, and authenticity as machine speed outpaces human comprehension.

3. Power, Distribution, and Responsibility: I examine who benefits from AI, who is displaced, and how governance, economics, and control shape outcomes.

These pillars guide everything I write here. AI’s future won’t be determined by capability alone, it will be determined by the structures, meanings, and power dynamics we build around it.

Thanks for reading.

Dan 11/6/25 Dan 11/6/25

Update — The AI OSI Stack: A Governance Blueprint for Scalable and Trusted AI

Following my September 9, 2025 post on the AI OSI Stack, this update expands the conversation with the release of the AI OSI Stack’s canonical specification and GitHub repo. It marks a shift from concept to infrastructure: transforming the Stack into a working blueprint for accountable intelligence. Each layer, spanning civic mandate, compute, data stewardship, and reasoning integrity, turns trust into something structural and verifiable.

Dan 10/3/25 Dan 10/3/25

My Journey Through the Berghain Challenge

When a mysterious billboard appeared in San Francisco showing only strings of numbers, few realized it hid an invitation to an underground coding arena: the Berghain Challenge. Designed by Listen Labs, the game asked players to become the bouncer at Berlin’s most exclusive club—only this time, the line outside was made of data. What follows is a personal reflection on that experiment, and how stepping up to the algorithmic door became a lesson in creativity, probability, and self-trust.

Dan 9/21/25 Dan 9/21/25

Who’s Responsible for AI Job Loss?

From factory floors to corporate boardrooms, AI is already reshaping work. Some jobs vanish outright, others quietly erode into under-employment. We like to say workers can “just upskill,” but access to retraining is uneven and often out of reach for those most affected. Behind every algorithmic shift stand human choices: executives chasing efficiency, investors rewarding cuts, policymakers setting weak guardrails. The question isn’t whether AI eliminates roles, but whether those who benefit take responsibility for those left behind.

Dan 8/19/25 Dan 8/19/25

The AI Arms Race in Hiring: Why Everyone Loses

Hiring has become an arms race of algorithms, and everyone is losing. Job seekers optimize résumés for machines. Recruiters drown in applications generated by AI. Companies pursue return on investment that rarely arrives. Instead of solving the problem, technology has amplified it. The process becomes a prisoner’s dilemma where human connection is the casualty. Trust between employer and applicant erodes, replaced by optimization loops with little value. Real progress will come not from more tools, but from re-centering on dignity, clarity, and fairness in the hiring process.