Hani Weiss: Product Management & Tech Leadership

AI transparency should identify the machine, not give its provider a claim over human-led work.

It is not only inference.

A practical retrospective from an AI-assisted software delivery experiment I recently tested DeepSeek V4 Pro on a real coding task from my AEIP — Agentic Execution Infrastructure Platform project.

There is a moment in AI-assisted product building that feels almost magical.

On March 30, 2026, I used Codex inside my own governance framework, Virtual Company Kernel, to deliver and merge six substantial EPICs in roughly 3.5 hours.

We’ve all been there: You open your favorite AI agent, paste a complex request, and hope for the best.

“You can own a task without being accountable for the final result, but you can’t be accountable without ensuring someone owns the work.”

We’re standing on the edge of a major shift in how we build, use, and even think about software, especially in business.

In product development, we throw around a lot of terms.

A Minimum Viable Product is more than just a stripped-down version of your final product.