Skip to content
View utaknablein's full-sized avatar
  • New York City

Block or report utaknablein

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
Utaknablein/README.md

Uta Knablein - Product | Technology | Growth

Hi, I am Uta 👋

AI made building cheap. The expensive part is deciding what deserves to be built.

I build the operating systems that help companies turn strategy into growth: how decisions get made, how teams align, how technology gets deployed, and how organizations stay coherent as execution gets faster.

This GitHub is my lab for one question:

What happens to management when machines make execution cheap?

My working answer: judgment, coherence, and organizational design become more valuable, not less.

Current work

Question Before the Question

AI answers what you ask. This checks whether you are asking the right question in the first place.

A framework and prototype for surfacing hidden assumptions before they become decisions and execution.

Product Operating System

A system for keeping strategy, priorities, decision rights, metrics, and engineering capacity on one plan as execution gets faster.

Board Devil's Advocate

An independent AI challenger that pressure-tests consequential proposals before the decision is made.

Agent Workflows

Patterns for delegating real work to agents: triggers, permissions, human checkpoints, escalation, and measurement.

ENGINE

A diagnostic for whether an organization can actually carry AI transformation rather than simply add AI tools.

Take the ENGINE diagnostic →

The thread through the work

Problem → Question → Judgment → Decision → Execution → Outcome → Learning

The cheaper execution becomes, the more expensive incoherence gets.

Background

Former Chief Product Officer at iHeartMedia and WW (WeightWatchers). Previously JPMorgan Chase, Nickelodeon, CNBC.com, and Outbrain. Machine learning in product since 2015: recommendation and personalization at consumer scale, and most recently a customer data platform built to feed agentic systems. Co-founder of ZeroFHE, licensing fully homomorphic encryption IP.

I build here to test ideas, not just write about them.

Popular repositories Loading

  1. Utaknablein Utaknablein Public

    AI made building cheap. The expensive part is deciding what deserves to be built. Frameworks and prototypes for judgment, decision rights and AI operating models.

    1

  2. engine-diagnostic engine-diagnostic Public

    A five-minute AI maturity self-assessment for leadership teams: six disciplines, four stages, and a 90-day plan built from your answers. Website: https://utaknablein.github.io/engine-diagnostic/

    JavaScript

  3. product-operating-system product-operating-system Public

    AI made building cheap. Incoherence is now the expensive part. My operating system for keeping a product org coherent and fast.

  4. agent-workflows agent-workflows Public

    How I set up AI agents to do leadership work: triggers, permissions, human checkpoints, and a scorecard.

  5. board-devils-advocate board-devils-advocate Public

    An independent AI challenger that tests every board proposal through eight lenses before the meeting, and hands directors the questions to ask in the room.

    HTML

  6. question-before-the-question question-before-the-question Public

    A pre-answer layer for AI that checks whether you are asking the right question before it answers.

    HTML