Vertical Stack from Learning to Job Requirements and Project Forecasts with the Same Skill Classifications and Compositions and Skill Points

Sunday, 05 April 2026 101 Views

To ensure consistency with the products and process we offer our B2B clients, I produce Project Labels for all proposed projects at my company.

Most recently, I created a Project Label for an AI Infrastructure proposal designed to scale our current labeling capabilities to a factor of 100, looking to achieve 100,000 labels. While Project Labels are our flagship, proprietary asset and not publicly released, I published 'watered-down' public-facing (precursor) Task Labels to act as a white paper or proof of concept.

Our current catalog of tasks encompasses the following project types:

  • Introduction of AI Infrastructure to Scale and Establish Concurrency with a Current System

  • Build a Single Screen Business Intelligence Dashboard for Reporting

  • Build New Cybersecurity Apparatus to Mitigate Current and Emerging Threats

  • Adopt and Use a New Performance Management System

  • Build Native iOS and Android Apps.

This is a link to the complete public-facing task label catalog.

The power of our system is utilizing the same skill classifications, compositions, and Skill Points across the vertical stack—from learning and training to job requirements and corporate project forecasts. Unlike aggregators challenged with data sources from billions of data points, each of our labels serves as a "source of truth" for all insights. (I estimate our data points in the 10+ millions if there is any strategic value in the metric.)

The effectiveness of our vertical stack of labels (from learning to jobs to corporate projects) recently received global validation at a Google conference. Speakers at the event specifically highlighted the importance of a skills medium, understanding tasks in both automation and work processes—almost verbatim to our system and process—to address future workforce planning and development. (Google speakers did not mention our higher-order Project Label interpretation and how it could balance the effects of AI for the future workforce.)

To learn more, visit our public facing catalogs, create an account, or contact me for more information.