RLF Modules Documentation: Difference between revisions
(Created page with "=About= The Rapid Learning Facility (RLF) functions as a build-performance capture and standardization engine, whose core purpose is to convert real production work into measurable, repeatable, and teachable capability. During live builds, all work is continuously recorded and instrumented to capture actual build times, sequences, errors, and corrections under novice and semi-pro conditions. =Rollout= The Rapid Learning Facility (RLF) operates in two distinct phases to e...") |
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Phase 2 is the training and production phase, where students and workshop participants cycle through these rapid build modules as part of live builds, using the documented workflows, QC criteria, and time benchmarks developed in Phase 1. In this phase, participants both learn and produce, while their performance data continuously feeds back into refining the modules, enabling empirically grounded training, pay calibration, and predictable production outcomes. | Phase 2 is the training and production phase, where students and workshop participants cycle through these rapid build modules as part of live builds, using the documented workflows, QC criteria, and time benchmarks developed in Phase 1. In this phase, participants both learn and produce, while their performance data continuously feeds back into refining the modules, enabling empirically grounded training, pay calibration, and predictable production outcomes. | ||
Source - [https://chatgpt.com/share/696c5978-1044-8010-b199-6ca1493141c6] | |||
Revision as of 03:54, 18 January 2026
About
The Rapid Learning Facility (RLF) functions as a build-performance capture and standardization engine, whose core purpose is to convert real production work into measurable, repeatable, and teachable capability. During live builds, all work is continuously recorded and instrumented to capture actual build times, sequences, errors, and corrections under novice and semi-pro conditions.
Rollout
The Rapid Learning Facility (RLF) operates in two distinct phases to ensure speed, accuracy, and scalability of learning. Phase 1 is the RLF capitalization phase, during which a dedicated documentation team builds out the facility by capturing real production work in full—recording build sequences, timing, errors, corrections, and quality outcomes across all core build modules. This phase converts tacit build knowledge into standardized, data-backed rapid build modules without interrupting production flow.
Phase 2 is the training and production phase, where students and workshop participants cycle through these rapid build modules as part of live builds, using the documented workflows, QC criteria, and time benchmarks developed in Phase 1. In this phase, participants both learn and produce, while their performance data continuously feeds back into refining the modules, enabling empirically grounded training, pay calibration, and predictable production outcomes.
Source - [1]