Catalogue › Learning and Skills

CopilotForge - Learning and Skills

Use it in Copilot Cowork: download the Learning and Skills plugin for Copilot Cowork and upload it under Customize > Plugins > Upload plugin. How to install.

Create role-based learning, practice, assessment and progression pathways.

Layer: adoption
Lead role: Learning Lead
Plugin name: copilotforge-learning-and-skills

Skill Status Lifecycle Description

advanced-pathways draft Enable, Deliver, Scale Designs advanced AI pathways for makers, power users and specialists - entry on declared role, approved access and maker commitments, tracks for delegated Cowork work, agent and automation makers, Copilot Code and Microsoft Foundry, learning by building in governed sandboxes with mentoring, and evidence from a reviewed build. Use when building opens to more people, when makers learn in production, or when specialists lack a route.

ai-learning-pathway draft Mobilise, Enable, Scale, Improve Designs the progressive AI learning pathway shared across roles - foundation, applied, proficient and advanced levels with entry conditions and exit evidence, a route to skip a level by showing evidence, where role curricula and the Champion journey plug in, and refreshers when Microsoft AI changes. Use when every team builds its own course, when experienced users are forced through basics, or when nobody knows what follows foundation.

ai-role-curriculum draft Mobilise, Enable, Improve Builds a role-based AI curriculum for one priority role at a time from its skills needs statement - outcomes tied to the role's real scenarios, modules in sequence, formats that fit how the role works, practice on its own work, the evidence each outcome needs, agreed time and owners. Use when a role's needs are agreed and its learning must be designed, when generic courses are not changing work, or when a new role joins a wave.

ai-skills-needs-analysis draft Discover, Mobilise, Enable Analyses AI skills needs role by role, comparing the skills people have declared with what their future work will demand - the scenarios, agents and delegated tasks heading their way - and produces a prioritised needs statement per role, never per person. Use when a learning budget is being set, when training is about to be bought before anyone knows what roles need, or when a new group of roles joins the rollout.

facilitator-guide draft Enable, Launch, Improve Writes facilitator guides for AI learning sessions - outcomes, a timed running order, live demonstrations with a fallback when Copilot answers differently, protected hands-on practice, fictional materials, likely questions with safe answers, accessibility and an evidence step - so any prepared facilitator can run the session well. Use when a session depends on one presenter, when demos fail live, or before handing delivery to Champions.

learning-evidence-rubric draft Enable, Measure, Improve Defines the evidence rubrics that verify workforce AI learning - acceptable evidence types per pathway level, dimensions such as real work, safe use, verification, judgement and transfer with Not yet, Meets and Strong descriptors, who checks evidence and how, feedback and redaction rules - so completion means demonstrated practice, not attendance. Use when learning is counted by attendance, or when a pathway level or module needs exit criteria.

office-hours draft Launch, Enable, Improve Runs AI office hours and drop-in clinics as a learning service - open and themed formats, rhythm and timing, who staffs them, booking, safe screen-sharing, a light triage that routes faults and data concerns to the right support route, and capture of recurring questions by theme into curricula and guidance. Use when learners stall after training, when the same questions keep reaching the service desk, or when clinics have gone quiet.

practice-labs draft Enable, Deliver, Improve Designs safe hands-on practice for AI learning - realistic fictional scenario packs, practice spaces matched to what is being learnt from a learner's own approved tools to isolated maker and specialist sandboxes, rules on what may enter them, reset and clean-up, and lab exercises with expected results and a check step. Use when training is all demonstration, when people practise on live customer data, or when makers need somewhere safe to build.

skills-measurement draft Measure, Improve Measures AI skills growth at role and team level - declared-skills re-surveys against the needs baseline, verified evidence rates by pathway level, progression and time to evidence - and tests whether groups that built skills changed how they use AI, with a minimum group size and no per-person reporting. Use when a sponsor asks whether learning worked, before a learning dashboard is built, or when learning and adoption data disagree.

Skill	Status	Lifecycle	Description
`advanced-pathways`	draft	Enable, Deliver, Scale	Designs advanced AI pathways for makers, power users and specialists - entry on declared role, approved access and maker commitments, tracks for delegated Cowork work, agent and automation makers, Copilot Code and Microsoft Foundry, learning by building in governed sandboxes with mentoring, and evidence from a reviewed build. Use when building opens to more people, when makers learn in production, or when specialists lack a route.
`ai-learning-pathway`	draft	Mobilise, Enable, Scale, Improve	Designs the progressive AI learning pathway shared across roles - foundation, applied, proficient and advanced levels with entry conditions and exit evidence, a route to skip a level by showing evidence, where role curricula and the Champion journey plug in, and refreshers when Microsoft AI changes. Use when every team builds its own course, when experienced users are forced through basics, or when nobody knows what follows foundation.
`ai-role-curriculum`	draft	Mobilise, Enable, Improve	Builds a role-based AI curriculum for one priority role at a time from its skills needs statement - outcomes tied to the role's real scenarios, modules in sequence, formats that fit how the role works, practice on its own work, the evidence each outcome needs, agreed time and owners. Use when a role's needs are agreed and its learning must be designed, when generic courses are not changing work, or when a new role joins a wave.
`ai-skills-needs-analysis`	draft	Discover, Mobilise, Enable	Analyses AI skills needs role by role, comparing the skills people have declared with what their future work will demand - the scenarios, agents and delegated tasks heading their way - and produces a prioritised needs statement per role, never per person. Use when a learning budget is being set, when training is about to be bought before anyone knows what roles need, or when a new group of roles joins the rollout.
`facilitator-guide`	draft	Enable, Launch, Improve	Writes facilitator guides for AI learning sessions - outcomes, a timed running order, live demonstrations with a fallback when Copilot answers differently, protected hands-on practice, fictional materials, likely questions with safe answers, accessibility and an evidence step - so any prepared facilitator can run the session well. Use when a session depends on one presenter, when demos fail live, or before handing delivery to Champions.
`learning-evidence-rubric`	draft	Enable, Measure, Improve	Defines the evidence rubrics that verify workforce AI learning - acceptable evidence types per pathway level, dimensions such as real work, safe use, verification, judgement and transfer with Not yet, Meets and Strong descriptors, who checks evidence and how, feedback and redaction rules - so completion means demonstrated practice, not attendance. Use when learning is counted by attendance, or when a pathway level or module needs exit criteria.
`office-hours`	draft	Launch, Enable, Improve	Runs AI office hours and drop-in clinics as a learning service - open and themed formats, rhythm and timing, who staffs them, booking, safe screen-sharing, a light triage that routes faults and data concerns to the right support route, and capture of recurring questions by theme into curricula and guidance. Use when learners stall after training, when the same questions keep reaching the service desk, or when clinics have gone quiet.
`practice-labs`	draft	Enable, Deliver, Improve	Designs safe hands-on practice for AI learning - realistic fictional scenario packs, practice spaces matched to what is being learnt from a learner's own approved tools to isolated maker and specialist sandboxes, rules on what may enter them, reset and clean-up, and lab exercises with expected results and a check step. Use when training is all demonstration, when people practise on live customer data, or when makers need somewhere safe to build.
`skills-measurement`	draft	Measure, Improve	Measures AI skills growth at role and team level - declared-skills re-surveys against the needs baseline, verified evidence rates by pathway level, progression and time to evidence - and tests whether groups that built skills changed how they use AI, with a minimum group size and no per-person reporting. Use when a sponsor asks whether learning worked, before a learning dashboard is built, or when learning and adoption data disagree.

Credit

Created by Simon Foote as part of CopilotForge. Content is licensed under CC BY 4.0; keep the credit in each skill's license and authors fields when you share or adapt it. See NOTICE.md in the repository.