Multi-agentPersonal Development & CareerAdvancedFree

Learning & Skill Acquisition System.

3 agents, 3 deliverables.

Run a multi-agent workflow to produce an execution-ready learning & skill acquisition system deliverable.

WORKFLOW META

Agents3

Total tokens (avg)~500

Run time9 min

AI toolChatGPT · Claude · Gemini

Variables4

DifficultyAdvanced

CategoryPersonal Development & Career

SEQUENCE MAP · CLICK TO JUMP

· 01 ·

Learning Pathway Designer

· 02 ·

Resource Curation Agent

· 03 ·

Learning Schedule Builder

USE CASE INPUTS

Set the workflow's inputs once.

These variables feed into every agent prompt below. Fill them once, then copy each agent in order.

Skill to learn

Learning & Skill Acquisition System example context

Current level

Learning & Skill Acquisition System example context

Time available

Learning & Skill Acquisition System example context

Learning goal

increase organic traffic and generate product sales

THE AGENTS

The 3-step sequence.

AGENT · LEARNING PATHWAY

Learning Pathway Designer

GOAL OF THIS STEP

Design the optimal learning pathway. Define: the skill tree (what sub-skills make up mastery of this skill — ordered from foundational to advanced), the 80/20 analysis (which 20% of the skill delivers 80% of the practical value?), the learning sequence (in what order to learn sub-skills — what must be learned before the next can make sense), and the time-to-competence estimate (basic competence, practical application, professional-level mastery) given the weekly time available.

EXPECTED OUTPUT

Skill tree + 80/20 priority analysis + learning sequence + time-to-competence estimates at 3 levels

agent-01-learning-pathway-designer.md

### Input
Skill, current level, time, goal

### Task
Design the optimal learning pathway. Define: the skill tree (what sub-skills make up mastery of this skill — ordered from foundational to advanced), the 80/20 analysis (which 20% of the skill delivers 80% of the practical value?), the learning sequence (in what order to learn sub-skills — what must be learned before the next can make sense), and the time-to-competence estimate (basic competence, practical application, professional-level mastery) given the weekly time available.

### Output
Skill tree + 80/20 priority analysis + learning sequence + time-to-competence estimates at 3 levels

AGENT · RESOURCE CURATION

Resource Curation Agent

AGENT · LEARNING SCHEDULE

Learning Schedule Builder

HOW TO RUN

Three steps. 9 min.

STEP 01

Fill in the variables at the top. Copy them into a note or your tool's context window — every agent below uses them.

STEP 02

In your AI tool, paste Agent 1 and run it. Copy the output. Paste Agent 2 with the output appended. Repeat in order for all 3 agents.

STEP 03

At the final agent, review and refine. It outputs your finished deliverable, ready to publish or hand off.

WHAT YOU GET

The final output, end-to-end.

Learning Pathway Designer

Skill tree + 80/20 priority analysis + learning sequence + time-to-competence estimates at 3 levels

Resource Curation Agent

Resource stack per stage: primary course + 2 practice resources + community + project — with free/paid flag

Learning Schedule Builder

12-week learning schedule: focus + daily block + practice exercise + weekly assessment + difficulty flags

★ MULTI-AGENT PACK

The Multi-Agent Operator Pack.

100 production-ready workflows like this one. Agent prompts, variable cheat-sheets, and the operator's guide.

Free

View pack →

Learning & Skill Acquisition System.

Set the workflow's inputs once.

The 3-step sequence.

Learning Pathway Designer

Resource Curation Agent

Learning Schedule Builder

Three steps. 9 min.

The final output, end-to-end.

More multi-agent systems.

Career Strategy & Growth Plan System

Job Search & Application Optimization System

LinkedIn Profile & Personal Brand System

The Multi-Agent Operator Pack.