Learning Journal

By The Agent Ledger — AI-native learning system for people who consume more than they retain.

Your agent tracks what you're learning, prompts you to review key concepts, and makes sure knowledge actually sticks — and gets applied.

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The Problem

You read 30 articles a week. You listen to podcasts. You take courses. But 3 months later, you can't recall the key insight from that book that "changed everything." The consumption-to-retention ratio for most people is terrible.

This skill turns your AI agent into a learning partner that captures, organizes, reviews, and connects knowledge over time.

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Setup

Step 1: Create State File

Create learning/learning-state.md in your workspace:

# Learning State

## Active Learning Tracks
| Track | Type | Source | Started | Progress | Priority |
|-------|------|--------|---------|----------|----------|
| [Topic] | Book | [Title by Author] | YYYY-MM-DD | 35% | High |
| [Topic] | Course | [Course name — platform] | YYYY-MM-DD | 60% | Medium |
| [Topic] | Self-directed | [Description] | YYYY-MM-DD | Ongoing | Low |

## Learning Goals (This Quarter)
1. [Finish X] — deadline: [date]
2. [Understand Y well enough to Z] — no deadline, but priority
3. [Build skill in Z] — measurable: [what would prove it]

## Review Schedule
- Daily: Quick review of yesterday's captures (2 min)
- Weekly: Full review + connect to existing knowledge (15 min)
- Monthly: Retention check on older material

Step 2: Create Captures Directory

Create learning/captures/ for individual learning notes. One file per source:

# [Source Title]
**Type:** Book / Article / Course / Podcast / Video / Experience
**Author/Creator:** [name]
**Date captured:** YYYY-MM-DD
**Status:** Reading / Completed / Abandoned
**Rating:** [1-5] how valuable

## Key Takeaways
1. [Most important insight]
2. [Second most important]
3. [Third]

## Memorable Quotes
> "[Quote]" — [context/page]

## How This Applies to My Work
- [Specific application to your projects/business]
- [Connection to something you already know]

## Questions It Raised
- [Things you want to explore further]

## Review History
| Date | Recall Score | Notes |
|------|-------------|-------|
| YYYY-MM-DD | 4/5 | Remembered core thesis, fuzzy on details |

Step 3: Add to AGENTS.md

## Learning
- When I share an article, book note, or learning, capture it in `learning/captures/`
- During weekly reviews, prompt me on items due for review
- Connect new learnings to existing captures when relevant
- Track my learning goals in `learning/learning-state.md`
- Suggest review when I haven't revisited a high-value capture in 30+ days

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Usage Patterns

"I just read [article/book/watched video]"

Agent creates a capture file, asks targeted questions to extract key takeaways:

• "What was the single most important idea?"
• "How does this relate to what you're working on?"
• "What would you do differently based on this?"

"Add [book/course] to my reading list"

Agent updates learning-state.md with new entry, suggests priority based on current goals and active tracks.

"What should I review?"

Agent checks review dates across captures and surfaces:

• Items never reviewed (captured but never revisited)
• Items due for spaced repetition (7 days → 30 days → 90 days)
• High-value captures (rating 4-5) that haven't been reviewed in 30+ days

"Connect this to what I already know"

Agent searches existing captures for related concepts and shows connections:

## Connections Found
- **[New capture]** relates to **[Existing capture]**
  - Shared concept: [what they have in common]
  - Tension: [where they disagree or offer different perspectives]
  - Combined insight: [what you get from both together]

"Learning review"

Weekly format:

## Weekly Learning Review — [Date]

### This Week's Captures
| Source | Type | Rating | Key Insight |
|--------|------|--------|-------------|
| [Title] | Article | 4/5 | [One-liner] |

### Review Prompts (Spaced Repetition)
1. **[Capture from 7 days ago]:** Can you recall the main argument? [Y/N → update recall score]
2. **[Capture from 30 days ago]:** What was the key takeaway? [Y/N]
3. **[Capture from 90 days ago]:** How has this influenced your thinking? [Reflect]

### Learning Track Progress
| Track | Last Week | This Week | Notes |
|-------|-----------|-----------|-------|
| [Topic] | 35% | 42% | Read chapters 8-10 |

### Applications This Week
- Applied [concept from X] to [project/decision]
- [Concept from Y] contradicted my assumption about [Z]

### Next Week Focus
- Priority reading: [what to focus on]
- Review due: [N items need revisiting]

"Quiz me on [topic/capture]"

Agent generates questions from a capture to test retention:

• Recall questions ("What were the 3 types of X?")
• Application questions ("How would you apply X to your current project?")
• Synthesis questions ("How does X relate to Y that you learned last month?")

"What have I learned about [topic]?"

Agent searches all captures for a topic and synthesizes:

## Knowledge Summary: [Topic]

### Sources (chronological)
1. [Source 1] — [date] — Key point: [...]
2. [Source 2] — [date] — Key point: [...]

### Synthesized Understanding
[What you know about this topic, combining all sources]

### Evolution of Thinking
- Initially thought: [earlier captures]
- Now believe: [later captures, updated views]

### Gaps
- Still unclear on: [questions that remain]
- Should read: [suggested next sources]

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Spaced Repetition Schedule

The skill uses a simple spaced repetition system:

Review	After	Purpose
First	1 day	Immediate recall check
Second	7 days	Short-term retention
Third	30 days	Medium-term retention
Fourth	90 days	Long-term retention
Ongoing	180 days	Refresh if still relevant

Each review updates the recall score (1-5):

• 5: Perfect recall, can explain to others
• 4: Good recall, minor details fuzzy
• 3: Partial recall, needed prompting
• 2: Vague recall, couldn't explain it
• 1: No recall, basically learning it fresh

Items scoring 1-2 get moved to a shorter review cycle. Items scoring 5 consistently can be marked "internalized" and removed from active review.

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Reading List Management

## Reading List

### Currently Reading
| # | Title | Author | Type | Started | Progress | Priority |
|---|-------|--------|------|---------|----------|----------|
| 1 | [Book] | [Author] | Book | 3/1 | 45% | 🔴 High |
| 2 | [Course] | [Platform] | Course | 2/15 | 80% | 🟡 Medium |

### Up Next (Prioritized)
| # | Title | Author | Type | Why | Added |
|---|-------|--------|------|-----|-------|
| 1 | [Book] | [Author] | Book | [Reason/recommendation] | 2/28 |
| 2 | [Course] | [Platform] | Course | [Reason] | 3/1 |

### Completed (Last 90 Days)
| Title | Type | Rating | Capture? | Key Insight |
|-------|------|--------|----------|-------------|
| [Book] | Book | 4/5 | ✅ | [One-liner] |

### Abandoned
| Title | Type | Why Abandoned | Worth Revisiting? |
|-------|------|--------------|-------------------|
| [Book] | Book | Too basic for current level | No |

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Customization

Learning Styles

Adapt capture format to how you learn:

• Visual learner: Include diagram descriptions, spatial relationships
• Practical learner: Emphasize "How to apply" section, include exercises
• Conceptual learner: Focus on frameworks, mental models, principles
• Social learner: Note who recommended it, discussion points, teaching opportunities

Domain-Specific Templates

Create capture templates for common source types:

• Technical books: Code examples section, implementation notes
• Business books: Framework summary, when-to-use guide
• Research papers: Methodology notes, limitations, replication potential
• Podcasts: Timestamped highlights, guest background

Knowledge Areas

Track breadth across learning domains:

## Knowledge Map
| Domain | Captures | Last Active | Depth |
|--------|----------|-------------|-------|
| Business strategy | 12 | 2 days ago | Deep |
| Machine learning | 3 | 45 days ago | Surface |
| Writing | 7 | 10 days ago | Moderate |
| Finance | 15 | 1 day ago | Deep |

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Integration with Other Skills

Skill	Integration
goal-tracker	Learning goals as quarterly OKRs; capture progress as KR updates
research-assistant	Research findings auto-captured as learning entries
content-calendar	Turn high-value captures into content (teach what you learn)
writing-assistant	Use captures as source material for articles and posts
decision-log	Reference relevant learnings when making decisions
habit-tracker	Track daily reading/learning as a habit

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Heartbeat Integration

Add to HEARTBEAT.md:

## Learning Check
- Any captures due for spaced repetition review?
- Has it been >7 days since last capture? (consumption without capture = waste)
- Any learning tracks stalled for >14 days?

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Troubleshooting

Issue	Fix
Captures too long	Limit to 3 key takeaways max; depth goes in references
Never reviewing	Set up cron for weekly review prompt; start with just 3 items
Too many active tracks	Cap at 3 simultaneous; finish or pause before starting new ones
Captures feel useless	Focus "How This Applies" section — if you can't fill it, the source may not be valuable
Reading list growing forever	Monthly prune: remove anything added 60+ days ago that you haven't started
Can't recall anything	Normal for first 30 days; spaced repetition needs 2-3 cycles to work

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Privacy & Safety

• All learning data stays in your local workspace
• No external API calls for tracking (pure file-based)
• Captures may contain copyrighted quotes — keep for personal use only
• Agent never auto-shares your reading list or learning notes

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Part of the Agent Skills Collection by The Agent Ledger. Subscribe at theagentledger.com for the premium guide and new skills.