Talk stage 3: Concepts

Builds an exhaustive catalogue of all identifiable concepts in the source material. Each concept is numbered, categorized, and scored for its talk potential.

When to use this skill

• After Stage 1 (and Stage 2 if REX mode)
• Before Stage 4 (Position needs the concept catalogue)
• When you want a structured inventory of what's available before choosing an angle

What this skill does

1. Reads the summary: loads {slug}-summary.md
2. Reads the timeline (if available): enriches scoring with verified dates
3. Extracts concepts: full scan of the source material
4. Categorizes: assigns each concept to a domain category
5. Scores: HIGH / MEDIUM / LOW for talk potential
6. Optional repo enrichment: if repo_path is provided, analyzes AI config concepts
7. Writes output files

Input

• talks/{YYYY}-{slug}-summary.md (required)
• talks/{YYYY}-{slug}-timeline.md (optional, enriches REX concepts)
• repo_path (optional, for config/infrastructure concept extraction)

Output

• talks/{YYYY}-{slug}-concepts.md (main catalogue)
• talks/{YYYY}-{slug}-concepts-enriched.md (if repo_path provided)

Scoring criteria

HIGH: Strong potential

• Demonstrable live or with a screenshot
• Counter-intuitive or surprising (triggers a reaction)
• Associated with verifiable numbers
• Concrete and actionable (explainable in 30 seconds)
• Differentiator vs other talks on the same topic

MEDIUM: Moderate potential

• Useful but expected (not surprising)
• Missing concrete proof or numbers
• Too specific to one particular context
• Needs too much explanation for a 30-min talk

LOW: Weak potential

• Too abstract or philosophical without concrete grounding
• Already heavily covered by other speakers
• Requires specific technical background
• Hard to illustrate in a slide

Scoring discipline: Max 30% HIGH. If everything is HIGH, nothing is.

Standard categories

Category	Description
Architecture	Technical decisions, stack, structural patterns
Tooling	Tools, workflows, automations
Philosophy	Principles, mindsets, approaches
Workflow	Work processes, habits
Knowledge Transfer	Onboarding, team, knowledge sharing
Problems	Obstacles encountered, trade-offs
Open Source	Contributions, sharing, community
AI Config	AI configuration, profiles, knowledge feeding
AI Infrastructure	Agents, skills, hooks, commands
AI Quality	Review, tests, anti-patterns
AI Security	Security hooks, guardrails
Optimization	Performance, cost/token reduction

Adapt or create categories if the talk has domain-specific areas.

Output format

concepts.md

# Key Concepts: {provisional title}

**Date**: {date}
**Source**: {source path} x Summary x Timeline (if available)

---

## Concept table

| # | Concept | Category | Short description | Talk potential |
|---|---------|----------|------------------|----------------|
| 1 | **{Concept name}** | {Category} | {1-2 concrete sentences} | HIGH / MEDIUM / LOW |
...

---

## Category breakdown

| Category | Count | HIGH concepts | Examples |
|----------|-------|---------------|---------|
| {category} | {n} | {n} | {examples} |
...
| **TOTAL** | **{N}** | **{N HIGH}** | |

---

## Recommendations for positioning

{3-5 sentences on concept clusters that could form the talk's acts.
Which HIGH concepts reinforce each other? What narrative arc is emerging?}

concepts-enriched.md (if repo available)

Same structure but focused on what the repo analysis reveals:

• Specialized agents (count, size, roles)
• Invocable skills (catalogue, domains covered)
• System hooks (events, logic)
• Modular config (profiles, modules, pipeline)
• Project-specific code patterns

For each enriched concept, include:

• Exact source: file and approximate line
• Demo-able: yes/no (can it be shown in a slide or live?)

Anti-patterns

• Creating overly granular concepts (one feature = one concept max)
• Scoring HIGH by default (be selective)
• Omitting LOW concepts (they're useful in positioning as "angles to avoid")
• Duplicating very similar concepts (merge them instead)
• Analyzing repo code if the repo isn't accessible

Validation checklist

• Minimum 15 concepts identified (20+ for REX with repo)
• Each concept has a 1-2 sentence concrete description
• Scores are calibrated (not all HIGH, not all LOW)
• Categories cover the summary's themes
• Positioning recommendations present
• Files saved to correct paths

Tips

• The concept catalogue is what Stage 4 (Position) draws from; the richer it is, the better the angle choices
• LOW concepts are valuable: they define the boundaries of what NOT to put in the talk
• If two concepts feel very similar, merge them (a smaller, sharper list beats a long diluted one)

Related

• Stage 1: Extract: prerequisite
• Stage 2: Research: provides timeline (REX)
• Stage 4: Position: reads this catalogue
• Orchestrator