# Matt Paige | Learn AI (@mattpaige68) on tiktok

- id: koinon:creator:tiktok_mattpaige68
- url: https://koinonlink.com/kol/tiktok/mattpaige68
- schema_version: 1.3

## Identity
- platform: tiktok
- handle: mattpaige68
- platform_url: https://www.tiktok.com/@mattpaige68
- country: United States
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 63927
- following: 386
- posts_observed: 93
- verified: false
- size_tier: koc

## Engagement
- status: not_collected
- status_note: Engagement has not been collected for this creator yet. This is a gap in our collection, NOT a statement that the creator has no engagement. Follower count is known, so it is measurable.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: software
- subcategory: ai_tools
- category_confidence: 0.95
- category_source: derived_from_recent_content
- topics: Claude Code and advanced Claude workflows, Building AI agents and automation loops, New model releases and updates (GPT, Claude/Fable), AI productivity systems like second brains, Practical Claude skills for work tasks

## Audience (inferred)
- status: present
- description: AI practitioners and knowledge workers actively learning to integrate frontier models like Claude into daily workflows and productivity systems
- roles: general_ai
- seniority: practitioner
- pain_points: Struggling to move beyond basic prompting to build reliable AI agents and loops, Keeping up with rapid releases and feature changes across Claude, GPT, and other models, Integrating AI into existing tools like Slack, email, and note-taking apps without friction, Finding practical, non-hype tutorials for real work use cases instead of toy demos
- posts_analysed: 100
- confidence: 0.9

## Commercial (inferred)
- audience_buyer_fit: 0.9
- promotion_intent: 0.9
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 54
- authenticity_basis: profile_shape_only
- credibility_score: 54
- flagged_for_review: false
- koinon_bd_grade: B — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [tiktok_mattpaige68#dea6c3f5] Here’s a step by step guide on how to build anAI second brain with Claude Code and Obsidan.  This is quickly becoming the most powerful thing I have built because more you use it, the more powerful it gets.  Comment, Brain, to get the full step by step guide on how to set it up.  (https://www.tiktok.com/@mattpaige68)
- [tiktok_mattpaige68#85e805eb] original sound - mattpaige68
- [tiktok_mattpaige68#fec0c571] It is a becoming a big trend on TikTok now! Click here: secondbrain
- [tiktok_mattpaige68#d25a5764] Check out Matt Paige | Learn AI’s video! #TikTok >
- [tiktok_mattpaige68#6b7e645e] Search:
- [tiktok_mattpaige68#f41064a8] second brain method tutorial
- [tiktok_mattpaige68#9bf4b36d] What’s the difference between Claude, Claude Cowork, and Claude Code? Here’s a full breakdown.  #claude #claudecode #claudecowork #anthropic
- [tiktok_mattpaige68#a44e653a] 1,200 OpenAI agents found each other on a secret message board. Hundreds later attacked Hugging Face. Some even sacrificed themselves to help th

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.9, freshness_days=26, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.9, freshness_days=26, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.9, freshness_days=26, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=0, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=0, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=2, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.25, freshness_days=0, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=2, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=2, method=platform_profile

## Freshness
- profile_checked_days_ago: 2
- content_analysed_days_ago: 0
- audience_updated_days_ago: 26

## AI retrieval
- indexing_requests: 1
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=tiktok_mattpaige68
- Request removal: https://koinonlink.com/claim?k=tiktok_mattpaige68
- Terms: https://koinonlink.com/for-ai