# Matt Pocock (@mattpocockuk) on tiktok

- id: koinon:creator:tiktok_mattpocockuk
- url: https://koinonlink.com/kol/tiktok/mattpocockuk
- schema_version: 1.4

## Identity
- platform: tiktok
- handle: mattpocockuk
- platform_url: https://www.tiktok.com/@mattpocockuk
- website: https://totaltypescript.com
- country: United Kingdom
- entity_type: creator
- person_id: koinon:person:youtube_mattpocockuk

## Reach
- followers: 10319
- following: 61
- posts_observed: 1
- 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: devtools
- category_confidence: 0.95
- category_source: derived_from_recent_content
- topics: TypeScript patterns and advanced typing, Building AI agents and workflows, LLM prompting, tools, and observability, AI app architecture and guardrails, Recommended libraries and frameworks for TS + AI
- bio: Full-time TS/AI educator. Ex-Vercel. Creator of AI Hero.

## Audience (inferred)
- status: present
- description: TypeScript developers actively building AI apps, agents, and LLM-powered tools
- roles: dev
- seniority: practitioner
- pain_points: LLM hallucinations and unreliable agent outputs, Choosing the right models, tools, and frameworks for AI coding, Managing context windows, tokens, and prompt engineering effectively, Writing maintainable TypeScript types and patterns for AI applications
- posts_analysed: 80
- confidence: 0.9

## Commercial (inferred)
- audience_buyer_fit: 0.9
- promotion_intent: 0.8
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 44
- authenticity_basis: profile_shape_only
- credibility_score: 44
- flagged_for_review: false
- koinon_bd_grade: C — 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_mattpocockuk#06cfa52c] Yes, template literal error codes are actually useful (https://www.tiktok.com/@mattpocockuk)
- [tiktok_mattpocockuk#92ec4f46] original sound - mattpocockuk
- [tiktok_mattpocockuk#5d78e7f8] Check out Matt Pocock’s video! #TikTok >
- [tiktok_mattpocockuk#73670aa1] Library types can run, but they can't hide
- [tiktok_mattpocockuk#e283100c] There is no such thing as greenfield
- [tiktok_mattpocockuk#4e7793e4] Using /grill-me for interviews?!
- [tiktok_mattpocockuk#6b7e645e] Search:
- [tiktok_mattpocockuk#522e6dbc] grill me

## 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=79, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.9, freshness_days=79, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.9, freshness_days=79, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=79, 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=79, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=99, 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=79, 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=99, 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=99, method=platform_profile

## Freshness
- profile_checked_days_ago: 99
- content_analysed_days_ago: 79
- audience_updated_days_ago: 79

## AI retrieval
- indexing_requests: 8
- 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_mattpocockuk
- Request removal: https://koinonlink.com/claim?k=tiktok_mattpocockuk
- Terms: https://koinonlink.com/for-ai