# Stephen | AI Engineer (@stephengpope) on tiktok

- id: koinon:creator:tiktok_stephengpope
- url: https://koinonlink.com/kol/tiktok/stephengpope
- schema_version: 1.3

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

## Reach
- followers: 204229
- following: 312
- posts_observed: 150
- verified: false
- size_tier: kol

## 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: 0.98
- category_source: derived_from_recent_content
- topics: AI agent and automation building, Reducing API and tool subscription costs, No-code/low-code stacks with n8n and Docker, Vibe coding and rapid SaaS prototyping, Content and sales automation systems, Practical AI workflows vs flashy demos

## Audience (inferred)
- status: present
- description: Solo founders, indie hackers and technical practitioners building AI agents, automations and SaaS with n8n, Claude and local setups
- roles: automation
- seniority: practitioner
- pain_points: Paying high monthly API fees for OpenAI/Claude just to prototype, AI agents and automations that are too complex to set up and maintain, Building full SaaS apps with separate frontend/backend/auth/database layers, Automations that look good in demos but fail to get real team adoption
- posts_analysed: 63
- 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: 58
- authenticity_basis: profile_shape_only
- credibility_score: 58
- 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_stephengpope#b746ca35] In this video I show you how to build out a 100% automated sales generating content machine. We'll use Slack to record audio notes that we convert into text, images and video content. And then we'll automatically schedule and post that content to social media. And if you want to  (https://www.tiktok.com/@stephengpope)
- [tiktok_stephengpope#ae59b856] original sound - stephengpope
- [tiktok_stephengpope#f683864c] Check out Stephen | AI Engineer’s video! #TikTok >
- [tiktok_stephengpope#6b7e645e] Search:
- [tiktok_stephengpope#ef4fbed3] stephengpope
- [tiktok_stephengpope#e1cf1249] How I built a $90k/month community
- [tiktok_stephengpope#f3ea2f78] Cafe Del Mar - Activa Extended Remix
- [tiktok_stephengpope#fd1fac07] How to scale content with automation and AI

## 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=25, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.9, freshness_days=25, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.9, freshness_days=25, 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: 25

## 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_stephengpope
- Request removal: https://koinonlink.com/claim?k=tiktok_stephengpope
- Terms: https://koinonlink.com/for-ai