# Dan Ilies (@dan.mobile.developer) on youtube

- id: koinon:creator:youtube_dan.mobile.developer
- url: https://koinonlink.com/kol/youtube/dan.mobile.developer
- schema_version: 1.4

## Identity
- platform: youtube
- handle: dan.mobile.developer
- platform_url: https://www.youtube.com/@dan.mobile.developer
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 7330
- posts_observed: 2
- verified: false
- size_tier: nano

## 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: 0.9
- category_source: derived_from_recent_content
- topics: Mobile app development with Kotlin, Swift, Flutter, CMP, AI coding tools (Claude, Codex, LLMs) in real workflows, Developer career trends and 2026 outlook, App architecture and productivity techniques, Tech comparisons and future-proofing choices
- bio: Hi there! I'm Dan, a Mobile Software Engineer ‍   making apps since 2015 for iOS and Android using native technologies like ...

## Audience (inferred)
- status: present
- description: Mobile app developers (iOS/Android) with 2-10+ years experience, actively using or evaluating AI coding tools
- roles: dev
- seniority: practitioner
- pain_points: Keeping up with AI tools and new frameworks without falling behind, Deciding whether to adopt Kotlin Multiplatform, Flutter or stay native in 2026, Maintaining focus and code quality when LLMs generate large parts of the app, Career anxiety about AI replacing junior-to-mid roles
- posts_analysed: 46
- confidence: 0.75

## 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: 42
- authenticity_basis: profile_shape_only
- credibility_score: 42
- 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
- [youtube_dan.mobile.developer#b6767058] Making a “viral app” vs. Going where the money already is (https://www.youtube.com/@dan.mobile.developer)
- [youtube_dan.mobile.developer#f5a50808] If Netflix interviewed Developers in 2026 🧑‍💻🎬
- [youtube_dan.mobile.developer#8ab4ad47] Programming in Swift vs Kotlin vs …
- [youtube_dan.mobile.developer#be386b23] Software Developers in 2026
- [youtube_dan.mobile.developer#6ef3a1be] Using Fable 5 for real app development work
- [youtube_dan.mobile.developer#e7fe5c53] When a Mobile Dev bumps into his Backeng colleague
- [youtube_dan.mobile.developer#9c9d0511] Senior Developers in 2026
- [youtube_dan.mobile.developer#1f05a4cd] How to stop scrolling while AI is coding on your app

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

- audience.description: source_type=ai_inferred, confidence=0.75, freshness_days=79, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.75, freshness_days=79, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.75, 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=88, 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=88, 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=88, method=platform_profile

## Freshness
- profile_checked_days_ago: 88
- content_analysed_days_ago: 79
- audience_updated_days_ago: 79

## AI retrieval
- indexing_requests: 7
- 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=youtube_dan.mobile.developer
- Request removal: https://koinonlink.com/claim?k=youtube_dan.mobile.developer
- Terms: https://koinonlink.com/for-ai