# Michel Lieben (@MichLieben) on x

- id: koinon:creator:x_michlieben
- url: https://koinonlink.com/kol/x/MichLieben
- schema_version: 1.4

## Identity
- platform: x
- handle: MichLieben
- platform_url: https://twitter.com/MichLieben
- website: http://youtube.com/@MichLieben/
- country: Spain
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 11959
- following: 712
- posts_total: 3415
- posts_observed: 20
- posts_per_day: 0.639
- account_age_days: 5347
- verified: true
- size_tier: koc

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.03512
- best_post_interactions: 420
- measurement_source: x_post_interactions
- measurement_formula: interactions on one post — likes, or likes + reposts + replies depending on the discovery path (the two are not distinguishable in the stored data)
- comparable_pool: peak_interactions
- status_note: We have only the single best observed post, so no mean exists. peak_post_engagement_rate is an UPPER BOUND, systematically higher than an average — never compare it against an average rate.
- 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: martech
- category_confidence: 0.9
- category_source: derived_from_recent_content
- topics: AI and code automation for paid ads, Ad-ops efficiency and margin protection, Claude Code skills replacing ad managers, Python scripts and strategy files for client campaigns, Agency ownership of ad technology
- bio: CEO at https://t.co/YKizWZdxjK ($7M ARR). Helping GTM teams scale with AI & Tech: https://t.co/Vooe1yaqqx.

Connect:
https://t.co/VCBGhgKTW7
https://t.co/PhINKB8p78

## Audience (inferred)
- status: present
- description: Growth and ad-ops practitioners at agencies and GTM teams running paid campaigns who want to automate ad management with AI and code
- roles: ads
- seniority: practitioner
- pain_points: Manually logging into multiple ad platforms daily, Losing margin to platform fees and manual clicks instead of owning custom ops, Spending hundreds of hours on repetitive campaign work that could be scripted, Scaling ad spend without reliable automation tools or internal tech
- posts_analysed: 4
- confidence: 0.4

## 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: 87
- authenticity_basis: engagement_observed
- credibility_score: 87
- flagged_for_review: false
- koinon_bd_grade: A — 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
- [x_michlieben#030f2683] Our Head of Growth runs $300K+/mo in paid ads without opening a single ad manager. Three platforms, one terminal, 12 custom Claude Code skills. (https://twitter.com/MichLieben)
- [x_michlieben#8d39c119] 200+ hours of work off real client campaigns. Some clearing 4X ROAS on $1M+ spent. 40+ strategy files, 39 Python scripts hitting the platforms directly.
- [x_michlieben#6f33dc13] My bet: the agency that codes its ad-ops owns the margin everyone else burns in clicks.
- [x_michlieben#1f2f71a3] The whole th

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

- audience.description: source_type=ai_inferred, confidence=0.4, freshness_days=67, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=67, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=67, 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=108, 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=0.5, 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=108, 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=108, method=platform_profile

## Freshness
- profile_checked_days_ago: 108
- content_analysed_days_ago: 79
- audience_updated_days_ago: 67

## AI retrieval
- indexing_requests: 10
- 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=x_michlieben
- Request removal: https://koinonlink.com/claim?k=x_michlieben
- Terms: https://koinonlink.com/for-ai