# Marcel Velica (@MarcelVelica) on x

- id: koinon:creator:x_marcelvelica
- url: https://koinonlink.com/kol/x/MarcelVelica
- schema_version: 1.4

## Identity
- platform: x
- handle: MarcelVelica
- platform_url: https://twitter.com/MarcelVelica
- website: https://www.linkedin.com/in/marcelvelica
- country: United States
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 21079
- following: 23017
- posts_total: 10841
- posts_observed: 2
- posts_per_day: 6.419
- account_age_days: 1689
- verified: true
- size_tier: koc

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00256
- best_post_interactions: 54
- 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: security
- category_confidence: 0.9
- category_source: derived_from_recent_content
- topics: AI agent risks, Enterprise AI security, AI workflow automation, Digital risk management, AI governance, AI operational safety
- bio: Cybersecurity & AI Expert | Trusted by global businesses | 50K+ LinkedIn followers | Strategy, Risk Management & Digital Protection

## Audience (inferred)
- status: present
- description: Cybersecurity and AI strategy professionals in enterprise environments, especially those responsible for risk management and digital protection in global organizations
- roles: ads
- seniority: practitioner
- pain_points: Uncontrolled AI agent behavior leading to unintended system access or data exposure, Lack of visibility into AI workflows across business systems, Difficulty in auditing or monitoring AI agents operating during off-hours, Inadequate risk frameworks for AI agents with broad system privileges
- posts_analysed: 10
- confidence: 0.4

## 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: 71
- authenticity_basis: engagement_observed
- credibility_score: 71
- 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_marcelvelica#f33c3b7a] Most AI agent failures will not start with a jailbreak. (https://twitter.com/MarcelVelica)
- [x_marcelvelica#55ccf05c] They will start with a normal request.
- [x_marcelvelica#12be39b8] An agent opens a customer record.
- [x_marcelvelica#331d36a0] Checks internal documents.
- [x_marcelvelica#8da89cf5] Triggers a workflow.
- [x_marcelvelica#09e75367] Builds a report.
- [x_marcelvelica#2eb4a418] Touches systems across the business.
- [x_marcelvelica#bcec36be] All while the team is asleep.

## 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=21, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=21, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=21, 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=112, 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=112, 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=112, method=platform_profile

## Freshness
- profile_checked_days_ago: 112
- content_analysed_days_ago: 79
- audience_updated_days_ago: 21

## AI retrieval
- indexing_requests: 11
- 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_marcelvelica
- Request removal: https://koinonlink.com/claim?k=x_marcelvelica
- Terms: https://koinonlink.com/for-ai