# Vikas gupta (@vicky_grok) on x

- id: koinon:creator:x_vicky_grok
- url: https://koinonlink.com/kol/x/vicky_grok
- schema_version: 1.4

## Identity
- platform: x
- handle: vicky_grok
- platform_url: https://twitter.com/vicky_grok
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 9360
- following: 213
- posts_total: 30823
- posts_observed: 35
- posts_per_day: 5.665
- account_age_days: 5441
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.01624
- best_post_interactions: 152
- 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: ai_tools
- category_confidence: 0.95
- category_source: derived_from_recent_content
- topics: AI agents vs workflows, Prompt engineering for Claude, Practical LLM usage tips
- bio: 75K+ Audience on LinkedIn | AI Engineer | Resume Writer | AI Content Creator | AI Enthusiast | Influencer | DM for Promotion

## Audience (inferred)
- status: present
- description: AI engineers, prompt engineers and automation builders interested in agents and advanced LLM usage
- roles: automation
- seniority: practitioner
- pain_points: Deciding when to use agents versus fixed workflows, Getting consistent high-quality results from models like Claude without endless prompt tweaking, Keeping up with practical AI agent patterns and prompting techniques
- posts_analysed: 3
- confidence: 0.4

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

## Quality signals
- authenticity_score: 86
- authenticity_basis: engagement_observed
- credibility_score: 86
- 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_vicky_grok#c3be9521] WORKFLOW WALKS A PATH YOU DREW. AN AGENT DRAWS THE PATH ITSELF. Both take a task and produce an output. The difference is who decides the steps, and what happens when the input surprises you. I made a 24-second animated comparison: 1. Same goal: task in, output out, two drivers 2 (https://twitter.com/vicky_grok)
- [x_vicky_grok#6b720853] https://t.co/cvBaVbYKxU
- [x_vicky_grok#9ae5e032] 15 Ways to Get More from Claude (That Also Make You Better at Prompting) Most people think better AI results come from finding the "perfect prompt." In practice, they come from building better communication habits. The best users consistently provide context

## 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=76, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=77, 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=77, 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=77, 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: 77
- audience_updated_days_ago: 76

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