# AICamp (@aicampai) on x

- id: koinon:creator:x_aicampai
- url: https://koinonlink.com/kol/x/aicampai
- schema_version: 1.4

## Identity
- platform: x
- handle: aicampai
- platform_url: https://twitter.com/aicampai
- website: https://www.aicamp.ai
- country: United States
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 1850
- following: 228
- posts_total: 2534
- posts_observed: 12
- posts_per_day: 0.716
- account_age_days: 3540
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.0027
- best_post_interactions: 5
- 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: 0.9
- category_source: derived_from_recent_content
- topics: Enterprise AI, LLMs and LTMs comparison, Agentic AI in production, AWS AI partnerships, Developer-focused AI learning
- bio: Empower every developer to learn and practice AI from anywhere at any time.

## Audience (inferred)
- status: present
- description: Developers learning and practicing AI, especially those interested in enterprise AI, LLMs, and production-ready agentic systems
- roles: dev
- seniority: practitioner
- pain_points: Struggling to move AI prototypes from code to production in enterprise environments, Finding it hard to choose between LLMs and LTMs for structured data use cases, Lacking hands-on opportunities to practice enterprise AI in real-world settings
- posts_analysed: 2
- 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: 72
- authenticity_basis: engagement_observed
- credibility_score: 72
- 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_aicampai#2de3ebac] 🧠 Enterprise AI (SF) – LTMs vs. LLMs: The Structured Data Reality Check, by @LTMpredict Join us today, 7/28 in SF, for an evening that cuts through the generative AI hype and gets real about structured enterprise data. All star speakers line up: @GarneloMarta @Alexandre Gerbeaux (https://twitter.com/aicampai/status/2067371235168895319)
- [x_aicampai#27a3572b] 5th Edition. San Francisco. June 24. The AWS Agentic AI Partner Showcase is back – and this time, we're going from code to production. Join @awscloud @AWS_Partners : @saviynt , @DeepgramAI , @Zendesk & @4Min for live demos and deep dives into building production-ready AI agents o

## 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=80, 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=80, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=119, 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=80, 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=119, 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=119, method=platform_profile

## Freshness
- profile_checked_days_ago: 119
- content_analysed_days_ago: 80
- audience_updated_days_ago: 21

## AI retrieval
- indexing_requests: 12
- 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_aicampai
- Request removal: https://koinonlink.com/claim?k=x_aicampai
- Terms: https://koinonlink.com/for-ai