# shmidt (@shmidtqq) on x

- id: koinon:creator:x_shmidtqq
- url: https://koinonlink.com/kol/x/shmidtqq
- schema_version: 1.4

## Identity
- platform: x
- handle: shmidtqq
- platform_url: https://twitter.com/shmidtqq
- website: https://t.me/shmidtai
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 9360
- following: 549
- posts_total: 17399
- posts_observed: 54
- posts_per_day: 9.461
- account_age_days: 1839
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.04113
- best_post_interactions: 385
- 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: AI prompt engineering for company operations, Splitting tasks into LLM-based virtual employees, Prediction markets trading and forecasting profits
- bio: predicting the future with code / ai × prediction markets / tg: shmidtqq

## Audience (inferred)
- status: present
- description: AI practitioners and prediction market traders focused on using LLMs for business automation and forecasting
- roles: automation
- seniority: practitioner
- pain_points: Scaling multi-step business operations without hiring staff, Crafting effective prompts that reliably act as multiple employees, Profiting from forecasts without accurate prediction methods
- posts_analysed: 2
- 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: 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_shmidtqq#b3680652] ONE GIANT PROMPT IS AN INTERN RUNNING YOUR ENTIRE COMPANY Split it into steps and you get five employees. Free, in Claude and ChatGPT. Instead of "make me content from trends" you hand it the graph: find trending topics on Reddit rank by engagement remove duplicates 5 hooks per t (https://twitter.com/shmidtqq)
- [x_shmidtqq#8bc74d96] $71,210 on the weather forecast. He never guessed a single day. 202 trades since October 2024. $71,210 in profit, $48,300 still in play, best single ticket paid $10,283. One calculation sold into eight markets at once. February: $32,476 -> $42,759. January: $19,912 -> $28,

## 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: 9
- 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_shmidtqq
- Request removal: https://koinonlink.com/claim?k=x_shmidtqq
- Terms: https://koinonlink.com/for-ai