# Kai Milstein (@0xNotFounder) on x

- id: koinon:creator:x_0xnotfounder
- url: https://koinonlink.com/kol/x/0xNotFounder
- schema_version: 1.4

## Identity
- platform: x
- handle: 0xNotFounder
- platform_url: https://twitter.com/0xNotFounder
- website: https://notpeople.ai/
- country: Portugal
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 1296
- following: 1158
- posts_total: 4624
- posts_observed: 1
- posts_per_day: 5.015
- account_age_days: 922
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00772
- best_post_interactions: 10
- 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 agent limitations in maintenance and evaluation, Klarna AI support case study and its reversal, AI vs human roles in customer operations, Bootstrapped AI × revenue playbooks
- bio: If you reading this - click follow. Entrepreneur. Bootstrapped. 
AI × distribution × revenue. Sharing the playbook.

## Audience (inferred)
- status: present
- description: Bootstrapped entrepreneurs and operators testing AI agents for revenue, distribution and customer support
- roles: automation
- seniority: practitioner
- pain_points: AI agents failing on complex or edge-case customer issues, Overhyped AI replacing humans only to require quiet rehiring later, Difficulty evaluating whether an AI system actually works long-term, Maintaining and monitoring agent performance after initial build
- posts_analysed: 3
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.8
- promotion_intent: 0.9
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 47
- authenticity_basis: engagement_observed
- credibility_score: 47
- flagged_for_review: false
- koinon_bd_grade: B — 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_0xnotfounder#312f5f3c] The whole thing is in the word "maintaining." An agent can build it. An agent cannot tell you whether it works. Those are two different problems and only one of them got solved. Langchain asked 1,300+ teams building agents. Nearly 89% have observability - they can watch the agent (https://twitter.com/0xNotFounder/status/2070128735622250562)
- [x_0xnotfounder#f29159cd] Klarna is the case study for this number. It said its AI did the work of 700 support agents. 75% of chats, 2.3M conversations in month one. Everyone quoted it as proof the thing worked. Then repeat contact rate climbed. Same customers, same unresolved problem, coming back a secon
- [x_0xnotfounder#768d6cf9] Klarna said their AI was doing the work of 700 support agents. A year later they were quietly hiring humans back. Not because the AI couldn't answer - because it kept

## 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=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=110, 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=110, 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=110, method=platform_profile

## Freshness
- profile_checked_days_ago: 110
- content_analysed_days_ago: 80
- audience_updated_days_ago: 76

## 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_0xnotfounder
- Request removal: https://koinonlink.com/claim?k=x_0xnotfounder
- Terms: https://koinonlink.com/for-ai