# Attilio (@Attilio_D) on x

- id: koinon:creator:x_attilio_d
- url: https://koinonlink.com/kol/x/Attilio_D
- schema_version: 1.4

## Identity
- platform: x
- handle: Attilio_D
- platform_url: https://twitter.com/Attilio_D
- website: http://livinginthefuture.ai
- country: Canada
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 1101
- following: 710
- posts_total: 3247
- posts_observed: 1
- posts_per_day: 0.593
- account_age_days: 5473
- verified: true
- size_tier: nano

## Engagement
- status: not_collected
- status_note: Engagement has not been collected for this creator yet. This is a gap in our collection, NOT a statement that the creator has no engagement. Follower count is known, so it is measurable.
- 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: 0.98
- category_source: derived_from_recent_content
- topics: New LLM releases and benchmark results, Agentic AI and model-vs-model training, Open-weight models and pricing implications, Impact of model delays on builders and markets
- bio: I built an AI system that runs this account — real numbers every Monday. Shipping with AI daily. Bullish on Bitcoin. Living in the future — come see.

## Audience (inferred)
- status: present
- description: AI builders and developers actively shipping agentic systems and evaluating new LLMs
- roles: automation
- seniority: practitioner
- pain_points: Rapid model releases making it hard to pick the right base model for agents, Uncertainty around benchmark reliability and real-world coding/agent performance, Need for large context and open weights to build long-document or production agents cheaply
- posts_analysed: 4
- 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: 51
- authenticity_basis: profile_shape_only
- credibility_score: 51
- 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_attilio_d#f2f3ea0b] The self-improvement flywheel isn't a theory anymore. Kimi K3, Grok 4.5, GPT-Red, Inkling: models training and attacking other models, all in one week. For builders: human red-team cycles just became optional overhead. What's replacing that line item on your roadmap? (https://twitter.com/Attilio_D/status/2073138486543016337)
- [x_attilio_d#c31abd29] Breaking: Google reportedly pushed Gemini 3.5 Pro back several months — training data reportedly failed coding benchmarks, $GOOG down ~4.4%. If you built a roadmap around it, your timeline just moved. What's your Plan B?
- [x_attilio_d#d6f91e58] Breaking: xAI just shipped Grok 4.5. Coding benchmarks reportedly strong — if it holds, builders get another serious alternative to GPT-4o and Claude for agentic work. I'm testing it now. What's your first use case?
- [x_attilio_d#b184d59c] Breaking: Kimi K3 — reportedly 2.8T params, 1M context, open weights (Modified MIT), ~$3/$15 per M tokens. Largest open model yet. Long-doc agents just got a lot cheaper to run. What woul

## 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=67, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=67, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=67, 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=111, 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=0.25, 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=111, 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=111, method=platform_profile

## Freshness
- profile_checked_days_ago: 111
- content_analysed_days_ago: 80
- audience_updated_days_ago: 67

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