# Deno (@denogrowth) on x

- id: koinon:creator:x_denogrowth
- url: https://koinonlink.com/kol/x/denogrowth
- schema_version: 1.4

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

## Reach
- followers: 2601
- following: 1394
- posts_total: 17420
- posts_observed: 7
- posts_per_day: 4.125
- account_age_days: 4223
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00154
- best_post_interactions: 4
- 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: ChatGPT/model mention dynamics, AI compliance and liability allocation, large open-weight models for complex tasks
- bio: i build AI systems for growth + distribution. sharing what actually works (and what doesn't)

## Audience (inferred)
- status: present
- description: AI engineers and technical builders focused on growth/distribution systems and large model deployment
- roles: dev
- seniority: practitioner
- pain_points: sudden brand visibility drops from upstream model changes, unclear liability split between foundation labs and downstream products, achieving reliable performance on multi-step long-horizon AI workflows
- posts_analysed: 3
- 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: 61
- authenticity_basis: engagement_observed
- credibility_score: 61
- 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_denogrowth#a3552cd4] your brand's mentions inside chatgpt can fall without you shipping a single change. a new default model means new weights, and the associations from the old one do not carry over. it behaves like a search ranking update with no announcement and no rank tracker. (https://twitter.com/denogrowth/status/2058055304294617543)
- [x_denogrowth#c62d3026] who actually carries this compliance load, the lab or the product built on top of it? mostly the lab. the obligations attach to whoever places the general purpose model on the market. the part worth knowing: modify a model substantially enough and you can become the provider your
- [x_denogrowth#5fc66800] 2.4 trillion parameters, open weights, built for long-horizon tasks. > long-horizon means jobs that run hundreds of steps, not one prompt > at 99% reliability per step, a 200 step task still fails about 87% of the time > that math is why agents ace benchmarks and fall apart on re

## 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=81, 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=81, 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=81, 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: 81
- 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_denogrowth
- Request removal: https://koinonlink.com/claim?k=x_denogrowth
- Terms: https://koinonlink.com/for-ai