# John Rice (@hello_code_) on x

- id: koinon:creator:x_hello_code_
- url: https://koinonlink.com/kol/x/hello_code_
- schema_version: 1.4

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

## Reach
- followers: 1165
- following: 650
- posts_total: 4370
- posts_observed: 1
- posts_per_day: 3.401
- account_age_days: 1285
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00172
- best_post_interactions: 2
- 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: 0.95
- category_source: derived_from_recent_content
- topics: SEO and organic ranking strategies, AI prompting optimization, Startup user acquisition tactics, Google and AI's impact on traffic distribution

## Audience (inferred)
- status: present
- description: Startup founders and growth hackers focused on SEO, organic traffic, and AI-driven user acquisition
- roles: seo_geo
- seniority: practitioner
- pain_points: Struggling to rank #1 on Google despite investing in SEO, Finding it hard to get the first 100 users without expensive marketing, Not understanding why competitors are getting more organic visibility than them, Confused about how to effectively prompt AI models like Opus 5 for better coding results
- posts_analysed: 5
- 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: 52
- authenticity_basis: engagement_observed
- credibility_score: 52
- 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_hello_code_#68003e3b] What's the most overrated AI startup right now? (https://twitter.com/hello_code_/status/2069193733640278460)
- [x_hello_code_#4f9d778e] Every startup asks: "How do we rank #1 on Google?" Almost nobody asks: "Why does ChatGPT recommend my competitor?" That question will matter a lot more over the next five years https://t.co/Ha4cp9QNUg
- [x_hello_code_#ba8485c7] Opus 5 isn't bad at coding. Most people are prompting it wrong. The biggest improvements I found came from telling it what not to do. Less narration. Less overthinking. Smaller diffs. Better code. This one prompt made Opus 5 feel much closer to fable Prompt in the comments 👇
- [x_hello_code_#213e8b66] How did you get your first 100 users? One tactic. No fluff.
- [x_hello_code_#d2515403] Google’s AI is eating the traffic it used to send Reddit. Reddit gets paid for its data, but that same data helps AI answer questions without users ever clicking through. Big takeaway: AI visibility is not the same as website traffic. Brands need to track mentions, citations, and

## 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=20, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=20, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=20, 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=122, 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=122, 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=122, method=platform_profile

## Freshness
- profile_checked_days_ago: 122
- content_analysed_days_ago: 80
- audience_updated_days_ago: 20

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