# Lya | Software Engineer & AI (@codewithlya) on threads

- id: koinon:creator:threads_codewithlya
- url: https://koinonlink.com/kol/threads/codewithlya
- schema_version: 1.4

## Identity
- platform: threads
- handle: codewithlya
- platform_url: https://www.threads.net/@codewithlya
- website: https://github.com/lyasantoscode?fbclid=PAQ0xDSwMO1wpleHRuA2FlbQIxMQABp6pEjaKL0Y6SA6s73WMWCC99chMtrQEZbRap4lZHYA3-qaTehOWZbiUq4QAk_aem_KIE9mHak0J2S5YGIJDj8Jw
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 2245
- posts_observed: 1
- verified: false
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.0343
- best_post_interactions: 77
- measurement_source: threads_post_likes
- measurement_formula: likes on one post (Threads exposes no reply or repost count on this path)
- 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: devtools
- category_confidence: 0.95
- category_source: derived_from_recent_content
- topics: coding motivation, project initiation, AI in software development, statistical thinking for developers, software prototyping, learning through coding
- bio: Hi.
M.Sc. in Computer Science. Exploring AI, programming & tech.
Long live education 🚀🔥📝🎓

## Audience (inferred)
- status: present
- description: Software engineers and tech enthusiasts, primarily early-career developers and computer science students exploring AI and programming
- roles: dev
- seniority: practitioner
- pain_points: Struggling to stay motivated during long coding sessions, Finding it hard to start new projects without clear direction, Difficulty in applying statistical thinking to real-world coding problems
- posts_analysed: 8
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.9
- promotion_intent: 0.6
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 40
- authenticity_basis: engagement_observed
- credibility_score: 40
- flagged_for_review: false
- koinon_bd_grade: C — 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
- [threads_codewithlya#4521a38c] Sharing a fraction of my journey, with my favorite soundtrack in the background. Coding (https://www.threads.com/@codewithlya/post/DaZL9ozDcZl)
- [threads_codewithlya#d763c0dc] @_pikavoice well well well
- [threads_codewithlya#1e6ae596] Tell me what you’re doing today:
- [threads_codewithlya#70eff01e] Vamos codar meu povo... Let's code, everyone! ¡Vamos a programar, gente!
- [threads_codewithlya#85a3e7e1] Back to work Today, Wednesday, July 29, 2026. Continuing the development of a prototype for an upcoming showcase.
- [threads_codewithlya#2a3c49a8] Happy Monday! Have a great week! Coding coding coding....
- [threads_codewithlya#57301853] The beginning of a new project.....
- [threads_codewithlya#ca60b378] 📊 Did You Know? Statistics helps us understand data by identifying patterns, trends, and relationships that might otherwise go unnoticed. From weather forecasting and medical research to artificial intelligence and sports analytics, statistics plays a key role in making informed

## 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=78, 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=78, 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=78, 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: 78
- audience_updated_days_ago: 20

## AI retrieval
- indexing_requests: 11
- 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=threads_codewithlya
- Request removal: https://koinonlink.com/claim?k=threads_codewithlya
- Terms: https://koinonlink.com/for-ai