# codebasics (@codebasics) on youtube

- id: koinon:creator:youtube_codebasics
- url: https://koinonlink.com/kol/youtube/codebasics
- schema_version: 1.3

## Identity
- platform: youtube
- handle: codebasics
- platform_url: https://www.youtube.com/@codebasics
- country: United States
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 1550000
- posts_observed: 8
- verified: false
- size_tier: kol

## 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: AI Agent与工具链演进, AI时代软件工程师职业转型, LLM与模型平台对比, AI Engineer技能路线图, Hype vs Reality与实际应用案例
- bio: I am Dhaval Patel, an AI professional with 14 years of experience with big tech companies such as Bloomberg and NVIDIA.

## Audience (inferred)
- status: present
- description: Software engineers and developers, especially those looking to transition into or deepen their expertise in AI, from junior to mid-level technical practitioners
- roles: dev
- seniority: practitioner
- pain_points: Traditional programming skills are rapidly devaluing in the AI era, requiring constant learning of new tools and agent frameworks, Difficulty distinguishing AI hype from real-world value, making it hard to decide which skills to invest in, Confusion around internal company AI adoption tiers, unclear about one's role in the AI transformation, Unclear career paths, unsure about the specific requirements and next steps for an AI Engineer role
- posts_analysed: 48
- confidence: 0.75

## 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: 58
- authenticity_basis: profile_shape_only
- credibility_score: 58
- 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
- [youtube_codebasics#6fae4b1e] This job post is showing up everywhere on freelancing websites (https://www.youtube.com/@codebasics)
- [youtube_codebasics#7decd679] Codebasics AI Day is almost here ⚡
- [youtube_codebasics#bef38e5e] Why Python Dominates AI?
- [youtube_codebasics#ac46419b] What is Large Language Model (LLM)?
- [youtube_codebasics#fa488571] This Is Where Machine Learning Begins
- [youtube_codebasics#03816dc7] What Top AI Companies Really Look For When Hiring
- [youtube_codebasics#8a7415f6] One Line That Changes How Recruiters See You In Interviews
- [youtube_codebasics#ad2ea04f] What a Google DeepMind Lead Really Looks For While Hiring

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.75, freshness_days=35, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.75, freshness_days=35, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.75, freshness_days=35, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=0, 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=0, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=39, 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=0, 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=39, 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=39, method=platform_profile

## Freshness
- profile_checked_days_ago: 39
- content_analysed_days_ago: 0
- audience_updated_days_ago: 35

## AI retrieval
- indexing_requests: 1
- 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=youtube_codebasics
- Request removal: https://koinonlink.com/claim?k=youtube_codebasics
- Terms: https://koinonlink.com/for-ai