RRepoGEO

REPOGEO REPORT · LITE

alexeygrigorev/ai-engineering-field-guide

Default branch main · commit 9757d25b · scanned 5/9/2026, 6:42:30 AM

GitHub: 3,425 stars · 307 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface alexeygrigorev/ai-engineering-field-guide, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add specific topics to clarify the repo's category

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    ai-engineering, career-guide, interview-prep, job-market, skills-analysis, mlops-career, data-science-career, field-guide
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Add a LICENSE file (e.g., MIT License) to the root of the repository.
  • mediumhomepage#3
    Add a homepage URL to the repo's 'About' section

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    Add a homepage URL to the repo's 'About' section, linking to a relevant project page or the author's newsletter (e.g., 'https://alexeygrigorev.com/newsletter').

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface alexeygrigorev/ai-engineering-field-guide
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch · recommended 1×
  2. TensorFlow · recommended 1×
  3. Keras · recommended 1×
  4. NumPy · recommended 1×
  5. Pandas · recommended 1×
  • CATEGORY QUERY
    What are the essential skills and interview questions for an AI engineering role?
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. TensorFlow
    3. Keras
    4. NumPy
    5. Pandas
    6. Git
    7. Flask
    8. FastAPI
    9. Django
    10. PostgreSQL
    11. MySQL
    12. MongoDB
    13. Cassandra
    14. AWS SageMaker
    15. Google Cloud AI Platform
    16. Azure Machine Learning
    17. Docker
    18. Apache Airflow
    19. Kubeflow

    AI recommended 19 alternatives but never named alexeygrigorev/ai-engineering-field-guide. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find a comprehensive guide to AI engineering career paths and responsibilities?
    you: not recommended
    AI recommended (in order):
    1. LinkedIn Learning
    2. Coursera
    3. deeplearning.ai
    4. Google Cloud
    5. Kaggle Learn
    6. Glassdoor
    7. LinkedIn Jobs
    8. Indeed
    9. O'Reilly Media
    10. Towards Data Science
    11. Medium
    12. Google

    AI recommended 12 alternatives but never named alexeygrigorev/ai-engineering-field-guide. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of alexeygrigorev/ai-engineering-field-guide?
    pass
    AI did not name alexeygrigorev/ai-engineering-field-guide — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts alexeygrigorev/ai-engineering-field-guide in production, what risks or prerequisites should they evaluate first?
    pass
    AI named alexeygrigorev/ai-engineering-field-guide explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo alexeygrigorev/ai-engineering-field-guide solve, and who is the primary audience?
    pass
    AI did not name alexeygrigorev/ai-engineering-field-guide — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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alexeygrigorev/ai-engineering-field-guide — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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