A Comprehensive Guide for Generative AI, Agentic AI, Multimodal AI, Physical AI Interviews. Proven Formula for multiple FAANG offers and more
This report summarizes scanner evidence for alirezadir/AIMLInterviews, a Jupyter Notebook project with 9,807 GitHub stars. SynthScan examined 15,354 lines of code across 138 source files, recording 108 pattern matches distributed across 5 syntactic categories. The legacy adjusted pattern signal is 9.6 (Moderate pattern signal); it is not an authorship estimate.
Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain, over-engineering, and review-effort vectors when available. These are prompts for human verification, not probabilities, security findings, or measured maintenance costs.
Use each vector to guide manual verification of the underlying findings.
Can maintainers explain intent, assumptions, and trade-offs? 63 finding(s).
Are imports declared and package/API names verified? 44 finding(s).
Are wrappers, guards, and repeated structures necessary? 50 finding(s).
Which changes need focused human review? 108 finding(s).
This chart tracks the legacy adjusted pattern score across scan runs. Changes can reflect source changes, scan coverage, or detector/scoring versions; they do not measure AI adoption or prove that a team refactored code. Compare runs only when their scoring versions are compatible. The dashed line tracks the raw pattern-hit count.
Groups findings by configured severity weight. Severity is not a confidence estimate, security rating, or proof that a package is missing. Verify imports against the project's manifests and inspect each finding in its local design context.
This horizontal bar chart shows where configured pattern scores accumulate across directories. Treat the bars as locations to inspect, not as evidence of authorship or code quality. Use the file-level findings to decide whether a directory needs a focused ownership, dependency, complexity, or review check.
The scanner identified 108 distinct pattern matches across 5 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a detector match to inspect in context. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the configured finding weight (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — legacy comment-context matches receive a ×1.5 score weight. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier under the legacy scoring model.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | cn/src/MLC/pytorch-ml-coding.md | 725 | def linear_regression_gradients(x, y, weight, bias): | CODE |
| LOW | tests/test_sync_translations.py | 14 | def test_root_and_behavior_overrides(self) -> None: | CODE |
| LOW | tests/test_sync_translations.py | 34 | def test_default_mapping_mirrors_source_tree(self) -> None: | CODE |
| LOW | tests/test_sync_translations.py | 46 | def test_only_selects_added_or_modified_english_markdown(self, run_git) -> None: | CODE |
| LOW | tests/test_sync_translations.py | 61 | def test_deletion_requires_manual_review(self, run_git) -> None: | CODE |
| LOW | tests/test_sync_translations.py | 68 | def test_valid_chinese_structure_passes(self) -> None: | CODE |
| LOW⚡ | tests/test_sync_translations.py | 79 | def test_missing_url_and_heading_are_reported(self) -> None: | CODE |
| LOW⚡ | tests/test_sync_translations.py | 86 | def test_farsi_preferred_terms_are_enforced_in_prose_only(self) -> None: | CODE |
| LOW⚡ | tests/test_sync_translations.py | 92 | def test_future_local_path_is_accepted(self) -> None: | CODE |
| LOW⚡ | tests/test_sync_translations.py | 100 | def test_broken_and_escaping_links_are_rejected(self) -> None: | CODE |
| LOW⚡ | tests/test_sync_translations.py | 110 | def test_response_text_is_extracted_from_message_items(self) -> None: | CODE |
| LOW | tests/test_sync_translations.py | 122 | def test_incomplete_response_is_rejected(self) -> None: | CODE |
| LOW | tests/test_sync_translations.py | 128 | def test_markdown_wrapper_is_removed(self) -> None: | CODE |
| LOW | MCP/src/catalog.ts | 258 | function shouldTreatNumberedItemAsProblem( | CODE |
| LOW | src/MLC/pytorch-ml-coding.md | 725 | def linear_regression_gradients(x, y, weight, bias): | CODE |
| LOW⚡ | src/MLC/tests/test_problem_answers.py | 41 | def test_softmax_and_cross_entropy_are_stable(self): | CODE |
| LOW⚡ | src/MLC/tests/test_problem_answers.py | 47 | def test_linear_regression_recovers_line(self): | CODE |
| LOW⚡ | src/MLC/tests/test_problem_answers.py | 54 | def test_logistic_regression_separates_simple_data(self): | CODE |
| LOW⚡ | src/MLC/tests/test_classic_additional.py | 49 | def test_multinomial_naive_bayes(self): | CODE |
| LOW⚡ | src/MLC/tests/test_classic_additional.py | 56 | def test_matrix_factorization_reconstructs_observations(self): | CODE |
| LOW⚡ | src/MLC/tests/test_classic_additional.py | 63 | def test_gradient_boosting_residual_stump(self): | CODE |
| LOW⚡ | src/MLC/tests/test_classic_additional.py | 68 | def test_dataset_splits_are_disjoint_and_complete(self): | CODE |
| LOW⚡ | src/MLC/tests/test_classic_additional.py | 75 | def test_standardizer_reuses_training_statistics(self): | CODE |
| LOW⚡ | src/MLC/tests/test_classic_additional.py | 80 | def test_missing_and_unseen_values(self): | CODE |
| LOW | src/MLC/tests/test_classic_additional.py | 92 | def test_streaming_weighted_mean(self): | CODE |
| LOW⚡ | src/MLC/tests/test_language_and_genai.py | 36 | def test_causal_attention_mask(self): | CODE |
| LOW⚡ | src/MLC/tests/test_language_and_genai.py | 40 | def test_sinusoidal_position_encoding(self): | CODE |
| LOW⚡ | src/MLC/tests/test_language_and_genai.py | 46 | def test_top_k_top_p_filtering(self): | CODE |
| LOW⚡ | src/MLC/tests/test_language_and_genai.py | 67 | def test_contrastive_loss_prefers_matching_pairs(self): | CODE |
| LOW⚡ | src/MLC/tests/test_language_and_genai.py | 77 | def test_dpo_loss_rewards_policy_preference(self): | CODE |
| LOW⚡ | src/MLC/tests/test_language_and_genai.py | 82 | def test_classifier_free_guidance(self): | CODE |
| LOW⚡ | src/MLC/tests/test_agentic_ai.py | 26 | def test_tool_argument_validation(self): | CODE |
| LOW⚡ | src/MLC/tests/test_agentic_ai.py | 36 | def test_tool_registry_permission_boundary(self): | CODE |
| LOW⚡ | src/MLC/tests/test_agentic_ai.py | 44 | def test_planner_executor_stops_on_failure(self): | CODE |
| LOW⚡ | src/MLC/tests/test_agentic_ai.py | 54 | def test_retry_and_idempotency(self): | CODE |
| LOW | src/MLC/tests/test_agentic_ai.py | 79 | def test_sliding_window_memory_pins_system_message(self): | CODE |
| LOW | …oblems/language_models/scaled_dot_product_attention.py | 14 | def scaled_dot_product_attention( | CODE |
| LOW | …oblems/language_models/sinusoidal_position_encoding.py | 12 | def sinusoidal_position_encoding(length: int, width: int) -> np.ndarray: | CODE |
| LOW | src/MLC/problems/classic_ml/sampling_strategies.py | 32 | def stratified_sample_indices( | CODE |
| LOW | src/MLC/problems/classic_ml/softmax_cross_entropy.py | 22 | def cross_entropy_from_logits(logits: np.ndarray, targets: np.ndarray) -> float: | CODE |
| LOW | src/MLC/problems/classic_ml/dataset_split.py | 12 | def train_validation_test_indices( | CODE |
| LOW | src/MLC/problems/classic_ml/dataset_split.py | 35 | def stratified_train_validation_test_indices( | CODE |
| LOW | src/MLC/problems/classic_ml/binary_metrics_roc_auc.py | 12 | def binary_classification_metrics( | CODE |
| LOW | src/MLC/problems/classic_ml/multinomial_naive_bayes.py | 14 | def fit_multinomial_naive_bayes( | CODE |
| LOW | src/MLC/problems/classic_ml/multinomial_naive_bayes.py | 39 | def predict_multinomial_naive_bayes( | CODE |
| LOW | src/MLC/problems/classic_ml/logistic_regression.py | 12 | def logistic_regression_gradient_descent( | CODE |
| LOW | src/MLC/problems/classic_ml/pca.py | 12 | def principal_component_analysis( | CODE |
| LOW | src/MLC/problems/classic_ml/linear_regression.py | 12 | def linear_regression_gradient_descent( | CODE |
| LOW | src/MLC/problems/genai/contrastive_loss.py | 12 | def symmetric_contrastive_loss( | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_sync_translations.py | 1 | CODE | |
| LOW | scripts/sync_translations.py | 8 | CODE | |
| LOW | src/MLC/tests/test_problem_answers.py | 3 | CODE | |
| LOW | src/MLC/tests/test_classic_additional.py | 3 | CODE | |
| LOW | src/MLC/tests/test_language_and_genai.py | 3 | CODE | |
| LOW | src/MLC/tests/test_agentic_ai.py | 3 | CODE | |
| LOW | src/MLC/problems/language_models/padded_batches.py | 7 | CODE | |
| LOW | …/MLC/problems/language_models/causal_attention_mask.py | 7 | CODE | |
| LOW | …c/MLC/problems/language_models/top_k_top_p_sampling.py | 7 | CODE | |
| LOW | src/MLC/problems/language_models/kv_cache.py | 7 | CODE | |
| LOW | …oblems/language_models/scaled_dot_product_attention.py | 7 | CODE | |
| LOW | src/MLC/problems/language_models/byte_pair_encoding.py | 8 | CODE | |
| LOW | src/MLC/problems/language_models/tfidf.py | 7 | CODE | |
| LOW | …oblems/language_models/sinusoidal_position_encoding.py | 7 | CODE | |
| LOW | src/MLC/problems/agentic_ai/bounded_agent_loop.py | 8 | CODE | |
| LOW | src/MLC/problems/agentic_ai/tool_registry.py | 7 | CODE | |
| LOW | src/MLC/problems/agentic_ai/planner_executor.py | 8 | CODE | |
| LOW | src/MLC/problems/agentic_ai/tool_argument_validation.py | 8 | CODE | |
| LOW | src/MLC/problems/agentic_ai/sliding_window_memory.py | 8 | CODE | |
| LOW | src/MLC/problems/agentic_ai/retry_with_idempotency.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/streaming_weighted_mean.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/decision_tree_split.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/sampling_strategies.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/softmax_cross_entropy.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/dataset_split.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/feature_standardization.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/binary_metrics_roc_auc.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/gradient_boosting_step.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/kmeans.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/conv2d.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/multinomial_naive_bayes.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/logistic_regression.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/pca.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/reservoir_sampling.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/matrix_factorization.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/linear_regression.py | 7 | CODE | |
| LOW | …c/MLC/problems/classic_ml/categorical_preprocessing.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/multiclass_metrics.py | 7 | CODE | |
| LOW | src/MLC/problems/classic_ml/knn.py | 7 | CODE | |
| LOW | src/MLC/problems/genai/lora_linear.py | 7 | CODE | |
| LOW | src/MLC/problems/genai/dpo_loss.py | 7 | CODE | |
| LOW | src/MLC/problems/genai/classifier_free_guidance.py | 7 | CODE | |
| LOW | src/MLC/problems/genai/contrastive_loss.py | 7 | CODE | |
| LOW | src/MLC/problems/genai/rag_retrieval.py | 8 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM⚡ | cn/src/genai-resources.md | 15 | ### RAG 与生产系统 | COMMENT |
| MEDIUM⚡ | cn/src/genai-resources.md | 23 | - [Agentic AI Systems](https://www.educative.io/courses/agentic-ai-systems) - 介绍面向自主工作流的智能体架构和系统设计决策。 | CODE |
| MEDIUM⚡ | cn/src/genai-resources.md | 24 | - [Agentic Design Patterns](https://www.educative.io/courses/agentic-design-patterns) - 讲解工具、检索、记忆、路由和评估器等智能体构建模块。 | CODE |
| MEDIUM | scripts/sync_translations.py | 510 | source = "# Retrieval\n\nUse `RAG` with [the guide](https://example.com/guide)." | STRING |
| MEDIUM⚡ | fa/src/genai-resources.md | 15 | ### RAG و سیستمهای production | COMMENT |
| MEDIUM⚡ | fa/src/genai-resources.md | 23 | - [سیستمهای هوش مصنوعی عاملمحور](https://www.educative.io/courses/agentic-ai-systems) — معماری عامل و تصمیمهای طراحی | CODE |
| MEDIUM⚡ | fa/src/genai-resources.md | 24 | - [الگوهای طراحی عاملمحور](https://www.educative.io/courses/agentic-design-patterns) — ابزار، retrieval، حافظه، routing | CODE |
| MEDIUM⚡ | src/genai-resources.md | 15 | ### RAG and production systems | COMMENT |
| MEDIUM⚡ | src/genai-resources.md | 21 | ### Agents and agentic systems | COMMENT |
| MEDIUM⚡ | src/genai-resources.md | 23 | - [Agentic AI Systems](https://www.educative.io/courses/agentic-ai-systems) - Introduces agent architecture and system-d | CODE |
| MEDIUM⚡ | src/genai-resources.md | 24 | - [Agentic Design Patterns](https://www.educative.io/courses/agentic-design-patterns) - Covers tools, retrieval, memory, | CODE |
| MEDIUM | src/genai-resources.md | 35 | - [Agentic AI Systems](https://github.com/alirezadir/Agentic-AI-Systems) - System-design notes, implementation examples, | CODE |
| MEDIUM | src/MLC/ml-coding.md | 105 | - [Agentic AI Systems interview prep](https://github.com/alirezadir/Agentic-AI-Systems/tree/main/06_interview_prep) cove | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | scripts/sync_translations.py | 539 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/MLC/problems/agentic_ai/planner_executor.py | 36 | except Exception as error: # The boundary turns tool errors into trace data. | CODE |