Agent
Tracks A/B tests, feature flags, and experiments for data-driven development decisions.
Agent
Tracks A/B tests, feature flags, and experiments for data-driven development decisions.
Agent
Master SQL optimization, query tuning, and database design across cloud platforms. Examples: Context: User has slow queries user: "This query is taking 30 seconds on a 10M row table" assistant: "I'll use the sql-expert to analyze the query plan and identify optimization opportunities." Query optimization requires…
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Use when "Dask", "parallel computing", "distributed computing", "larger than memory", or asking about "parallel pandas", "parallel numpy", "out-of-core", "multi-file processing", "cluster computing", "lazy evaluation dataframe".
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Use when "data pipelines", "ETL", "data warehousing", "data lakes", or asking about "Airflow", "Spark", "dbt", "Snowflake", "BigQuery", "data modeling".
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Use when "statistical modeling", "A/B testing", "experiment design", "causal inference", "predictive modeling", or asking about "hypothesis testing", "feature engineering", "data analysis", "pandas", "scikit-learn".
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Use when "experiment tracking", "MLflow", "Weights & Biases", "wandb", "model registry", "hyperparameter logging", "ML experiments", "training metrics".
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Use when "GeoPandas", "geospatial", "GIS", "shapefile", "GeoJSON", or asking about "spatial analysis", "coordinate transformation", "spatial join", "choropleth map", "buffer analysis", "geographic data", "map visualization".
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Use when "tokenizers", "HuggingFace tokenizer", "BPE", "WordPiece", or asking about "train tokenizer", "custom vocabulary", "tokenization", "subword", "fast tokenizer", "encode text".
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Use when "LLM inference", "serving LLM", "vLLM", "llama.cpp", "GGUF", "text generation", "model serving", "inference optimization", "KV cache", "continuous batching", "speculative decoding", "local LLM", "CPU inference".
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Use when "training LLM", "finetuning", "RLHF", "distributed training", "DeepSpeed", "Accelerate", "PyTorch Lightning", "Ray Train", "TRL", "Unsloth", "LoRA training", "flash attention", "gradient checkpointing".
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Use when "deploying ML models", "MLOps", "model serving", "feature stores", "model monitoring", or asking about "PyTorch deployment", "TensorFlow production", "RAG systems", "LLM integration", "ML infrastructure".
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Use when "Modal", "serverless GPU", "cloud GPU", "deploy ML model", or asking about "serverless containers", "GPU compute", "batch processing", "scheduled jobs", "autoscaling ML".
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Use when "CLIP", "Whisper", "Stable Diffusion", "SDXL", "speech-to-text", "text-to-image", "image generation", "transcription", "zero-shot classification", "image-text similarity", "inpainting", "ControlNet".