Use when reducing model size, improving inference speed, or deploying to edge devices - covers quantization, pruning, knowledge distillation, ONNX export, and TensorRT optimizationUse when ", " mentioned.
Infrastructure and practices for reproducible computational research. Covers environment management, data versioning, code documentation, and sharing protocols that enable others to reproduce your...
Formal Design of Experiments (DOE) methodology for maximizing information from experiments while minimizing resources. Covers factorial designs, blocking, randomization, and optimal design...
Use when reviewing contracts, extracting key terms, identifying risks, or building contract analysis tools - covers NLP approaches, clause identification, and risk scoringUse when ", " mentioned.
Use when implementing RL algorithms, training agents with rewards, or aligning LLMs with human feedback - covers policy gradients, PPO, Q-learning, RLHF, and GRPOUse when ", " mentioned.
Use when implementing GDPR compliance, handling data subject requests, conducting DPIAs, managing consent, or responding to data breaches - covers all key GDPR requirementsUse when ", " mentioned.
Use when implementing policy-as-code, continuous compliance monitoring, automated evidence collection, or audit-ready systems requiring SOC2/ISO/PCI/HIPAA complianceUse when ", " mentioned.
Patterns for embedded software development including real-time systems, memory management, hardware abstraction, interrupt handling, and debugging techniques for resource-constrained environments....
Patterns for designing, building, and operating microservices architectures. Covers service decomposition, inter-service communication, resilience patterns, data consistency, and observability in...
Use when pricing options, calculating Greeks, implementing exotic derivatives, or building pricing engines - covers Black-Scholes, binomial trees, Monte Carlo, and QuantLib integrationUse when ",...
Patterns for building reliable background job processing systems. Covers message queues, worker pools, retries, dead letter handling, and async workflow orchestration. Use when ", " mentioned.
Use when building DeFi protocols, implementing AMMs, yield farming strategies, or integrating with Ethereum/L2s - covers smart contract patterns, liquidity pools, and security considerationsUse...
Patterns for building robust, reproducible genomics analysis pipelines. Covers workflow managers, NGS data processing, variant calling, RNA-seq, and common bioinformatics pitfalls. Use when ", " mentioned.
Use when adapting large language models to specific tasks, domains, or behaviors - covers LoRA, QLoRA, PEFT, instruction tuning, and full fine-tuning strategiesUse when ", " mentioned.
Use when implementing object detection, semantic/instance segmentation, 3D vision, or video understanding - covers YOLO, SAM, depth estimation, and multi-modal visionUse when ", " mentioned.
Use when designing multi-tenant SaaS architectures, implementing tenant isolation, data partitioning strategies, or building billing/metering systems - covers pooled, siloed, and hybrid modelsUse...
Use when automating model architecture design, optimizing hyperparameters, or exploring neural network configurations - covers NAS algorithms, search spaces, Bayesian optimization, and AutoML...
Use when building VaR models, stress testing portfolios, Monte Carlo simulations, or implementing enterprise risk management - covers market risk, credit risk, and operational risk frameworksUse...
Use when designing enterprise systems, applying TOGAF framework, creating capability maps, implementing domain-driven design, or planning technology transformations - covers ADM phases,...
Use when designing disaster recovery strategies, defining RPO/RTO targets, implementing failover mechanisms, or conducting chaos engineering tests - covers active-active, pilot light, and backup...