Formal Design of Experiments (DOE) methodology for maximizing information from experiments while minimizing resources. Covers factorial designs, blocking, randomization, and optimal design...
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 building DeFi protocols, implementing AMMs, yield farming strategies, or integrating with Ethereum/L2s - covers smart contract patterns, liquidity pools, and security considerationsUse...
Patterns for embedded software development including real-time systems, memory management, hardware abstraction, interrupt handling, and debugging techniques for resource-constrained environments....
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 constructing portfolios, implementing mean-variance optimization, factor models, risk parity, or Black-Litterman allocation - covers modern portfolio theory and practical enhancementsUse...
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 ",...
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.
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 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,...
Patterns for physics-based simulation including numerical integration, rigid body dynamics, fluid simulation, finite element methods, and multi-physics coupling. Covers accuracy, stability, and...
Patterns for laboratory automation including liquid handling robotics, LIMS integration, protocol development, quality control, and high-throughput workflows. Covers both open-source (Opentrons)...
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...
Use when implementing attention mechanisms, building custom transformer models, understanding positional encoding, or optimizing transformer inference - covers self-attention, multi-head...
Patterns for protein structure prediction using AlphaFold2/ColabFold, structural analysis, model quality assessment, and integration with experimental data. Covers best practices and critical...