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Model Selection Logic: Fit-for-Task Decision Trees
Model Selection Logic: Fit-for-Task Decision Trees A model choice is a product choice. The moment you ship more than one model, you are no longer “using AI.” You are operating a decision system that trades cost, latency, and quality in real time. Fit-for-task selection is how serious teams stop arguing about which model is “best” […]
Planning-Capable Model Variants and Constraints
Planning-Capable Model Variants and Constraints “Planning” is an overloaded word in AI. In a research demo, it often means a model can produce a neat list of steps. In a production system, planning means something stricter: the system can choose actions over time, cope with partial feedback, and still land on an outcome that is […]
Quantized Model Variants and Quality Impacts
Quantized Model Variants and Quality Impacts Quantization is the most common way teams turn “a model that works” into “a model that ships.” It changes the unit economics of inference, reshapes latency, and often determines whether a feature can be offered broadly or only to a premium tier. But quantization is not free compression. It […]
Tool-Calling Model Interfaces and Schemas
Tool-Calling Model Interfaces and Schemas Tool calling is where language models stop being “a box that prints text” and become a participant in a larger machine. The moment a model can trigger an API request, write a database query, open a ticket, or schedule a workflow step, the problem changes. You are no longer evaluating […]
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Models and Architectures
Model families and architecture choices that shape capability, cost, and reliability.
Context Windows and Memory Designs
Concepts, patterns, and practical guidance on Context Windows and Memory Designs within Models and Architectures.
Diffusion and Generative Models
Concepts, patterns, and practical guidance on Diffusion and Generative Models within Models and Architectures.
Embedding Models
Concepts, patterns, and practical guidance on Embedding Models within Models and Architectures.
Large Language Models
Concepts, patterns, and practical guidance on Large Language Models within Models and Architectures.
Mixture-of-Experts
Concepts, patterns, and practical guidance on Mixture-of-Experts within Models and Architectures.
Multimodal Models
Concepts, patterns, and practical guidance on Multimodal Models within Models and Architectures.
Rerankers and Retrievers
Concepts, patterns, and practical guidance on Rerankers and Retrievers within Models and Architectures.
Small Models and Edge Models
Concepts, patterns, and practical guidance on Small Models and Edge Models within Models and Architectures.
Speech and Audio Models
Concepts, patterns, and practical guidance on Speech and Audio Models within Models and Architectures.
Agents and Orchestration
Tool-using systems, planning, memory, orchestration, and operational guardrails.
AI Foundations and Concepts
Core concepts and measurement discipline that keep AI claims grounded in reality.
AI Product and UX
Design patterns that turn capability into useful, trustworthy user experiences.
Business, Strategy, and Adoption
Adoption strategy, economics, governance, and organizational change driven by AI.
Data, Retrieval, and Knowledge
Data pipelines, retrieval systems, and grounding techniques for trustworthy outputs.
Hardware, Compute, and Systems
Compute, hardware constraints, and systems engineering behind AI at scale.