Latency is architecural
Most latency comes from retrieval hops and orchestration, not the model; RAG pipelines often recreate microservice-style chatter that slows systems down.
Most latency comes from retrieval hops and orchestration, not the model; RAG pipelines often recreate microservice-style chatter that slows systems down.
AI systems behave like probabilistic components; engineers must build structured interfaces and layered constraints to make them reliable inside software systems.
Executives must treat LLMs as probabilistic systems requiring controls, governance, and new forms of oversight.
AI adoption is an organisational transformation requiring mandates, measurement, and redesigned processes.
A clear explanation of what AI is—and is not—cutting through hype to define its real capabilities and limits.
Software engineers must understand tokens, structure, and probabilistic behaviour to build reliable systems and avoid mismatches between test and production behaviour.
Clear, practical prompting habits to help you get faster, more reliable results from everyday AI tasks.
A framework for evaluating claims made about AI systems, focusing on evidence, capability, and verifiable performance.