Evaluating AI Systems: Metrics that Matter
Evaluating AI systems means measuring real behaviour, not synthetic benchmarks.
How to Evaluate the Output of an AI Chat Session
A practical guide to assessing the quality, reliability, and safety of AI chat session outputs.
How to Use AI Safely and Effectively
Guidance on using AI safely and effectively, grounded in recent examples of misuse and emerging best practices.
Latency is architectural
Most latency comes from retrieval hops and orchestration, not the model; RAG pipelines often recreate microservice-style chatter that slows systems down.
Chat Interface to System Component
AI systems behave like probabilistic components; engineers must build structured interfaces and layered constraints to make them reliable inside software systems.
What Tech Executives Need to Know About Working With LLMs
Executives must treat LLMs as probabilistic systems requiring controls, governance, and new forms of oversight.
Transforming Your Business for AI
AI adoption is an organisational transformation requiring mandates, measurement, and redesigned processes.
What software engineers need to know about LLMs
Engineers must think in tokens to avoid test‑to‑production mismatches.
A Beginner's Guide to AI Chatbot Prompting
Clear, practical prompting habits to help you get faster, more reliable results from everyday AI tasks.