Section
AI
Understanding and using artificial intelligence: agentic commerce, AI at work and in everyday life, models & tools – concrete instead of buzzwords.
When AI agents do the shopping: LLM visibility, agent-ready stores and AI content in commerce.
LLM Optimisation: How Your Store Shows Up in AI Answers
LLM optimisation for stores: how to get cited in ChatGPT, Claude and Perplexity – the key levers, common mistakes, and how to measure GEO visibility.
Agent-Ready Commerce: When AI Agents Are Your Customers
AI agents increasingly shop on their own. Here's how to make your store agent-ready: structured data, open checkouts and interfaces for machines.
AI Product Copy at Scale: Why Quality Is a Data Problem
Creating AI product descriptions without ending up with duplicate content: why scaled copy is a data problem – the four-step workflow that fixes it.
Agents, adoption and working practice: how AI turns from pilot project into a productive tool.
AI Agents at Work: From Chatbot to Colleague
AI agents complete tasks rather than just answering questions: researching, booking, coding. Where agents work well today – and how to get started properly.
Context Engineering: Why Context Beats the Prompt
Context engineering decides AI quality, not the prompt. The three layers explained, RAG versus fine-tuning compared, and a seven-step guide to getting started.
AI Adoption in SMEs: From Pilot Project to Everyday Practice
Adopting AI in SMEs: the three-step approach of pilot area, tool plus workflow, and time tracking – with a worked example and the most common mistakes.
Assistants, learning, everyday help: what AI already does for everyone – no expertise required.
AI Assistants in Everyday Life: What Actually Works Today
Beyond the demo videos: where AI assistants reliably help in daily life, where they fail – and how to use them without trusting them blindly.
Learning with AI: The Personal Tutor for Everyone
Learning with AI: the four most effective usage patterns, a seven-step learning routine, active versus passive compared – and the most common mistakes.
Deepfakes: Spot Them, Assess Them, Guard Against Them
Cloned voices, faked video calls: deepfakes are now an everyday risk. Why spotting them isn’t enough on its own – and which safeguards actually work.
Cloud or local, open or proprietary: the technical decisions behind using AI.
Fable 5 vs. Kimi K3: The New Top Duel in AI Models
Claude Fable 5 versus Kimi K3 – and the rest of the field: strengths, prices, context windows and benchmarks of today's frontier models, soberly compared. As of July 2026.
Local AI vs. Cloud: When Your Own Models Pay Off
Local AI vs. cloud compared: data sovereignty, costs under sustained load, a worked payback example, and the routing pattern that combines both worlds.
AI PCs and NPUs: What's Really Behind the Marketing
“AI PC” is stamped on almost every new laptop. What NPUs actually do, which specs matter when buying – and when waiting for the next generation pays off.