An AI chatbot for your business: where to start
A good chatbot isn't just an "answerer". It has the right knowledge, knows its limits and hands over to a person. Here is the set-up path, common mistakes and how to measure success.
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AI articles
Building products with AI: assistants and agents, knowledge sources, human handoff, quality measurement and cost control.
11 articles
What is RAG? AI that answers from your own documents
Language models don't know what they haven't seen. RAG means finding the most relevant parts of your documents before answering and handing them to the model. Here is the idea, the benefit and the limits.
Read articleHow an AI sales assistant actually works
An AI sales assistant is not a rule-based bot. It answers from the store's real catalogue, reads buying intent and hands the conversation to a person when it should. A look at the parts that make it work.
Read articleAI agent vs chatbot: what actually separates them
A chatbot answers; an AI agent gets things done. The difference lies in tools, memory and the authority to act. Where each one fits, and when building an agent is worth it.
Read articleHuman handoff: the most important moment in an AI assistant
A good AI assistant knows when to step aside. Designing the moment a conversation passes to a human operator is what separates a trustworthy product from an irritating one. Triggers, method and common mistakes.
Read articleAI in the product: core, not decoration
Adding a chat box doesn't make a product intelligent. AI earns its place when it shortens or enables a real task for the user. Four questions that separate real use from a demo.
Read articleControlling AI cost: a multi-model gateway and a budget per conversation
In an AI product every answer costs money, and user growth can turn into growing losses. A multi-model gateway, the right model for each task, caching and usage caps make the cost predictable.
Read articleAI assistant persona and tone: making the model sound like the brand
An AI assistant speaks for the brand, and every sentence is credited to you. Defining its persona, tone, scope and red lines is design work, not just a few lines of instructions. A practical method and common pitfalls.
Read articleEvaluating AI quality: from "looks good to me" to systematic measurement
An AI product can't be approved with a handful of manual tries. An evaluation set, clear criteria and a quality gate before each release are the only dependable way to change models and prompts without breaking the product.
Read articleAI-assisted engineering: more speed, the same responsibility
AI tools have made writing code fast, but not deciding what to write. A team benefits from them when it already has a precise definition, a clear architecture and automated tests. The human role has changed; it hasn't gone.
Read articleGEO: how to be visible in AI answers
Some searches now end in a ready-made answer instead of a list of links. Generative engine optimisation means content an AI can find, understand and cite with confidence.
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