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Everyone is building an AI startup. Thin wrappers around a model are fragile; ideas built on proprietary data, deep workflows and distribution can last. Here is how to choose and test one.
AI can write product descriptions, answer shopper questions and personalise recommendations. See where it helps, how to roll it out safely and the pitfalls to avoid.
Where should a small team start with AI? Six low-risk tasks save the most time, plus a safe pilot plan, a one-page policy and a simple way to measure the result.
AI-generated faces and voices are used in real fraud. Learn the warning signs of a deepfake, why they are not enough on their own and the verification habits that defeat the scam.
Vibe coding is building software by describing what you want and letting an AI write the code. Here is where the term came from, what it is good for and where it breaks.
Retrieval-augmented generation lets a chatbot answer from your own documents instead of guessing. Learn how RAG works, how to chunk and search, and how to test it.
Shipping an LLM feature is the easy part. AI observability shows you what it is really doing: quality, cost, speed and failures. Here is what to track and why.
An eight-step plan for your first AI agent: scope one job, pick a model, design tools, add guardrails, test with real cases and launch in stages.
AI agents do more than answer questions: they plan, use tools and finish tasks. Here is how they work, how they differ from chatbots and workflows, and where they pay off.
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