
Prompting, RAG or fine-tuning? Choosing how to adapt a language model
Better prompts, retrieval, fine-tuning or tools? A practical guide to working out what your AI feature is missing, and choosing the simplest change that fixes it.
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Engineering practice for software that lasts: architecture, testing, delivery and operations.

Better prompts, retrieval, fine-tuning or tools? A practical guide to working out what your AI feature is missing, and choosing the simplest change that fixes it.
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Headless, traditional or hosted builder? A practical way to decide, based on who edits the site, what it must integrate with and how it will be operated.
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A demo shows an AI feature on a good day. Here is a practical way to test it on real cases, agree what good looks like, and keep checking once it is live.
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Delivery is a moment; maintenance is the life of a product. The engineering habits that keep software changeable years after launch.
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Retrieval-augmented generation lets an AI assistant answer from your organisation's own documents and show its sources. How it works, what decides its quality, where it fails and when it fits.
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