AI Tutorials
Hands-on, code-first walkthroughs for building real products with AI.
What a tutorial here looks like
Tutorials are step-by-step and implementation-focused: a clear goal, the prerequisites, the code, and an honest note on what breaks in production. Where a walkthrough depends on a specific model, framework or pricing tier, we say so, because those change quickly.
Areas we cover
- Calling LLM APIs safely from a server, including keys, retries and rate limits.
- Retrieval pipelines: chunking, embeddings, vector search and evaluation.
- Agents and tool calling — structuring prompts, validating output, handling failure.
- Cost and latency control: caching, smaller models, batching and streaming.
- Shipping: observability, prompt versioning and regression testing.
Before you start building
Pick your stack first. The tools directory lists assistants, builders and automation platforms by category, and AI guides explain the concepts behind them. For releases that affect what you build on, follow AI news.
Start here while this section grows
Articles filed under ai tutorials appear here automatically as our editors publish them. In the meantime, these parts of AIWeekly cover the same ground.
- Latest AI newsDaily coverage of launches, funding and policy across the AI industry.
- AI tools directoryBrowse assistants, builders, marketing and automation tools by category.
- The AIWeekly newsletterA weekly email round-up of what actually mattered in AI.
- AI for UK businessPractical support for teams adopting AI in their day-to-day operations.