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AI Terminology for Your First Week

AI Terminology for Your First Week

Beginner Guides

The essential AI terms worth knowing in your first week, covering prompts, context, hallucinations, agents, and tokens.

You don’t need to memorize every AI term before getting started, but a handful come up constantly enough in the first week that knowing them upfront saves real confusion.

Prompt. Simply what you type or say to the AI, your actual request. “Prompting well” means writing clear, specific requests, covered in our full prompt engineering guide.

Context. Everything the model can currently “see”: your prompt, attached files, the conversation so far. More context generally means better answers, up to a real limit.

Hallucination. When a model states something false with total confidence. Our full explainer covers why this happens, worth understanding early since it affects how much you should trust specific claims.

Agent. An AI system that takes multi-step actions toward a goal, rather than just answering a question. Token. The basic unit a model reads and generates. It shows up constantly in pricing, and our full explainer covers what it means in practice. Bookmark our full AI glossary for anything else that comes up, and see Anthropic’s own help center as one starting point.

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AI App Builders for Internal Tools

AI App Builders for Internal Tools

App Builders

A look at why internal tools are the strongest current fit for AI app builders, and how to keep proper data handling discipline while building fast.

Internal tools, dashboards, approval workflows, small data-entry apps used by a handful of employees, are the single strongest fit for AI app builders right now, well ahead of consumer-facing products.

Our honest look at what AI can build from a prompt covers why: simple internal tools with a small, known user base and lower security stakes than a public-facing product are exactly the category current AI app builders handle well.

Many internal tools never get built at all because the engineering cost doesn’t justify the value for a small internal audience. AI app builders lower that cost enough that tools which weren’t previously worth building become genuinely feasible.

“Internal” doesn’t mean “no security considerations.” If the tool touches sensitive employee or customer data, apply the same data handling scrutiny you’d apply to any other system, regardless of how quickly it was built.

Genuinely expands what’s feasible to build, not just speeding up what was already planned. Keep real data handling discipline regardless of how quickly the tool came together. See Google’s own announcement on folding app-building into Gemini.