The response is a structured object, not a string

The biggest reason AI breaks on its own first LLM call: it treats the response like it's just a string. It isn't. It's a structured object with a list of content blocks, each tagged by type.

Why a list? Because a single response can contain multiple things — plain text, a tool call, an image, a thinking block. Today you'll see mostly text. Tomorrow, when we get to agents, you'll see tool_use blocks in the same list.

The pattern AI ships every time:

• response.content[0].text — the actual reply text (Anthropic SDK)
• response.choices[0].message.content — the OpenAI equivalent
• response.usage.input_tokens / output_tokens — what you'll bill

Both SDKs return objects in production. In this lesson we use dicts that match the same shape, so the indexing is identical: response["content"] [0]["text"] instead of response.content[0].text. Same fields, two notations.

The single most common AI bug here: writing response["text"] or response.text directly. There is no top-level text field. The text is always nested inside a content block.

Run the editor. Two reads from the same response: the reply, then the token count.