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Defining Cache Breakpoints

⚡ Prompt Caching Framework⏱ 20 min⭐ 350 BASE XP⌨ HANDS-ON LAB

Strategic Context Storage

Anthropic's Prompt Caching allows developers to persist large prefixes (like system instructions or tool definitions) in the model's high-speed memory. Unlike automatic caching systems, Anthropic requires explicit markers. You must append a cache_control object set to {"type": "ephemeral"} at specific breakpoints in your request array.

The 4-Breakpoint Constraint

A single API request can contain a maximum of 4 cache breakpoints. This limit forces developers to be strategic: typically, you would cache your system prompt at breakpoint 1, your tool definitions at breakpoint 2, and maybe a large set of reference 'knowledge documents' at breakpoint 3. This leaves the final user-turn volatile while keeping the heavy repetitive context 'warm' in the cluster.

Architecture Note: Hashing is performed on the entire prefix up to the breakpoint. Even a single character change before a breakpoint will invalidate the cache for that block and all subsequent blocks.
⌨ HANDS-ON LABMark Ephemeral Cache Breakpoints
⭐ +200 XP

Persist repeated system instructions in cache. Add a cache_control object with type 'ephemeral' to your system prompt content array.

1POST to /v1/messages with system structured as an array of content blocks and cache_control: {"type": "ephemeral"}.
lab-sandbox — simulated environment
INFINITY LAB SANDBOX v2.6 — simulated shell
Type the command for the current objective. Helpers: "hint", "solution", "clear".
$
OBJECTIVE 1 / 1 — type "hint" if stuck
SYNAPSE VERIFICATION
QUERY 1 // 3
How is a cache boundary physically marked in the Anthropic schema?
By checking a box in the Console
By appending a cache_control object set to 'ephemeral' inside specific content arrays
By putting the context in XML tags
Using an external Redis database