# Stop Parsing LLM Junk: Zero-Latency JSON with Claude Prefill, Spring AI, and Java 26 Records

> Source: <https://dev.to/machinecodingmaster/stop-parsing-llm-junk-zero-latency-json-with-claude-prefill-spring-ai-and-java-26-records-2pmj>
> Published: 2026-06-13 06:38:50+00:00

Stop wasting precious CPU cycles and token budget on retry loops just because an LLM decided to wrap your JSON in markdown code blocks. In 2026, production-grade Java backends are achieving zero-latency, deterministic JSON parsing by forcing Claude's very first output token to be the opening brace of a Java 26 Record.

`ObjectMapper`

try-catch blocks and prompting "return ONLY JSON" which inevitably fails under high load.

``json`

) from the response before parsing.Force Claude's output structure by pre-populating the assistant's response directly within Spring AI, bypassing the LLM's formatting decisions entirely.

`AssistantMessage`

containing the exact JSON prefix you expect to guarantee the structure.`ChatClient`

fluent API to merge your user prompt and the prefilled assistant response in a single round-trip.``java`

record DevProfile(String name, String role, int level) {}

String prefill = "{\n \"name\": \"Alex\",\n \"role\": \"Architect\",\n \"level\": ";

var response = chatClient.prompt()

.user("Generate a profile for a senior dev.")

.messages(new AssistantMessage(prefill))

.call()

.content();

// Reconstruct and parse instantly with zero validation overhead

var profile = jsonMapper.readValue(prefill + response, DevProfile.class);

```

`ChatClient`

with Java 26 Records keeps your data layer type-safe, immutable, and easy to maintain.

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