Unit 11 · Ship AI systems you can operate

See failures, cost, and latency in production

You add traces, usage and cost accounting, cache policy, cancellation, bounded retries, and safe logs. Debug output becomes evidence for tests and operations.

9 focused minutesNot started

Unit example (nearest native match)

See the idea in context

var program = Ax.ax("text:string -> label:string");
var usage = program.getUsage();

Trace the run
tracer connects model and tool activity to the surrounding request.
Make cancellation possible
abortSignal lets callers stop work that is no longer useful.
Control repeated work
contextCache makes reuse an explicit operational policy.

Run itIn your own project

// Gradle (build.gradle):
implementation 'dev.axllm:ax:22.0.4'
// Maven (pom.xml):
<dependency>
  <groupId>dev.axllm</groupId>
  <artifactId>ax</artifactId>
  <version>22.0.4</version>
</dependency>

import dev.axllm.ax.Ax;

var llm = Ax.ai("openai", Map.of("apiKey", System.getenv("OPENAI_API_KEY")));
var classify = Ax.ax("review:string -> sentiment:class \"positive, negative, neutral\"");

Set OPENAI_APIKEY in your environment before running provider-backed code.

In the ax repo

From a clone of the ax repo:

npm run example -- java src/examples/java/long-agents/SmartDefaultsAgentExample.java

Active practice

Show that you can use it

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See the idea in context

Show that you can use it

Source-backed follow-up