Unit 8 · Measure and improve AI quality

Improve a generator or workflow with data

You tune a generator or workflow from examples and a metric. Bound the budget, keep validation data separate, and apply the returned artifact through the program API.

optimize()10 focused minutesNot started

Unit example (nearest native match)

See the idea in context

auto engine = axllm::AxGEPA(reflectionClient, axllm::object({}));
auto result = engine.optimize(request, evaluator);

Run itIn your own project

include(FetchContent)
FetchContent_Declare(axllm GIT_REPOSITORY https://github.com/ax-llm/ax GIT_TAG main SOURCE_SUBDIR packages/cpp)
FetchContent_MakeAvailable(axllm)
target_link_libraries(your_app PRIVATE axllm::axllm)

#include <axllm/axllm.hpp>

auto llm = axllm::ai("openai", axllm::object({{"apiKey", std::getenv("OPENAI_API_KEY")}}));
auto classify = axllm::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 -- cpp src/examples/cpp/optimization/axgen_optimization.cpp

Active practice

Show that you can use it

Answer 2 in a row to learn this · attempt 1

Keep exploring

See the idea in context

Show that you can use it

Source-backed follow-up