Unit 8 · Measure and improve AI quality

Improve how an agent chooses and acts

You evaluate the whole agent pipeline and tune its actor or responder. Good task records exercise tool choice, clarification, delegation, and final quality.

optimize()11 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