Accelerating Idea Discovery and Prototyping with AI Agents

Description and use

The author successfully modernized a legacy C++ XML parser and optimized its performance to exceed competitors in specific benchmarks. The process, which would have taken weeks manually, was completed in a fraction of the time using AI agents. This allowed the author to explore the idea's limits, learn new optimization techniques, and free up time for other projects.

Problem

Software engineers face high opportunity costs when pursuing side projects or legacy code maintenance. Routine tasks like setting up CI/CD, documentation, and test suites consume time that could be spent on core logic or exploring new ideas. Without AI, bringing a project up to modern open-source standards or optimizing performance can take weeks or months of evenings and weekends.

Outcome

The author successfully modernized a legacy C++ XML parser and optimized its performance to exceed competitors in specific benchmarks. The process, which would have taken weeks manually, was completed in a fraction of the time using AI agents. This allowed the author to explore the idea's limits, learn new optimization techniques, and free up time for other projects.

Workflow

• Identify a legacy project or new idea with high potential but low current maturity.
• Use an AI agent (e.g., Claude Code) to generate a comprehensive test suite.
• Configure GitHub Actions to automatically generate API documentation using tools like Doxygen.
• Set up GitHub Actions for cross-platform compilation and continuous integration.
• Use an AI agent harness (e.g., omp) with an LLM (e.g., GPT) to benchmark the code against existing libraries.
• Prompt the AI agent to implement specific performance improvements to match or beat competitors.
• Allow the AI agent to run in the background while the engineer focuses on other tasks or learning.
• Review the results, validate the improvements, and decide whether to continue, discard, or pivot the project.

Evidence

I used Claude Code to: create a test suite, build a GitHub Action to automatically generate the API documentation using Doxygen, compile the C++ library for different operating systems with a GitHub Action.

Source

Most recently I used omp, an AI agent harness, with GPT to revisit the code... my XML parser library was much faster in a subset of benchmarks.

Source

In the past, I would have taken time for each step of the process and it would have taken weeks of evenings and weekends to discover and implement the improvements.

Source