Combining Claude Code and GPT to build and debug a programming language
This describes a workflow for building a where two AI models split the work of finding and fixing crashes and . Claude Code handles architectural review along with reproducing and fixing crashes and .
A GPT-family model handles the actual code editing and refinement. Splitting the work this way noticeably sped up both development and debugging compared to relying on a single AI.
of the AI's output is called out as a required step, not optional. The workflow itself is rated 80 out of 100 for practical value and is classified as advanced-level.
Key points
- Claude Code handles plus reproducing and fixing crashes and
- A GPT-family model handles actual code editing and refinement
- Applied to the demanding task of building a
- of AI output is treated as a required step, not optional
- Workflow rated 80/100 for practical value, classified as advanced-level