Oleksandr Kuzmenko, EditorPublished 4 min readAI-assisted · editor-reviewed
TL;DR
- Credit and accountability are two sides of the same coin; tools cannot be held accountable for software flaws.
- Disclosing AI involvement in pull requests can dilute personal responsibility without providing technical benefit.
- Engineers must retain full ownership of merged code and tests regardless of how they were generated.
Accountability vs. Tool Crediting
Developers have developed a habit of announcing AI involvement when sharing pitch documents or pull requests, volunteering statements like "I asked an LLM to write this" or "the LLM wrote the unit tests." While this may stem from honesty or excitement, crediting an LLM creates an accountability problem.
Credit and accountability are two sides of the same coin. A tool can only take as much credit as it can be held accountable for. Because an AI tool cannot be blamed or held responsible for production bugs or incomplete work, attributing work to it dilutes human ownership.
Taking Full Ownership of Deliverables
If you create something remarkable using an LLM, take full credit for the result. Conversely, if the generated work is flawed or incomplete, accept full responsibility and refine it. Ownership remains with the engineer, with or without AI assistance.