Speakers and attendees at AIE Code Summit propose a manifesto for taking responsibility for AI-assisted code, documents, and messages. Their concern is the work passed to the next person: generated output can be cheap to produce and expensive to understand or review.
They propose a few practical commitments:
- Understand the problem and own the consequences of what ships, even when an agent helps make it.
- Check the parts that matter before sharing agent-written work; scale the amount of review to the stakes.
- Measure what shipped and how it helps people, rather than output volume or the number of agents running.
- When mistakes repeat, improve the system and automate checks where possible instead of patching each output alone.
The authors acknowledge that quick, unreviewed experiments can be useful. Their concern is output that undermines the product, maintainability, or teammates’ time.
The 106-comment thread on Hacker News adds practical review ideas and challenges the manifesto’s definition.
What the thread adds
- courtcircuits suggests including the prompt with a large AI-generated change to expose the contributor’s reasoning, while acknowledging it is no silver bullet. grey-area instead argues for splitting large changes into smaller, safer ones.
- BrandoDev_it asks how human review can keep pace with generated code. TexanFeller replies that faster code is not necessarily better and describes cutting generated code down for clarity and maintenance.
- seizethecheese questions whether defining slop by the effort imposed on the reader would also cover valuable AI-generated mathematical proofs that take significant work to understand.
- Pannoniae challenges the assumption that producing the same result as others is necessarily bad, arguing that ordinary, good-enough solutions can leave room to innovate where it matters.
HN handles are pseudonymous, per-comment scores are not public, and ordering follows HN’s ranking. This is a slice of the discussion, not a consensus.