
I'm fed up of people using the excuse of AI slop
AI slop is the result of weak direction and absent editorial judgement, not an excuse to blame the tool.

AI slop is the result of weak direction and absent editorial judgement, not an excuse to blame the tool.

A multi-agent quality pipeline that replaces routine line-by-line review with executable evidence and deterministic gates.

Long context windows do not guarantee reliable recall. Design retrieval, reranking and prompt assembly so the model can use the evidence it receives.

How to run a nightly AI security audit without giving the model credentials, production access or authority to merge its own fixes.

Claude's invisible marks could improve provenance, but Anthropic has not yet shown that they leave generated code quality and optimisation untouched.

What stacked pull requests are, how GitHub's native workflow works, and where the public preview still needs care.

Keep model names in configuration, select models by task, and compare routes using the cost of completed work.

Why a short cooldown for routine dependency releases is a practical supply-chain control, not neglect disguised as caution.