
I trusted AI agents after I stopped trusting their first draft
How deep tests, stacked pull requests, adversarial review and isolated environments let me delegate parallel software delivery safely.

How deep tests, stacked pull requests, adversarial review and isolated environments let me delegate parallel software delivery safely.

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.

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

Why pull-request-controlled AI review instructions collapse a trust boundary, and how teams can restore it without giving up useful repository context.