Triggered, not trusted.

Automation only earns trust when the team can inspect what it did and intervene when it shouldn't have. Most of the automation we inherit fails the second test — opaque scripts, hidden rules, brittle integrations that work until they don't.

We separate the work first. Some operational steps are mechanical: validation, transformation, dispatch, repetition. Those belong in code. Others are judgement calls that look mechanical until something unusual arrives. Those don't — and rules that pretend they do are the dangerous part. The boundary between the two is where the work starts.

We write the logic somewhere humans read. A runbook that names the inputs, the rules, the failure paths, and what to do when each one fires. The code follows the runbook, not the other way around. If the documentation rots, we treat that as a system fault.

We design for the visibility the operators need. Every automated step emits enough signal to be diagnosed when it behaves unexpectedly. Failed runs route somewhere a human notices. Rollback paths exist. Black-box automation is fragile by construction.

This work covers workflow automation across operational tools, data integrations between systems that don't share an API, and AI-assisted steps where retrieval and triage genuinely help — used where they fit, not because they are available.