- Situation
- On a regulatory document platform, generated documents came out wrong in ways that did not reproduce, and retries repeated the bad output.
- Task
- Find the true cause in a pipeline whose output reaches a client in a regulated industry.
- Action
- I traced it to a global result cache that also stored partial failed runs, then re-architected generation around per-step isolation with failure-aware cleanup.
- Result
- Failed runs stopped affecting later ones, a retry became a real retry, and the written root cause let the team review it.
◈ View in the world- Situation
- Medical writing deliverables showed misplaced tables, detached titles, and sometimes raw markup visible as text in the client's document.
- Task
- Produce one root cause analysis for three separately reported bugs before anyone wrote a fix.
- Action
- I found three causes: raw XML mutation, incomplete model-emitted HTML, and context-blind placeholders. I moved tables to a structured contract with neighbour context.
- Result
- The whole class of defect went away, not just the three reported instances.
◈ View in the world- Situation
- Two engineers were joining a document platform module covering audit logs, automatic mapping and server management.
- Task
- Give onboarding an intended outcome rather than just an activity.
- Action
- I asked the lead for the target outcome, how we would judge pace, and when production value was expected, and offered a reference checklist.
- Result
- Onboarding ran against a stated target and a first-value date, and the checklist was reused.
◈ View in the world
Architecture Decision Records
Azure OpenAI
Azure
Terraform
Python
Embeddings
PDF Processing
