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Occasional writing on workflow study, evaluation, human review, and running AI systems in production.
Sit with operators, study a live workflow, and build the production system that changes it.
Build and maintain the connectors that let a deployment read and write a customer's systems of record.
Build the test sets, scoring, and monitoring that decide whether a workflow is ready for production.
Run the one-week study: trace the process, find the constraint, and write the scope.
Design the review queues, approval screens, and evidence views operators use every day.
Keep shipped workflows healthy: watch failures, review corrections, and report on the agreed measure.
Choose the right mix of models, retrieval, and plain software for each part of a workflow.
Turn what repeats across deployments into the shared system every engagement builds on.
Find the teams whose workflows are worth changing, and stay accountable for the result.