Cost Attribution, at Three Scales
One discipline — making compute fleets legible and their costs attributable — proven from $10–12M/quarter cloud spend down to invoices I personally pay.
Fleet-Scale Financial Attribution — Apple
Own the CIBO/FinTrack pipeline correcting cost misattribution across roughly 700,000 servers, where quiet errors distort budgets by millions. Plus cloudOS, an internal platform giving Finance, SRE, and execs visibility into livability, deployment state, and financial attribution. Now piloting LLM inference to pre-label project cost hierarchies.
Cost-Attribution Pipeline — Roku
Built the pipeline handling $10–12M/quarter of AWS spend and co-led the ECS→Kubernetes migration. The engagement where the theme crystallized: cost data is an engineering artifact, not an accounting afterthought.
Trendvesting — Unit Economics in Production
AI signal-intelligence platform live since Feb 2024: multi-mode Go backend, Next.js app, React Native client, Python FastAPI consensus service. A real AI system whose invoice I pay — ~$1.50–2.00 fully loaded per signal, ~$400–500/month steady state. The case study I live in.
TendForm — Infrastructure Discipline, Solo
Solo SaaS form builder with multi-form packets, a markdown DSL, a production MCP integration, and a HIPAA-compliant tier on a CloudNativePG enclave with a full BAA chain. Real customers, real deployments — run like the fleet work, just smaller.
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By the Numbers
How I Work
Attribute
Map the spend to owners, systems, and units. Nobody owns a cost they can't see.
Instrument
Turn cost into an engineering artifact — measured in the system, not reconciled after the fact.
Reconcile
Validate the architecture against the invoice. The diagram and the truth have to match.
Make it legible
Ship a surface Finance, SRE, and execs can all read — cost data people actually use.
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