FinOps operating models and cloud economics
Establish decision rights, allocation, forecasting, optimization, reporting, and adoption practices that make cloud investment actionable.
FinOps · AI economics · TBM · Technology governance
FinOps leadership for the economics of cloud and AI.
I help technology, finance, and product leaders turn consumption data into policy, accountability, optimization, and measurable business value.
Enterprise FinOps advisory
Client-facing operating models
TBM-aligned value transparency
AI economics development
Professional foundation
Proven FinOps practice. Deliberate AI-economics trajectory.
I am a senior, client-facing FinOps consultant at Apptio, an IBM company. My work spans FinOps strategy, operating models, governance, cloud economics, optimization, forecasting, reporting, and organizational adoption.
I am applying that foundation to a newer business problem: governing AI usage and token consumption so model choices, cost allocation, risk, quality, and outcomes can be evaluated together.
Connected capabilities
Economics, governance, and execution as one system.
Strong technology economics requires more than a cost report. It connects consumption, ownership, policy, architecture, behavior, and business outcomes.
AI economics and token governance
Extend FinOps practices to AI consumption, model selection, unit economics, cost attribution, quality, responsible-use guardrails, and ROI.
TBM and value transparency
Connect technology cost and resource consumption to services, consumers, business capabilities, and the decisions leaders must make.
Governed automation and decision support
Encode repeatable advisory logic into focused tools, agents, connectors, and workflows without creating unnecessary software or technical debt.
Selected work
Methods and products that make judgment repeatable.
Work is labeled by maturity. Intended value is not presented as a realized outcome until it has been measured.
Persona-Based Report Architect
A conditional interview and specification workflow designed to translate stakeholder priorities into practical, persona-aligned FinOps reporting.
S3 Transition Cost Validator
A focused decision-support product for estimating one-time S3 storage-class transition charges using object-level size, age, and duration requirements.
Task-to-Model Governance Catalog
A policy model for mapping a user’s role, seniority, use case, risk, and task requirements to an approved and economically appropriate AI model.
Whole-system governance
A learning loop from business intent to measurable value.
- Align business goals, decision rights, and value measures.
- Instrument cost, usage, ownership, quality, and outcomes.
- Govern through policy, guardrails, workflows, and exceptions.
- Set materiality thresholds, review cadences, and explicit stopping rules.
- Optimize architecture, consumption, commitments, and process.
- Measure adoption, value, risk, and unintended consequences.
- Feed evidence back into controlled policy improvement.
Professional direction
Building the operating discipline for AI value.
“Token economics” here means the production and consumption economics of AI: how tokens, models, infrastructure, quality, risk, and business outcomes interact. It does not refer to cryptocurrency token design.
The objective is practical: help organizations make governed AI investment decisions with the same financial and operating discipline expected of cloud.
Read the professional narrative