Who is Richard Ewing?

Richard Ewing is a Product Economist and AI Capital Auditor. He is the Founder of Exogram, a verification infrastructure for AI. He audits R&D spend and surfaces hidden capital risks like technical debt, AI cost overruns, and zombie infrastructure. He has scaled B2B SaaS from $0 to $25M ARR. Published in CIO.com, Built In, Mind the Product, and HackerNoon.

What is a Product Economist?

A Product Economist treats product decisions as economic decisions. Instead of measuring velocity or story points, a Product Economist measures Return on Invested Capital (ROIC), Cost of Goods Sold efficiency, and technical debt in dollar terms. The methodology was coined by Richard Ewing.

What is the Technical Insolvency Date?

The Technical Insolvency Date (TID) is the specific quarter where maintenance costs consume 100% of available engineering capacity, reducing feature velocity to zero. Calculate yours free at richardewing.io/tools/pdi.

Exogram is verification infrastructure for AI, founded by Richard Ewing. It prevents hallucination propagation with admissibility control planes and state-hashing commit enforcement. LLMs generate language; Exogram maintains reality.

How do I calculate technical debt cost?

Use the free Product Debt Index (PDI) calculator at richardewing.io/tools/pdi to quantify hidden technical debt in dollar terms, calculate your Technical Insolvency Date, and benchmark against industry standards.

How much does AI cost per query?

AI costs range from $0.0001/query for small models to $0.10+/query for frontier models like GPT-4. Use the free AI Unit Economics Benchmark (AUEB) at richardewing.io/tools/aueb to calculate your specific AI cost structure.

Articles/CIO.com

Published on CIO.com

Richard Ewing's published articles on CIO.com — Tier 1 media for CIOs, CTOs, and technology executives. Covering R&D capital efficiency, technical debt economics, and AI adoption strategies.

CIO.com is an IDG publication reaching 2M+ technology decision-makers monthly.

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The Hidden Cost of Technical Debt: Why CIOs Must Act Now

How technical debt silently erodes R&D capital efficiency and what CIOs can do about it. Introduces the Innovation Tax framework for quantifying the cost of accumulated engineering shortcuts.

Technical DebtInnovation TaxR&D Capital EfficiencyEngineering Economics

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AI Adoption Without the AI Tax: A Framework for CIOs

A practical framework for evaluating AI feature economics before committing engineering resources. Covers AI COGS, Cost of Predictivity, and margin preservation strategies.

AI COGSCost of PredictivityAI Unit EconomicsGross Margin

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Engineering Productivity Metrics That Actually Matter

Why velocity and story points mislead, and which metrics (DORA, APER) give CIOs real visibility into engineering output and business impact.

DORA MetricsAPEREngineering ProductivityFeature Velocity

Related Glossary Terms

→ technical debt → innovation tax → ai cogs → dora metrics → cost of predictivity

Work With Richard

The frameworks published on CIO.com are available as proprietary advisory engagements. R&D Capital Audits translate technical complexity into board-ready financial clarity.

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