You're In — Checklist Below
You've been added to The Product Economist briefing. Here's the checklist as promised.
The R&D Audit Checklist
The 15 questions I ask in every $7,500 diagnostic engagement. These questions surface hidden capital risks, zombie features, and structural margin collapse before they become catastrophic.
What percentage of engineering time is spent on maintenance vs. new features?
Why this matters: If maintenance exceeds 40%, you may be approaching Technical Insolvency.
What is your Revenue Per Engineer (RPE), and how does it trend?
Why this matters: Declining RPE signals engineering capital misallocation — you're spending more but earning less per engineer.
Can you identify which features generate revenue and which are zombie features?
Why this matters: Most organizations can't. This means they're maintaining features that destroy value.
What is the fully-loaded cost per AI inference request?
Why this matters: AI features often have hidden variable costs that erode gross margins. The Cost of Predictivity compounds.
What is your Technical Insolvency Date?
Why this matters: The exact quarter when maintenance costs consume 100% of engineering capacity. Most companies don't know theirs.
What percentage of your "R&D spend" is actually maintenance OpEx?
Why this matters: The Innovation Tax — many companies report 50% R&D investment when 80% is actually maintenance.
Do your PMs own a P&L, or just a backlog?
Why this matters: PMs who don't understand their P&L make uninformed capital allocation decisions every sprint.
What is your DORA metrics profile (deployment frequency, lead time, failure rate, MTTR)?
Why this matters: DORA measures delivery speed. Pair with PDI to see if you're shipping fast toward insolvency.
How much of your production code was generated by AI, and what's its defect rate?
Why this matters: Vibe-coded applications accumulate hallucination debt — technical debt no one on the team fully understands.
Can you calculate the gross margin of each product line?
Why this matters: AI features introduce variable COGS. Without per-product margin visibility, you may be scaling losses.
What would happen if you removed your 10 least-used features tomorrow?
Why this matters: The Kill Switch Protocol typically recovers 20-40% of engineering capacity from zombie features.
Do you have a model right-sizing strategy for AI features?
Why this matters: Using a frontier model for every request is like using a Ferrari for the mailbox. Right-sizing cuts AI costs 60-80%.
What is the accuracy-cost curve for your critical AI features?
Why this matters: Going from 80% to 95% accuracy often costs 10x more. The Cost of Predictivity must be modeled before commitments.
Is your engineering organization structured around products or projects?
Why this matters: Project-based teams ship and move on. Product-based teams own the outcome. The P&L impact is dramatic.
If a PE firm audited your engineering organization today, what would they find?
Why this matters: Technical Due Diligence reveals hidden liabilities. Better to find them yourself than have an acquirer negotiate them down.
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