Engineering Alpha in Private Equity
A podcast about how software engineering, data science and AI create operational alpha in PE-backed companies. Paul Karner, PhD, founder of Horizon Data Partners, and Dave Mangot, author of DevOps Patterns for Private Equity, talk through the research, the news and the hard numbers with operating partners, CTOs and researchers.
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All episodes
Episode 19 ·
Agentic Software Factories: Specialist Agents, Cutting Cloud OPEX, and Protecting Production
When AI makes code fast to write, every other stage of delivery becomes the bottleneck. Paul and Dave look at OpenAI's internal agentic software factory and what it means for cloud costs and production stability.
Related service: AI-ROI Assessment
Episode 18 ·
Rethinking Incentives: (AI)ms vs. Goals and the Economics of Experimentation
Local targets like story points and commit volume create perverse incentives once AI enters R&D. An economist's look at aims versus goals, and at experiments that measure real results.
Related service: AI-ROI Assessment
Episode 17 ·
The New Calculus of Buy vs. Build: Claude Code, Undifferentiated Heavy Lifting, and Slashing COGS
With code cheaper to write, deal teams are re-examining SaaS subscriptions. Why code generation is a small part of the cost of owning software, and how to make the buy-or-build call on the P&L.
Episode 16 ·
Meta's Experiment: Why You Can't Outsource System Ownership to AI
Meta shrank engineering teams around AI agents. Commits rose 220%, but only 36% reached production and incidents rose 40%. What that means for boards targeting engineering headcount.
Related service: AI-ROI Assessment
Episode 15 ·
The Developer Productivity Viper Pit: Why DevEx Is Your Real EBITDA Driver
Why lines of code, velocity points and pull-request times mislead boards measuring engineering productivity, and why the coordination work those tools ignore matters.
Related service: AI-ROI Assessment
Episode 14 ·
Engineering Alpha Internally: Burning the Ships and the '30-Hour Analyst' Dividend
Jarrad Berman, Partner in TZP Group's Portfolio Growth Group, on how the firm rebuilt its own deal team's work around AI instead of manual spreadsheets.
Episode 13 ·
The 15x Fallacy: Why Coding Speed Isn't Your AI Bottleneck
Michael Frendo, CTO of New Relic, on why a 5x increase in coding speed yields about a 15% overall efficiency gain, and what leading a thousand-person engineering organization through AI has taught him.
Related service: AI-ROI Assessment
Episode 12 ·
Doing Math on Opinions: Why Bug Counts Aren't Science
Elisabeth Hendrickson, former VP of R&D for Data Products at Pivotal, on why bug counts mislead boardrooms, and how software quality reaches EBITDA through churn and outages.
Episode 11 ·
3 a.m., the 2x Productivity Cap, and the Ceiling of AI Automation
Teams trained on AI hit a 2x productivity cap: code gets written faster but not shipped. The systemic changes, such as platform engineering, that lift the ceiling.
Related service: AI-ROI Assessment
Episode 10 ·
The 85% Inventory Trap: What 28 Million Workflows Reveal About AI ROI
CircleCI's 2026 report shows code throughput up 59% with AI, but 85% of the new code stuck in feature branches. That is inventory, not operational alpha.
Related service: AI-ROI Assessment
Episode 9 ·
The AI "Hoax," Economic Accounting, and Nobel-Winning ROI
Nobel laureate Daron Acemoglu argues AI's productivity gains are harder to reach than promised. Paul explains "economic accounting": what a company could achieve without AI, just by fixing its data, workflows and engineering foundations.
Related service: Data and AI readiness assessment for PE due diligence
Episode 8 ·
Token Economics, Data Moats, and the Future of Tech Due Diligence
Dan Bender, Kirby Montgomery and Jason Langenauer of the tech due diligence firm Code & Co. on how AI has changed diligence: token costs that erode gross margins, proprietary data as the remaining moat, and AI skepticism as an investment risk.
Related service: AI-ROI Assessment
Episode 7 ·
Double-Speed Baseball and the New SaaS Multiple
Why agentic proficiency is the new equivalent of the SaaS multiple: AI agents lower the marginal cost of delivering software, and daily deployment is the prerequisite for getting more at-bats in the market.
Related service: AI-ROI Assessment
Episode 6 ·
The 'Maintenance Window' Red Flag & The AI Death Spiral
A software company that still releases in maintenance windows has a delivery problem. Why that matters to operating partners evaluating an acquisition, and why forcing AI into a slow-deploying organization doubles its costs.
Related service: AI-ROI Assessment
Episode 5 ·
The AI Amplifier Effect & Why Rework Is Killing Your EBITDA
Nathen Harvey, who leads Google Cloud's DORA research program, on DORA's findings about AI: it amplifies whatever delivery capabilities a company already has, and speeding up code generation without fixing bottlenecks reduces output.
Related service: AI-ROI Assessment
Episode 4 ·
Measuring the ROI of Tech Transformations
How to prove a technology transformation is working, using a portfolio company that automated manual document review with machine learning: start from the financial goal, and tie operational data to timekeeping and the ERP.
Related service: Technology and AI ROI measurement for portfolio companies
Episode 3 ·
Uber COO Questions Tokenmaxxing
Uber's COO says AI token spending is getting harder to justify while hiring slows to pay for it. Why heavy token use often produces stranded inventory rather than revenue, and why cutting engineers before AI proves its ROI is a mistake.
Related service: AI-ROI Assessment
Episode 2 ·
Finding "Free EBITDA" in Cloud Contracts & The AI Optionality Playbook
The wave of partnerships between cloud vendors and PE firms, starting with Thoma Bravo and Google Cloud: enterprise cloud agreements as an immediate cost lever, and why keeping options open matters in an uncertain AI market.
Episode 1 ·
What's Engineering Alpha & Why You Can't Just Rub AI on It
The first episode: what engineering alpha means for middle-market PE, why operational excellence inside engineering drives returns, and why AI without the right foundations amplifies problems rather than profits.
Related service: AI-ROI Assessment