Technical Due Diligence
Technical Due Diligence is the forensic evaluation of software architecture, technical debt, and team use prior to M&A.
“What you do not discover in technical due diligence, you will pay for ten times over in post-acquisition refactoring.”
Flawed technical due diligence leads to disastrous acquisitions where post-close value is wiped out by hidden technical debt, unmaintainable legacy spaghetti, catastrophic security vulnerabilities, or negative-margin AI compute COGS.
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Technical Due Diligence
Technical Due Diligence is the forensic evaluation of software architecture, technical debt, and team use prior to M&A.
Direct Relationships (3)
Transitive Neighbors (Connected via Hop 1)
Extended Causal Ripple Effects
Richard Ewing’s Research Thesis
Technical due diligence must forensic audit code quality, technical debt, and unit margins to protect investor capital.
Why This Specification Exists
Buyers overpay for software companies only to find the codebase is unmaintainable and requires a complete rewrite.
Superficial check-the-box questionnaires that do not inspect code or unit economics.
No standardized framework linking architectural health and Product Debt Index to financial valuation.
Forensic Technical Due Diligence connecting code audit findings directly to transaction valuation.
What Changes If You Believe This?
Acquiring engineering teams receive clear remediation roadmaps for post-merger integration.
Enables buyers to negotiate deal purchase prices based on verified technical liabilities.
Identifies which product modules are ready for enterprise scale and which need complete rewrites.
Identifies latent vulnerabilities, compliance non-conformities, and open-source license violations.
Recommended Action by Role
Require a forensic Product Debt Index audit before finalizing transaction valuation multiples.
Inspect target codebase for undocumented third-party AI APIs and license liabilities.
Verify whether R&D capitalization claims reflect durable software assets or unmaintainable zombie code.
Assess runtime carrying costs and infrastructure cloud debts during post-merger integration planning.
Technical Due Diligence Scorecard
Comprehensive audit scorecard for M&A technology evaluation.
Latest Publications & Research Activity
I Put AI Agents in Charge of My To-Do List. Here's What They Actually Took Off My Plate.
Testing autonomous AI agents across administrative, research, and software engineering chores proves that delegation does not eliminate workloads, but shifts human labor into an air traffic control supervisory review queue. While agents excel at bounded, easily verifiable technical tasks like CI pipeline monitoring, DOM contrast audits, and build validation, they fail silently with perfect syntax during complex database refactors and struggle with physical reality collisions and interpersonal nuance. Real productivity gains require four operational laws: start with read-only triggers, enforce narrow definitions of done, require human approval on external actions, and treat all output as junior drafts.
GitHub Copilot Is Generating More Code Than Your Team Can Review: Why Senior Engineers Are Now the Bottleneck
Identifies the review capacity crunch created when AI code generation outpaces senior engineering verification velocity.
In the Vibe Coding Era, What Does a Software Engineer Even Do?
Defines the 4 Laws of Probabilistic Software Development and the shift from code authoring to system verification.
When AI Writes the Code, What Skills Are Employers Hiring For?
Presents the 4 Dimensions of Engineering Judgment scorecard for evaluating software engineers in the AI era.
Frequently Asked Questions
Q:What is Technical Due Diligence?
A deep-dive investigation into a company’s technology stack, code quality, engineering processes, and infrastructure costs prior to an investment or acquisition.
Q:What are the biggest red flags in Technical Due Diligence?
High Product Debt Index, undocumented single-person dependencies, unmaintainable vibe coding spaghetti, unhedged AI token COGS, and unpatched security vulnerabilities.
Canonical Specification Origin
Technical due diligence protects capital by auditing architectural debt.
Corpus Interconnections
Richard Ewing artifacts developed around this canonical framework, including publications, execution tools, and diagnostic models.
External Adoption & Peer Citations
Documented instances where independent researchers, engineering teams, and publications have cited, implemented, or referenced this concept outside Richard Ewing’s ecosystem.
External Evidence: No independently verified references recorded yet.
This concept is part of Richard Ewing’s original baseline canon. External citations and implementations are added only upon rigorous empirical verification.
Inspectable Evidence Ledger
Classified evidence items supporting, extending, or refining this canonical research specification.
Recommended Citation
Ewing, R. (2026). "Technical Due Diligence." Richard Ewing Research Canon. Available at: https://www.richardewing.io/concepts/technical-due-diligence
@article{ewing_technical_due_diligence,
author = {Ewing, Richard},
title = {Technical Due Diligence},
journal = {Richard Ewing Research Canon},
year = {2026},
url = {https://www.richardewing.io/concepts/technical-due-diligence}
}