3-1: Technical Due Diligence Red Flags
Exposing hidden technical risks that destroy M&A enterprise value.
🎯 What You'll Learn
- ✓ Spot legacy code rot
- ✓ Audit key person dependencies
- ✓ Evaluate architecture scaling ceilings
- ✓ Assess AI lock-in risks
Lesson 1: Valuing Technical Debt in Deals
A target company with $10M ARR looks great until you realize their codebase is 15 years old and moving to the cloud will cost $2M in R&D. That $2M must be subtracted from the enterprise valuation.
The capital required post-close to modernize.
Dependencies on deprecated frameworks (e.g. Angular 1).
Quality of Technology assessment delivered to the deal team.
Run a simulated QoT evaluation on a target architecture diagram, identifying three severe PDI flags.
Lesson 2: Key Person Dependency
If the company relies on one Senior Architect who holds all system knowledge in their head, the asset is immensely fragile. If they quit post-acquisition, the value drops to zero.
The number of people who can securely operate the system.
Is the system architecture codified or tribal knowledge?
Ensuring the core technical team is tied to the earn-out.
Assess the key person risk in a due diligence data room based on their git commit history distribution.
Lesson 3: Architecture Scaling Ceilings
The code works at 1,000 users. Will it work at 100,000? Investors pay for future scale. Identify monolithic bottlenecks and database deadlocks that will require ground-up rewrites.
Can the data tier scale horizontally?
Can the application tier auto-scale?
Is the edge network protecting the origin servers?
Examine an infrastructure topology bill (AWS report) to determine if the target company is scaling efficiently.
Continue Learning: Track 3 - PE / VC / Investor
2 more lessons with actionable playbooks, executive dashboards, and engineering architecture.
Access Execution Fidelity.
You've seen the theory. The Vault contains the exact board-ready financial models, autonomous AI orchestration codes, and executive action playbooks that drive 8-figure valuation impacts.
Executive Dashboards
Generate deterministic, board-ready financial artifacts to justify CAPEX workflows immediately to your CFO.
Defensible Economics
Replace heuristic guesswork with hard mathematical frameworks for build-vs-buy and SLA penalty negotiations.
3-Step Playbooks
Actionable remediation templates attached to every module to neutralize friction and drive instant deployment velocity.
Engineering Intelligence Awaiting Extraction
No generic advice. No filler. Just uncompromising architectural truths and unit economic calculators.
Vault Terminal Locked
Awaiting authorization clearance. Access the module to decrypt architectural playbooks, P&L models, and deterministic diagnostic utilities.
Module Syllabus
Lesson 1: Lesson 1: Valuing Technical Debt in Deals
A target company with $10M ARR looks great until you realize their codebase is 15 years old and moving to the cloud will cost $2M in R&D. That $2M must be subtracted from the enterprise valuation.
Lesson 2: Lesson 2: Key Person Dependency
If the company relies on one Senior Architect who holds all system knowledge in their head, the asset is immensely fragile. If they quit post-acquisition, the value drops to zero.
Lesson 3: Lesson 3: Architecture Scaling Ceilings
The code works at 1,000 users. Will it work at 100,000? Investors pay for future scale. Identify monolithic bottlenecks and database deadlocks that will require ground-up rewrites.
Explore Related Economic Architecture
Foundational Research & Empirical Studies
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.
The AI Economist: Leading Product Strategy When Build Costs Approach Zero
When generative AI collapses the cost of writing software toward zero, developer bandwidth ceases to be the constraint. The product bottleneck shifts from managing backlog velocity to managing uncertainty, evaluating system architecture efficiency, and preserving unit margins as a Product Economist.
When the Cost of Writing Software Approaches Zero, Traditional Product Management Frameworks Break Down
When generative tools collapse the marginal cost of writing software toward zero, developer capacity ceases to be the constraint. The product bottleneck shifts from managing backlog velocity to managing uncertainty, evaluating system architecture efficiency, and preserving unit margins as a Product Economist.
Hey, Senior PMs: Shipping Faster Won’t Get You Promoted
Shifts product management focus from feature output to margin contribution and P&L ownership.
Want to apply this to your organization with Technical Due Diligence Red Flags?
Run a free diagnostic first. If the numbers concern you, book a session to build a remediation plan.
Richard Ewing: AI Economist & Capital Auditor