Preparing for Technical Due Diligence: The Founder's Complete Guide

You've closed the negotiation round with an investor, agreed on all terms, and it seems like the money is almost in the bank. Then the investor says: "Great, now it's time to conduct technical due diligence."

For many founders, especially those going through this procedure for the first time, these words sound like a sentence. Not because there's something wrong with the product, but because no one explained what exactly will be checked and how to prepare for it.

I've seen deals fall apart at this stage, I've seen company valuations drop by 30-40% after the investor's technical consultants found "pitfalls." But I've also seen well-prepared teams pass due diligence in a week without a single question.

The difference is in the preparation.

What is Technical Due Diligence and Why Is It Needed

Technical Due Diligence (TDD) is an independent assessment of the technical side of your product. Investors want to understand what they're investing money in: how reliable the architecture is, whether the system can scale, what risks are hidden in the code and processes.

It's important to understand: the goal of TDD is not to check the code - perfect code simply doesn't exist. The goal is to assess technical risks and understand whether the team can handle the challenges that are inevitable during growth.

Investors are looking for answers to four key questions:

Does the team understand its technical debt? Every product accumulates compromises and "hacks." A mature team knows about them, tracks them, and has a plan to eliminate them. An immature team either denies their existence or doesn't understand the scale of the problem.
Does the architecture scale for the next 2-3 years? What works for 1,000 users often falls apart at 100,000. Investors want to make sure the foundation can handle the growth they're paying for.
Can the engineering team grow from 10 to 50+ people? This isn't just about hiring. Does the architecture allow teams to work independently? Do processes scale? Will engineering culture break down with rapid growth?
Are there any pitfalls? Critical security vulnerabilities, licensing violations, dependence on one person who "knows how everything works" - all of this can collapse after the deal closes.

When to Expect Technical Due Diligence

TDD is usually conducted in the following situations:

Series A and higher funding rounds. In seed rounds, investors more often rely on the team's reputation. But starting with Series A, when amounts become significant, technical audit is standard practice.
M&A deals. When acquiring a company, the buyer wants to understand exactly what they're acquiring. This is where particularly deep and detailed TDD is conducted.
Strategic partnerships. Large companies may request a technical audit before integrating with your product.
Internal preparation. Smart founders conduct self-audits before investors start asking questions. This allows fixing critical issues in advance and confidently conducting negotiations.

Anatomy of a Technical Audit: What Will Be Checked

Experienced technical consultants assess not only code. They need to see the whole picture: architecture, processes, team, infrastructure. Let's break down the key areas.

Architecture and Domain Boundaries

The first thing they look at is how the code is organized at a high level. Is there a clear separation between business logic and technical infrastructure? How is responsibility distributed among system components?

Examples of red flags:

Business logic is spread across controllers, services, and the database layer
Direct database access from UI
Spaghetti architecture, "everything is connected to everything"
Shared database tables between different business contexts

When business logic is intertwined with technical implementation, each new feature takes more and more time. Worse, you can't scale the team. New engineers break existing functionality because there are no clear domain boundaries. And this problem grows exponentially.

Data Ownership and Database Coupling

Who owns which data? Can multiple services write directly to the same tables?

Examples of red flags:

Multiple services write to the same tables
A shared schema that different teams modify without clear ownership
Microservices using one database
Direct cross-service queries to foreign tables

This is the number one reason why companies can't scale engineering teams. When data doesn't have a clear owner, you can't deploy services independently, can't scale them separately, can't assign owners. One team's database change breaks another team's code.

Deployment Rollback Capability

If a deployment causes problems in production, how quickly can you roll back? Can you roll back database changes?

Examples of red flags:

"We've never rolled back"
Database migrations can't be rolled back
Rollback requires manual actions or "someone who knows what and how"
No automated rollback process
Deployment takes more than two hours

Without the ability to quickly roll back, each deployment is Russian roulette. A production problem can stop revenue for hours. If there are problems with rollback processes, such companies deploy less often, release slower, and lose competitive advantage.

Synchronous and Asynchronous Communication

How do different parts of the system communicate with each other? When one service needs to notify another, how does it happen?

Examples of red flags:

Everything is built on synchronous HTTP calls
"User clicks a button, and 5 services must respond before the page loads"
No message queue or event bus
Timeout issues where one service slows down the rest
Cascading failures - one service falling brings down all

Synchronous coupling means: slow services make everything slow, and one service failing cascades to the rest. You can't scale services independently. User experience degrades.

Technical Debt

What are the three main elements of technical debt preventing scaling? What's the plan to eliminate them?

Examples of red flags:

"We have no technical debt at all"
No documented technical debt backlog
Critical parts of the system with comments "Don't touch this code"
New feature development takes much longer than it should
The team can't explain why technical debt appeared

Technical debt exists absolutely in every codebase, but the question is whether the team understands it, tracks it, and has a plan to eliminate it. Untracked debt means the team is either lying or doesn't understand its own system - both variants are dangerous.

Medium and High-Risk Areas

In addition to critical elements, auditors assess several other important areas.

Testing Strategy

"We have 80% code coverage with tests!" - sounds great until it turns out these are all integration tests that can't be run without a database and external services, and which take 30+ minutes to execute.

Test coverage percentage means nothing without understanding what exactly is being tested. Slow and fragile integration tests lead to developers not running them locally, and bugs make it to production.

Deployment Frequency

How often do you deploy to production? How much time passes from commit to production?

Deployment frequency directly correlates with development speed. Companies that deploy daily respond faster to customer needs. Long time from commit to deployment means features reach users weeks after the code is actually written.

Security

How are authentication and authorization organized? Who has access to production data?

Red flags here are critical and can potentially lead to deal cancellation: passwords in plain text or using weak MD5, API keys in version control, everyone having access to the production database, lack of audit logs for sensitive operations.

Security violations destroy companies. That's why it's important to maintain basic security hygiene - it's a necessary minimum. Investors walk away if passwords are discovered in plain text or API keys in GitHub.

Infrastructure as Code

How is your infrastructure defined? Can you recreate the production environment from scratch?

Manual infrastructure setup ("ClickOps") means each environment is unique. Recovery after failure is slow or impossible. Scaling requires manual work, new environments take weeks to create.

Maturity Indicators: What Distinguishes Strong Teams

There are elements that aren't critical but show a high level of engineering culture.

Documentation quality. Where is the architecture documented? How does a new engineer go through onboarding? Poor documentation means each new engineer becomes productive in 3-6 months, not a few weeks.
Feature flags and experiments. Can you roll out features gradually? Can you disable a feature without redeployment? Companies without feature flags deploy more cautiously, test less in production, and learn more slowly from user behavior.
Disaster recovery. What's the recovery plan after technical failures? How quickly will you recover from complete infrastructure loss? Disasters happen. The question isn't if, but when.
Team structure and areas of responsibility. How are teams organized? How is ownership of services and domains assigned? Conway's Law really works - system architecture reflects team structure. Companies that successfully scale align team responsibility areas with system boundaries.

Common Mistakes When Preparing for TDD

Mistake 1: Starting to Prepare After Investor Request

By this time, it's too late to fix serious architectural problems. You need to start preparing in advance; the best time to prepare is 3-6 months before the planned round. Conduct an internal audit, make a plan to eliminate critical problems, and start working.

Mistake 2: Trying to Hide Problems

Experienced auditors have seen hundreds of codebases - believe me, they'll find problems. Trying to hide them destroys trust and looks worse than the problems themselves.

The best strategy is to honestly acknowledge existing problems and show a plan to solve them. "Yes, we have technical debt in module X. Here's why it arose, here's our refactoring plan for next quarter" - this is an answer that builds trust.

Mistake 3: Lack of Architectural Decision Documentation

When an auditor asks "why did you choose this solution?", the answer "it happened historically" is a red flag. Document architectural decisions: what options were considered, why this one was chosen, what compromises were made.

Mistake 4: Dependence on One Person

"Only Sasha knows how this works" - a phrase that scares investors. It means bus factor: if Sasha leaves, critical knowledge leaves with them. Maintain documentation, organize knowledge sharing, eliminate single points of failure - yes, in people too.

Mistake 5: Ignoring Security Rules

Some security issues are absolute red flags. API keys in the repository, passwords in plain text, lack of basic authorization - all of this needs to be fixed before any conversations with investors.

How to Use the Checklist for Self-Preparation

I've prepared a detailed technical due diligence checklist that covers 20 key assessment areas. It's organized by risk level: critical, high, medium, and low.

For founders: use it to prepare for technical due diligence before conversations with investors. Go through each point, honestly assess the current state, make a plan for critical areas.

For CTOs and technical leaders: use it for regular self-audits. Once a quarter, go through the checklist and track progress.

The checklist includes:

Specific questions auditors ask
Red flags they pay attention to
Explanation of why each area is important for the business
Guide for assessing overall risk level

Download Checklist

Conclusion

Technical Due Diligence is not an exam you need to pass with flying colors. It's an honest conversation about risks and readiness to scale.

Even the best and most successful startups have red flags. The difference is they can explain why these problems exist and how they plan to solve them. The worst don't know what they don't know.

Preparing for TDD is not a one-time exercise before a round. It's a practice of constantly understanding the state of your technical foundation, tracking debt, and making informed decisions.

Start with the checklist above, conduct an honest self-audit, make a plan. And when the investor says "let's conduct technical due diligence" - you'll be ready.

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