A Series A investor sent their technical DD request on a Monday with a two-week deadline. The founder — a first-time technical CEO who had shipped the product himself — had never been through the process. He shared the request with us on Tuesday morning. What followed was fourteen intense days that exposed gaps neither of us had fully anticipated, and ultimately resulted in a clean term sheet with one minor remediation clause.
Technical due diligence at Series A is not a code review. It is a structured risk assessment: can this technology scale to the growth the investor is funding, does it have exploitable vulnerabilities that could become liabilities, and is the team capable of maintaining and extending it? The preparation work is about demonstrating credibility, not perfection.
What Technical DD Actually Covers
Investor technical DD typically spans four domains. First, architecture review: does the system design support the projected growth trajectory, or will it require expensive re-platforming at scale? Second, security posture: are there known vulnerabilities, open attack surfaces, or compliance gaps that create legal or reputational risk? Third, code quality and maintainability: is this a codebase one engineer can understand and extend, or has it accumulated debt that makes it brittle? Fourth, team capability: does the engineering team have the depth to execute the roadmap they have committed to?
The investor typically engages a specialist firm to conduct the review over two to four weeks. They will request repository access (often read-only via GitHub), infrastructure documentation, architecture diagrams, and access to staging environments. They may conduct interviews with the CTO and one or two senior engineers. The output is a risk-rated report with findings categorised as blockers, major concerns, and minor observations.
Blockers are rare but devastating: active security vulnerabilities, hardcoded credentials in the repository, no backup strategy for the production database. Major concerns slow the deal: poor test coverage, undocumented architecture, reliance on a single engineer. Minor observations are noted but rarely change the outcome. Understanding this hierarchy helps founders prioritise preparation correctly.
DD Risk Categories
- Blockers: active security vulnerabilities, hardcoded secrets, no data backup
- Major: poor test coverage, single point of failure, undocumented critical paths
- Minor: inconsistent naming, missing docstrings, outdated dependencies
Architecture and Scalability Review
The architecture question investors are really asking is: does this system need to be rebuilt before it reaches the revenue milestones we are funding? A monolith running on a single server serving ten thousand daily active users is fine. The same architecture serving ten million daily active users with no clear migration path is a risk. Investors want to see that you have thought about the path to scale, even if you have not executed it yet.
The most common architecture finding at Series A is that the database is the bottleneck: no read replicas, queries that will not survive a 10× traffic increase, no pagination on list endpoints that will eventually return millions of rows. These are not hard problems, but they need to be on the roadmap with a credible plan. Reviewers will look at your slowest database queries, your connection pooling configuration, and your caching strategy.
Document your architecture before the DD request arrives. A simple diagram showing the major components, how data flows between them, and where the stateful boundaries are will save hours of explanation during the review. If you do not have one, producing it during the two-week window is time well spent — it forces clarity on decisions that may not have been explicitly made.
Security and Compliance
Security findings are the most likely blockers in technical DD. The review will check whether secrets are in the codebase — run git log --all -S "secret" and similar searches before the reviewers do. Check for hardcoded API keys, database passwords, JWT signing secrets, and webhook verification tokens across the entire git history, not just the current HEAD.
Dependency vulnerability scanning is routine. Run a tool like Dependabot, Snyk, or OWASP Dependency-Check on your entire dependency tree and address any critical CVEs before the DD window. Many investors now use automated tooling that flags open CVEs in the first pass — walking in with clean dependency scans removes one category of finding entirely.
If your product handles personal data, the reviewer will ask about your data handling practices. Where is data stored? How is it encrypted at rest and in transit? What is your backup strategy and recovery time objective? Do you have a process for responding to data subject access requests? These questions are not about whether you have achieved SOC 2 compliance — they are about whether you have thought seriously about data responsibility.
Code Quality and Technical Debt
The most common major finding at Series A is a test coverage gap: a production codebase where less than 20% of code paths are covered by automated tests. Low test coverage does not mean the software does not work — it means that future changes carry high regression risk, and the next engineer who touches the codebase cannot be confident their changes are safe. Investors have funded companies where a single failed deployment wiped out a week of user data.
Before the DD window, establish test coverage measurement and add it to your CI pipeline. You do not need to get to 80% coverage in two weeks — you need to demonstrate that you understand the problem and have a concrete plan. A test coverage dashboard showing improvement over the past month is more credible than a one-week sprint to 40% before the reviewers arrive.
Code documentation matters more than founders expect. The reviewer is not looking for every function to have a docstring. They want to understand the architecture by reading the code — meaningful variable names, clear module boundaries, and README files that explain how to run the system locally. If your README is empty, write one. If your local development setup requires tribal knowledge, document it.
A Realistic Two-Week Preparation Plan
Week one priorities: rotate all secrets and move them to a secrets manager, run dependency vulnerability scans and patch critical CVEs, write or update your architecture documentation, and add test coverage measurement to CI. These are the high-impact, low-regret actions that address the most common blocker and major findings.
Week two priorities: prepare your infrastructure documentation (what runs where, disaster recovery process, backup strategy), brief your senior engineers on the interview questions they are likely to face, and do a self-review of your own codebase from the perspective of someone seeing it for the first time. Fix the embarrassing issues — the TODO comments that have been sitting for six months, the endpoint with no authentication, the log statement that prints a user email.
Do not try to hide problems from the reviewer. If you have a known scalability issue that you plan to address post-funding, write it up clearly in your architecture documentation with your proposed solution and timeline. A documented known issue with a credible plan is a minor observation. An undocumented known issue that the reviewer finds independently is a major concern — and raises questions about whether there are other problems you have not disclosed.
