English for Writing a Technical Due Diligence Summary

Technical due diligence reports get read by people making a decision — an investment, an acquisition, a major vendor contract — often without deep engineering context. The English needs to translate code-level observations into risk statements a non-engineer can act on, without either overstating or hiding real problems. This guide covers the structure and phrasing for writing that report.

Key Vocabulary

Risk rating — a categorized severity level (e.g., low/medium/high, or critical/major/minor) assigned to each finding, used so a non-technical reader can prioritize without needing to understand the technical detail fully. “We rated the lack of automated testing as a medium risk — it doesn’t block near-term operation, but it will slow down any team taking over this codebase.”

Technical debt inventory — a structured list of known shortcuts, outdated dependencies, or deferred fixes in a codebase, framed by their cost to address rather than just described. “The technical debt inventory includes an outdated authentication library (estimated 2-week migration), a monolithic deployment process (estimated 1-month investment to modernize), and inconsistent error handling across services (ongoing cost, harder to estimate precisely).”

Bus factor — the number of people whose departure would put a project at serious risk, because critical knowledge isn’t documented or shared; a bus factor of one is a common and significant finding. “The payments integration has a bus factor of one — a single engineer holds undocumented knowledge of how the reconciliation process works, and there’s no written runbook.”

Remediation estimate — a rough time or cost estimate for addressing a finding, included so the reader can weigh the finding against the deal or decision at hand. “Remediation estimate for the missing CI pipeline: roughly 3-4 engineer-weeks to bring this codebase to the standard we’d consider production-ready.”

Blocking vs. non-blocking finding — a distinction stating whether a finding should stop or delay the decision entirely, versus one that’s a known cost to factor in but doesn’t require stopping. “We consider the lack of a disaster recovery plan a non-blocking finding — it’s a real gap, but a reasonable one to address post-acquisition rather than a reason to halt the deal.”

Common Phrases

• “We rate this finding as [risk level] because [specific reasoning].”
• “Remediation estimate: [time/cost], based on [comparable work].”
• “This is a blocking/non-blocking finding for the purposes of this evaluation.”
• “Bus factor for [system/component]: [number], due to [reason].”
• “In summary, the codebase is [overall assessment], with the primary risks being [top 2-3 items].”

Example Sentences

Opening a due diligence summary with a clear top-level assessment before the detail: “Summary: the codebase is functional and actively maintained, with reasonable test coverage on core paths (approximately 65%). The primary risks are a bus factor of one on the payments integration, an outdated and unsupported version of the core framework, and the absence of any documented incident response process. None of these are blocking, but all three should be addressed within the first two quarters post-acquisition.”

Writing a finding with risk rating, reasoning, and remediation estimate together: “Finding: the application currently runs on Node.js 14, which reached end-of-life in April 2023 and no longer receives security patches. Risk rating: high — this is an active security exposure, not a hypothetical one. Remediation estimate: 2-3 weeks for the upgrade itself, though dependent libraries may require additional compatibility work.”

Describing a bus factor finding without assigning blame: “The recommendation engine has a bus factor of one. This isn’t a reflection on the current team’s practices — the system was built under significant time pressure during an earlier growth phase — but it does represent real risk: if this engineer were unavailable, no one else on the team could currently debug or modify this system with confidence.”

Distinguishing a blocking finding from a non-blocking one in the same report: “We consider the lack of automated deployment a non-blocking finding — manual deploys are inconvenient but functional. We consider the absence of any access control audit trail for the production database a blocking finding for a company handling financial data, and recommend addressing this before finalizing the acquisition.”

Professional Tips

• Always pair a risk rating with specific reasoning — “high risk” alone is an opinion; “high risk because this is an active, unpatched security exposure” is a claim the reader can evaluate.
• Include a remediation estimate for every significant finding — a reader making a decision needs to weigh the cost of fixing something, not just know that it’s broken.
• Use “bus factor” deliberately when describing knowledge concentration risk — it’s precise, standard terminology that avoids sounding like you’re criticizing an individual.
• Explicitly mark findings as blocking or non-blocking for the decision at hand — this is often the single most useful sentence in the entire report for a reader trying to act on it quickly.
• Open with a top-level summary before the detailed findings — a busy decision-maker may only read the first paragraph, so it needs to stand alone.

Practice Exercise

1. Write a due diligence finding with a risk rating, reasoning, and remediation estimate.
2. Write a bus factor finding that describes the risk without assigning blame to an individual.
3. Write two sentences distinguishing a blocking finding from a non-blocking one in the same hypothetical report.

Navigating Nuance: Common Pitfalls for Non-Native Speakers

Writing a technical due diligence summary – particularly one demanding precise language – can be daunting at any stage of your career. For developers whose first language isn’t English, the subtle nuances of professional phrasing and common idioms can create significant hurdles. It’s not simply about translating words; it’s about conveying meaning with clarity, confidence, and a level of technical authority that resonates with reviewers and stakeholders. A seemingly minor word choice can dramatically alter the perceived risk or opportunity associated with a project or technology. Let’s consider some frequent challenges and how to approach them strategically.

One persistent issue is using overly literal translations. For example, directly translating “bug” from another language might result in describing a problem as “defect,” which subtly shifts the connotation. While technically accurate, “bug” carries an immediate sense of urgency and often implies user-facing impact – something you want to clearly communicate. Similarly, phrases like “to fix” can sound overly simplistic when discussing complex architectural issues. Instead, consider phrasing such as “to remediate” or “to address” which demonstrate a more thorough understanding of the underlying cause. Pay close attention to verbs; their selection significantly impacts your tone and perceived expertise.

Another common difficulty arises with expressing degrees of certainty. Native English speakers frequently use modal verbs like “should,” “could,” and “might” to soften statements and acknowledge potential uncertainties, especially when evaluating a vendor’s roadmap or the quality of documentation. A statement like “The API should be well-documented” is less assertive than “The API documentation is expected to cover…” This difference is crucial in due diligence – demonstrating careful analysis rather than making definitive declarations based on limited information. Remember, acknowledging uncertainty isn’t a weakness; it’s a sign of responsible assessment.

Finally, mastering the conventions around describing technical debt and legacy systems is essential. Phrases like “old code” or “legacy system” can be perceived negatively. It’s better to frame them with objective descriptions: “The codebase exhibits characteristics consistent with established patterns of technical debt related to [specific area]” or “The architecture reflects decisions made prior to the adoption of [modern practice], presenting opportunities for optimization.” Focusing on measurable aspects – lines of code, complexity metrics, adherence to standards – provides a more robust and defensible argument than subjective judgments.