How to Write Release Notes for Technical and Non-technical Audiences

Your engineering team just spent three months building a feature that solves a real customer problem. They shipped it on time. The product marketing team drafted the positioning. The changelog was updated, the product update email was sent, and the sales team was briefed.

Three weeks later, adoption is sitting at single digits.

The sales team can't pitch the feature because they don't understand what it actually does. The support organization is fielding tickets about the fix because they can't explain it to the customer who complained about it last quarter. Customer success has no idea how to tie the update to the pain point the client mentioned on their last call.

The release notes exist. They are technically accurate. They are comprehensive. And they are completely useless to anyone outside of engineering.

This is the reality for most software companies. The notes are written for engineers, by engineers. They document what changed in the codebase, not what changed for the user. And when non-technical stakeholders need to act on them, the communication breaks down.

Anyway. We have a translation problem.

The Translation Tax

When internal communication breaks down, so does productivity, engagement, and innovation. In software companies, these breakdowns derail product launches and divide teams.

The cost of poor documentation isn't just a few confused salespeople. It is a measurable drag on the organization. When release notes are vague or overly technical, they create a barrier to effective communication between development teams and users. Research studying 32,425 release notes across 1,000 GitHub projects found significant discrepancies between what release note producers think is important and what users actually need. The gap is structural, not accidental.

Someone has to translate the engineering output into business value. Usually, this falls on a product manager or a technical writer who is already under-resourced. They end up writing two versions of everything: one for the developers, and one for everyone else.

This doesn't scale. But the alternative, publishing notes no one outside engineering can parse, has a real cost in misalignment, duplicated questions, and missed opportunities.

There is a better way to structure this information so that it serves both audiences without dumbing anything down or requiring two separate documents.

Lead with the Outcome, Not the Implementation

Non-technical readers need to know what changed for the user and why it matters before they care how it works under the hood.

Start every release note with a single sentence that answers a basic question: what can someone now do that they couldn't do before, or what problem does this fix?

Use outcome-driven language for this summary, not feature-driven language.

"Customers can now export reports in PDF format" beats "Added PDF export functionality."

"This release fixes the timeout error that affected bulk uploads over 5GB" beats "Resolved issue in batch processing endpoint."

"Dashboard load times are now 3x faster for accounts with over 10,000 records" beats "Optimized database query execution."

"The v1 authentication endpoint will stop working on October 1st; migrate to v2 before then or your integrations will break" beats "Deprecated v1 authentication endpoint."

You get the idea. State the impact first. Then layer in the technical detail for the readers who actually need it.

Interaction designers have a concept called progressive disclosure: initially, show users only a few of the most important options, and offer a larger set of specialized options upon request. The same logic applies to documentation. The very fact that something appears at the top of a note tells readers it is important. Everything else is detail, and detail can wait.

The structure that follows from this is straightforward. The first sentence or two is the customer-facing summary: the outcome-driven statement that answers what changed and why it matters. Below that, a clearly marked technical explanation covers the mechanics for support agents and technical PMs who need to understand the fix. Below that, implementation details handle API changes, schema updates, and code-level specifics for the developers who need them.

The sales rep reads the first sentence and moves on. The support agent reads the first two sections to understand the fix. The developer reads the whole thing to update their integration.

Everyone gets what they need. One document, one source of truth, no translation required.

The Operational Reality of Doing This at Scale

Knowing how to structure a good release note doesn't solve the operational problem of actually writing them.

Many developers view writing release notes as a tedious and dreadful task. They want to write code, not documentation. And when they do write documentation, they write it for themselves. Documentation is frequently viewed as unnecessary overhead, and in fast-paced development environments, it gets deprioritized due to tight deadlines and a focus on delivering working code. The result is informal, hard-to-understand documentation that quickly becomes outdated as the software evolves.

You cannot ask your engineering team to manually write outcome-driven, progressively disclosed release notes for every minor update. They won't do it. And you cannot ask your product managers to manually translate every commit into business value. They don't have the time.

The solution is to define the structure once, and then generate the customer-facing layer consistently. That is where tooling fits. The system should do the translation work. The human should ensure it landed correctly.

The current generation of documentation tools can generate release notes directly from engineering artifacts: commit messages, pull requests, and issue titles. The challenge that existing tools have struggled with is audience personalization, which limits their relevance and conciseness. A tool that generates a single undifferentiated output has the same problem as the engineer writing the note manually: it optimizes for one reader.

The right model is generation plus validation. AI drafts the customer-facing summary and the technical detail as separate layers. A product manager or technical writer reviews the output, adjusts where the framing missed, and approves it. The human doesn't rewrite from scratch; they ensure the translation landed correctly. This is what makes the approach scalable without sacrificing accuracy.

Doc Holiday is built around this workflow. It generates release notes directly from engineering artifacts, with user-facing summaries and technical detail separated by default, and provides a review layer so the right person can validate the output before it ships. The structure is defined once. The generation is consistent. The human oversight is the quality check, not the bottleneck.

The result is release notes that work for every reader without requiring separate documents or doubling the workload. Non-technical stakeholders get clarity, technical stakeholders get precision, and no one has to maintain two versions of the truth.