Short answer: An automated first-pass edit adds the most value when a workflow has clear rules to enforce, meaningful consistency stakes, and a human reviewer who will act on the output. The ARC framework — Actionable, Rules, Consistency stakes — is a quick test for assessing fit.
At first, an AI that can do a reliable first-pass edit sounds incredible for almost every situation. But workflows vary, and document review comes in many forms. An automated first pass adds enormous value in some situations and less in others.
Before you build it into your workflow, this article outlines a simple framework that helps you determine whether an automated first-pass edit will add value to your work.
What is the ARC Framework for evaluating first-pass editing?
The framework consists of three questions to ask yourself about your work.
A — Actionable: is there a reviewer who will actually use the output?
An automated first pass creates more value when there’s a person who can act on it — reviewing tracked changes, accepting or rejecting edits, or making informed decisions. If you’re looking for a completely automated solution that cuts people out of the process, a first-pass editing tool may help to avoid some of the worst mistakes, but it won’t be a complete solution.
R — Rules: do you have a style guide with clear, binary rules?
Some guides consist of general writing guidance. That’s not the same as having clear rules. This part of the framework is about whether there are binary, auditable rules — such as terms that are always capitalised, abbreviations that shouldn’t be used, or spelling that follows a specific list. The more of these rules exist, and the more precisely they are specified, the more value an automated first pass can add.
C — Consistency stakes: does variation make a difference?
Using incorrect terminology in an internal email is different from using it in a proposal document with hundreds of millions at stake. Consistency stakes are amplified by volume and repetition. A short document with one author has lower stakes than a long document with many contributors, or a stream of documents going to the same audience.
Consider all three and then ask: to what extent does your workflow have ARC? If it’s strong on all three, a first pass offers enormous value. If it’s weak on one, the value is less. If it’s weak on all three, the value may be close to zero.
Applying the ARC Framework: a spectrum
The three parts of the ARC framework suggest that value is based on the nature of the work, the rules that govern it, and the structure of the team reviewing it.
The spectrum below provides examples from lowest to highest value. The framework is broad and there will be exceptions within each category.
| Possible value | Document type | What drives the assessment |
|---|---|---|
| Minimal | Fiction with no house style | The review work is probably weighted more toward judgment than rule-following. Many decisions may serve the author’s voice in ways that make rule enforcement less relevant or potentially counterproductive. There may be few clear rules to enforce. Basic proofreading catches, while real, tend to offer a relatively thin return in a workflow that leans heavily on human judgment. |
| Low | Literary fiction with light style conventions | A publisher may have some preferences. The editor’s role is more often about voice and structure than consistency enforcement. The risk of automation is that applying ‘correct’ usage may sand down intentional idiosyncrasy. |
| Low–moderate | One-off documents, no ongoing relationship | A short report or email may offer limited room for house style enforcement to add value. Without a downstream reviewer to act on the output, the gains can be modest relative to the overhead of using the tool for a one-off. Basic proofreading still adds something, but the return tends to be smaller here. |
| Moderate | Non-fiction with a publisher style guide | Where a style guide has clear rules, there is more for a first pass to do. The efficiency gain with one person is not as high as with multiple people and more documents. |
| Moderate–high | Academic or scientific journals | More detailed style guides, author–editor–reviewer chains, and consistent document structures tend to increase the value of a first pass. Output may be handed to a reviewer as a useful starting point. Consistency across documents is more likely to affect credibility here, and the cost of inconsistency can be higher. |
| High | Recurring corporate content with a house style | A team producing regular content against a shared style guide tends to benefit more, as the natural tendency for usage to vary across authors over time is picked up. Moreover, volume can create compounding value. |
| Very high | Legal and regulatory documents | More defined rules and style requirements, and formal review workflows tend to make a first pass more valuable. The style guide tends to be non-negotiable, volume is high, and inconsistency may carry legal or reputational cost. In these contexts a first pass contributes to risk reduction as much as efficiency. |
| Maximum | Large organisations with multiple departments, shared style standards, and AI-generated content in the workflow | Where content is produced at scale across several teams or departments, each using their own AI tools and prompts, consistency tends to erode without a dedicated enforcement layer. Different models, different drafting habits, and different interpretations of the same style guide pull in different directions over time. A first pass applied consistently across that output may do more here than in almost any other context — not because each individual document is more complex, but because the volume and variety of sources makes drift harder to detect and correct manually. |
Finding your bottleneck
The ARC framework is also useful for diagnosing partial fits — situations where the value is real but something else is getting in the way.
Bottleneck: Actionability (no structured reviewer)
The first pass can still catch errors, but the gains are less than they could be. The question to ask is whether the workflow could be adjusted to include a human review step, even a light one. If not, the value may remain modest however good the tool is.
Bottleneck: Rules (thin or vague style guide)
The best investment may be the style guide itself before the tool. Forming a committee to build out the style, or trusting it to a motivated individual or an independent editor, can solve this. Sam Enslen at Dragonfly Editorial has presented on this topic to ACES and can help. Once your rules are in place, manual house style enforcement vs FirstEdit covers the next question: how to enforce them reliably.
Bottleneck: Consistency stakes (one-off or low-stakes documents)
Consider whether there is a subset of documents that need more attention. Systematic first-pass automation is more useful for certain document types within an organisation than others. The tool may earn its place for higher-stakes documents even where it adds little for routine ones.
The limits of the framework
There are also situations where the framework simply doesn’t apply, regardless of where a workflow sits on the spectrum.
- Organisational AI policies. Some organisations have policies that restrict or prohibit the use of AI tools altogether. Where policy prohibits AI tools, the framework does not apply regardless of where the workflow sits on the spectrum.
- Partial-document workflows. Some organisations may want to apply a first pass to part of a document rather than the whole thing — a contract where only the boilerplate sections need style enforcement, or a report where the executive summary will be scrutinised closely but the appendices less so. These partial-use cases are real, and no framework built around whole-document workflows will map onto them perfectly.
Which Workflows Benefit Most from an Automated First-Pass Edit?
The two ends of the framework have the clearest conclusions.
If your work sits toward the low end — or if you recognise one of the exceptions above — that is useful information. Knowing where a tool doesn’t fit is as valuable as knowing where it does.
If your work sits toward the high end, with clear rules, meaningful stakes, and a reviewer who will use the output, the case for an automated first pass is likely worth exploring. For a full explanation of how an automated first pass works in practice and what it can and cannot handle, see the future of editing starts with an automated first pass.
In any case, the cost of evaluation is low. You can test documents for free with FirstEdit. Run one of your documents through it to see the benefit, then build it into your workflow if the added value is there.
FirstEdit is designed for the high end of this spectrum. It enforces your house style rules, under-edits by design, and returns every change as a tracked edit for human review. If your workflow has ARC, it’s worth seeing what a first pass looks like on your own documents. Join the waitlist →
Frequently asked questions
ARC is a three-question framework for assessing whether an automated first-pass edit will add value to a document workflow. It asks whether the output is Actionable (is there a reviewer?), whether there are clear Rules (is there a determinate style guide?), and whether there are meaningful Consistency stakes (does variation matter?).
Apply the ARC test. If you have a human reviewer who will act on tracked changes, a style guide with clear rules, and a context where consistency matters — across documents, over time, or with significant stakes — your workflow is likely a very strong fit. If one or more of those is missing, the value is lower but may still be significant.
Generally it adds less value for fiction, particularly where there is no house style. The editing work is more heavily weighted toward judgment than rule-following, and there may be few clear rules to enforce. Basic proofreading still applies, but the overall return is likely to be more modest.
The ARC framework assumes AI use is permitted. Where organisational policy prohibits AI tools, the framework does not apply regardless of where the workflow sits on the spectrum. If your organisation restricts (but does not prohibit) AI use, the framework can still be applied.
A first-pass edit is deliberately limited: it applies high-confidence, rule-based corrections and under-edits rather than over-edits. A full AI edit attempts to rewrite or improve the document more broadly. First-pass editing is designed to support human reviewers, not replace them. Every change is returned as a tracked edit for human approval.
A first-pass edit applies your organisation’s specific house style rules — capitalisation, terminology, hyphenation, abbreviations — consistently across a document before human review begins. This reduces the time reviewers spend on mechanical corrections and lets them focus on substance, tone, message, and impact.