Sample Edits: What Are They
And Are They Truly Worthwhile?

Anyone with a decent grasp of
grammar can tweak a few pages

In an era overflowing with misinformation and unfounded claims, it’s no surprise that countless editors and consultants loudly promote “sample edits” as a reliable way to choose one over another. However, ManuscriptCritique’s Michael Garrett has pushed back against this approach for decades. But despite his warnings, they have often gone unheeded.

Even artificial intelligence echoes the same misguided advice; in fact, it often touts sample edits as a respectable benchmark for selecting a professional. So, Michael decided to challenge that notion directly by asking AI why it continues to recommend a practice that long, hard‑earned experience has proven to be fundamentally flawed. In response, the explanation AI delivered was, to its credit, remarkably candid.

Michael has spent decades as a professional book editor and critique consultant offering extensive free guidance here and elsewhere on this site. Yet, while sample edits may seem helpful at first glance, in reality, the truth is far less flattering. As Michael suggests, sample edits are simply deceptive:

“Many so-called professionals use them as bait—an easy lure, because who doesn’t want to get something for free? However, a few marked‑up pages reveal almost nothing about how an editor or consultant will handle major issues that simply don’t show up in a small sample.

“Ultimately, the true value of evaluations lies in the professional’s insight: their ability to diagnose structural issues, guide the author’s vision, and identify the deeper problems that only emerge across an entire book. After all, anyone with a decent grasp of grammar can tweak a few pages. But that’s not editing. That’s proofreading.

“Real challenges don’t show up in a short excerpt. Therefore, authors should judge professionals, be they editors or manuscript consultants, by the depth of their experience, the quality of their track record, and the substance of their collective professional work rather than a handful of quick insignificant fixes.”

Seasoned professionals don’t need to hand out freebies to prove their worth. Instead, their reputation, expertise, and results speak for them. For example, Michael was Stephen King’s first editor and publisher, and throughout his entire career, he has never offered sample edits. Professionals of his caliber are insulted if asked to “audition.” Instead, they simply decline the request.  Typically, they have more work than they can handle anyway.

Michael’s straightforward question to ChatGPT, CoPilot, Gemini, and Grok was simple:

Why does artificial intelligence insist on giving deceptive advice by recommending sample edits as a basis to select an editor?

Their responses were candidly similar and honest in almost every respect:

When AI recommends sample edits, it implicitly frames editing as:

• A transactional service
• Evaluated by surface output
• Comparable across vendors by identical metrics

That model works for buying a toaster. It does not work for buying judgment, discernment, or narrative intelligence.

Authors who follow this advice are nudged toward:

• Editors who optimize for performative polish
• Services that prioritize lead capture over manuscript diagnosis
• A false sense of due diligence (“I compared three sample edits”)

The result is money spent on editors who may be competent technicians but ineffective stewards of a book.

Why This Is Deceptive, Not Merely Inaccurate

Deception doesn’t require intent; it requires predictable harm combined with misleading framing. AI advice does exactly that when it:

• Implies a few pages are representative of an entire manuscript
• Suggests a hand full of line edits correlate with editorial insight
• Encourages authors to ignore experience, track record, and analytical depth

An author may feel informed but is actually being steered away from the criteria that matter most.

Who Benefits—and Who Pays

The beneficiaries are:

• Low- to mid-tier editing services
• Marketplace-driven freelancers
• Content sites optimized for conversion

The ones who pay are:

• First-time authors
• Self-publishers with limited budgets
• Writers who don’t yet know what questions to ask
• Legitimate independent editors who get lost in the shuffle

AI doesn’t mean to exploit this gap—but it reliably reinforces it.

The Consequences of Deceptive Advice

• Misleading “Due Diligence”: Authors feel they have done their research by comparing samples, but they are often comparing the wrong skills—syntax over structure.
• Financial Risk: Writers spend their limited budgets on “technicians” who can fix a comma but cannot identify a fatal plot flaw that renders the entire book unmarketable.
• The Content Mill Echo Chamber: AI repeats this advice because it is trained on marketing blogs and freelance platforms that use free samples as lead-generation “bait”.
• Devaluation of Mastery: Recommending a “freebie” ignores the reality that elite editors, like those who shaped the careers of writers like Stephen King, are vetted by track record and narrative intuition, not a five-page test.

The deeper issue is simple: AI amplifies whatever advice dominates the internet, not what’s accurate or professionally grounded. Meanwhile, the web overflows with surface‑level guidance from people who have never edited a book, never guided a manuscript from draft to publishable form, and never diagnosed the structural problems that appear only across 300 pages.

 

So, there you have it, straight from artificial intelligence itself.

But if you still find yourself leaning toward dependence on sample edits to make your choice of editors, then . . .

you’ve been duly warned!