Ai Tools For Writers: What Works And What To Avoid

Gary Smailes
Gary Smailes | 13 November 2025
AI Tools for Writers: What Works and What to Avoid

The AI Tool Landscape for Writers

The AI writing ecosystem splits into five main categories. Each serves different parts of your publishing process, from first idea to final manuscript.

Generative AI: your brainstorming partner

Large language models like ChatGPT, Claude, and Gemini excel at idea generation and initial drafting support. Think of them as tireless collaborators who never run out of suggestions.

They help with:

These tools work best when you feed them specific constraints. "Give me three ways my detective could discover the body" produces better results than "help me write a mystery scene."

Warning: resist the temptation to let them write whole chapters. The prose will feel generic, and you will lose your voice in the process.

AI editing tools: your mechanical cleanup crew

Grammar and style checkers have evolved beyond simple spell-check. Tools like Grammarly, ProWritingAid, and Hemingway Editor now catch complex issues.

Modern AI editors flag:

These tools work well for copyediting tasks. They struggle with voice, subtext, and intentional rule-breaking. Accept their mechanical fixes, but ignore suggestions that flatten your prose.

Research and summarization: your fact-checking assistant

AI excels at processing large amounts of text and pulling out key information.

These tools help with:

Popular options include Notion AI, Mem, and specialized research tools like Elicit. Remember: these tools organize information but do not verify facts. Always check sources independently.

Dictation and transcription: your speed-writing solution

Voice-to-text has reached professional quality. Tools like Otter.ai, Rev, and built-in speech recognition let you:

This category works best for writers who think out loud or struggle with typing speed. The text needs editing afterward, but you capture ideas at the speed of speech.

Marketing copy assistants: your promotional wingman

Specialized tools help with the business side of writing:

These save time on promotional tasks that drain creative energy. Use them for first drafts, then refine to match your brand voice.

Map tools to your editing stages

Different AI tools shine at different points in your revision process. Match the right tool to the right job.

Developmental editing focuses on big-picture story elements:

Use generative AI for diagnostic feedback. Upload a scene and ask: "Does this advance the plot? Are the stakes clear? Is the pacing appropriate for this genre?"

Line editing targets voice, flow, and readability:

Grammar checkers help here, but use them selectively. Accept clarity improvements, reject changes that alter your voice.

Copyediting catches mechanical issues:

AI tools excel at this stage. They spot errors human eyes miss and maintain consistency across long documents.

Proofreading finds final formatting and typographical errors:

Use multiple passes with different tools. Each catches different error types.

Build your typical stack

Most successful authors use three to four AI tools in combination. Here is a proven setup:

Primary writing platform: Word, Google Docs, or Scrivener for actual drafting and major revisions.

LLM assistant: ChatGPT, Claude, or Gemini for brainstorming, problem-solving, and spot editing help.

Grammar/style checker: Grammarly or ProWritingAid for mechanical cleanup and consistency.

Readability tool: Hemingway Editor or similar for final sentence-level polishing.

Optional additions:

Start simple. Add tools only when you have a specific problem they solve.

Define your AI jobs list

Before you open any AI tool, decide what you want it to do. Write down specific tasks.

Good AI jobs:

Bad AI jobs:

Clear job definitions prevent feature creep. You stay focused on writing instead of playing with new tools.

Review your jobs list monthly. Remove tasks that waste time. Add new ones as your process evolves.

The goal is not to use every AI feature available. The goal is to write better books faster while preserving what makes your work uniquely yours.

What Works Well Right Now

Some jobs suit AI. Lean on those, save your focus for pages only you can write.

Brainstorming and outlining

Treat an LLM like a fast, opinionated writers’ room. Ask for structure, then shape the output to match your genre and word count.

Prompts that help:

Iterate with constraints. “Make midpoint a reversal, stakes double, antagonist gains advantage.” Or, “Target 50 scenes, average 1.8k words, raise tension every fifth scene.”

Quick exercise: pick your genre. Ask for three loglines with a protagonist, objective, obstacle, and consequence. Choose one. Replace the vague nouns with specifics from your world. Now ask for beats that deliver that promise.

Self-editing support

Grammar and style tools excel at drudgery. Offload pattern spotting. Keep decisions.

Run a pass to flag:

Example sentence: “There was a quick movement in the shadows which was very scary.”

Alternatives worth testing:

Ask for three revisions that keep POV, tense, and tone. Pick the one that serves the scene goal. If a suggestion smooths voice into oatmeal, decline.

Mini-checklist for a line pass:

Summarization

Long projects breed continuity leaks. Use AI to keep a clean map.

Helpful requests:

Series writers, build a simple bible from summaries:

Before drafting a new chapter, read the previous two summaries. Ask for a one-paragraph “what readers expect next” note. Use that to aim your scene.

Marketing collateral

AI speeds the business side so you can return to the book. First drafts only. Final polish stays with you.

Jacket copy prompt:

Query letter skeleton:

Ask for a one-paragraph pitch, a 50-word version, and a 15-word logline. Use the short version for social posts.

Example format for posts:

Always adjust voice. Swap bland verbs for specific ones. Check comps for recency and accuracy.

Style sheet drafting

A style sheet saves headaches across a long edit. AI builds the first pass in minutes. You decide final choices.

Ask for extraction with categories:

Example entries:

Update the sheet after every major pass. Share with your editor so corrections stay consistent.

Keep acceptance disciplined

AI excels at volume. Your job is curation.

Adopt a target acceptance range. Sixty to eighty percent of suggestions, averaged over a chapter, keeps speed without flattening voice. Below sixty, refine prompts or source material. Above eighty, watch for blandness.

Two-pass method:

  1. Mechanical pass. Fix grammar, punctuation, spacing, and obvious repeats. No voice changes.
  2. Voice pass. Review flows, metaphors, and rhythm. Accept only changes that preserve subtext and character.

Quick tests before accepting a change:

When a tool smooths a teen narrator into a polite middle manager, hit reject. When a model improves clarity without harming tone, take the win. Keep authorial decisions on the page where readers will feel them.

Pick the jobs that suit AI. Define the guardrails. Then write the scenes only you can write.

What to Avoid (or Use with Extreme Caution)

AI confidence runs high. AI accuracy runs patchy. Know where the gaps hide before they bite you.

Facts and citations

Models hallucinate with supreme confidence. Dates shift. Quotes morph. Sources vanish into thin air.

I watched a model invent a Shakespeare sonnet, complete with line numbers and scholarly commentary. Sounded legitimate. Problem: the sonnet never existed. Another time, a model cited three peer-reviewed papers about medieval armor. Two papers were real but said nothing about armor. The third paper was pure fiction, complete with fake journal name and author credentials.

Historical fiction writers face the worst traps. Ask for "three primary sources about 1847 Irish famine conditions" and you might get real book titles with fabricated page numbers, or real historians making claims they never made.

Verification steps that work:

Science fiction and fantasy writers, beware scientific "facts." Models blend real physics with movie physics. They mix current discoveries with speculation and present both with equal authority.

Simple rule: if a fact matters to your story, verify it yourself. If it appears in dialogue or narration as true, double-check twice.

Legal and medical procedures

Confidence does not equal accuracy. Models sound authoritative about complex fields while missing crucial details.

Legal procedure example: a model might describe a police interrogation with perfect Hollywood drama and terrible actual law. Miranda rights, warrant requirements, and custody rules vary by jurisdiction and change over time. Your thriller needs accuracy if readers include lawyers and cops.

Medical accuracy gets worse. Models mix symptoms, treatments, and timelines. They suggest outdated procedures or ignore drug interactions. A character with diabetes might receive advice that sounds clinical but could prove dangerous if a reader followed it.

When specialized knowledge drives plot:

Models excel at suggesting dramatic scenarios. Leave accuracy verification to humans who practice in those fields.

"Write like [living author]" prompts

This territory sits somewhere between mimicry and copyright infringement. Plus it shortcuts your own voice development.

Legal problems first. Contemporary authors hold copyright on their distinctive style elements. Direct imitation for commercial use enters murky water. Publishers avoid manuscripts that read like pale copies of bestselling authors.

Creative problems run deeper. Voice imitation trains you to echo someone else rather than develop your own approach. Readers want fresh voices, not processed versions of familiar ones.

Better approach: describe stylistic traits without naming authors.

Study authors you admire. Analyze how they build sentences, handle dialogue, and pace revelations. Then apply those techniques to your own material, your own characters, your own voice.

Influence differs from imitation. Let influences shape your approach without photocopying their style.

Long-form continuity

Models forget. Memory spans stay short. Details drift between sessions.

A character might shift from brown eyes to blue eyes between chapters. A wound on the left shoulder might migrate to the right arm. A deceased character might reappear without explanation. Timeline shifts happen without warning.

Series writers face bigger problems. A model might contradict established world rules, forget character relationships, or ignore previous plot threads. Magic systems gain new rules. Geography shifts. Character backstories drift.

Continuity solutions that work:

Feed context deliberately. Models work better with reminder prompts: "Maya has green eyes and a scar above her left eyebrow. She speaks with Irish accent and avoids contractions when angry."

Trust your series bible over AI memory. When details conflict, check your reference documents and correct the model, not the manuscript.

Privacy and IP risks

Your unpublished manuscript represents intellectual property. Some AI tools train on user submissions. Your novel might teach the next model, appearing in fragments across future outputs.

Reading terms of service reveals the scope. Some tools claim rights to train on submitted content. Others promise not to train but keep your content on servers indefinitely. A few offer local processing with no data retention.

Safer practices:

Professional consideration: agents and editors expect original work. If models trained on your submission produce similar content for other users, questions about originality may arise.

Check vendor policies on:

When in doubt, process work locally or choose providers with clear no-training policies.

Over-automation

One-click fixes flatten prose into oatmeal. Voice disappears. Personality evaporates. What remains sounds like everyone else.

Automated editing tools target patterns without understanding purpose. They smooth dialect into standard English. They expand contractions that create character voice. They suggest formal alternatives to casual dialogue.

Example sentence from a teen narrator: "Mom's gonna flip when she sees this mess."

Automated suggestion: "Mother will be displeased when she observes this disorder."

The suggestion fixes nothing. It erases personality, changes register, and sounds like a robot wrote it.

Similar problems hit rhythm and pacing. Tools might break up short sentences that build tension. They might combine sentences that work better apart. They flag intentional fragments and repetitions that serve specific purposes.

Defense strategies:

Automation saves time on grunt work. Grammar errors, spacing problems, and obvious typos get fixed faster with tools. But voice, tone, and rhythm need human judgment.

Use AI for pattern recognition. Keep decisions about voice and meaning for yourself. Speed helps. Homogenization hurts.

The goal stays clear: better books, faster workflow, preserved voice. When a tool serves those ends, lean on it. When a tool threatens voice or accuracy, step back and handle the work yourself.

A Safe, Efficient AI-Enhanced Editing Workflow

Work faster. Keep your voice. Ship clean pages. Here is a workflow that does the job without turning your book into paste.

Pre-draft

Front-load decisions, then write with fewer detours.

Example do-not-change list:

Two smart prompts for this stage:

Lock these pieces before drafting. You will thank yourself later.

Drafting

Write the scene yourself. Use AI like a sharp screwdriver, not a ghostwriter.

Good spot help:

Avoid full scene generation. Your voice sets the grain. Keep it.

Mini exercise: Set a 25-minute timer. Draft the scene. Mark rough lines with XX. When the timer ends, fix only the XX lines with targeted prompts. Stop once they read clean aloud.

Developmental pass

One scene at a time. Ask for diagnostics, not rewrites.

Paste the scene with a short checklist prompt:

"Role: developmental editor.
Constraints: no line rewrites, no new plot. Respond in bullets.
Passage: [paste 800–1200 words].
Request: assess
- POV consistency and psychic distance
- Goal, conflict, outcome
- Pacing and scene turn
- Stakes on the page
- Setting continuity with Chapter 3 and 4
Acceptance: return max 8 notes, each under 30 words, include one question for author intent."

Useful follow-ups:

Keep a notes file. Move only the notes you accept into your revision plan. If the model pushes plot surgery you did not request, park it. You decide structure.

Line and copyediting pass

Now polish sentences and mechanics without sanding off voice.

For targeted LLM help, limit scope:

"Role: line editor.
Constraints: preserve first-person teen voice, humour, and contractions. UK spelling.
Passage: [paste 150–250 words].
Request: return 3 to 5 rewrites for only the sentences marked [UNCLEAR]. Offer one-line reason for each change.
Acceptance: do not alter slang, names, or dialect."

Mark sentences like:

You pick the fix, or you keep your original. Control stays with you.

Readability and final pass

Run a readability tool such as Hemingway. Use it as a spotlight, not a judge.

Quick checks before you move on:

Version control

Protect your future self. Label, log, and track.

Changelog example:

Track acceptance rate of AI suggestions. A simple method:

If acceptance goes higher, the tool might be steering the prose. If it dips too low, either prompts need tuning, or the tool adds noise.

Two final habits that save books:

How to Evaluate and Choose AI Writing Tools

Pick tools with proof, not promises. Treat this like hiring help for your book. Test, measure, then decide.

Accuracy and usefulness

Start with a small, repeatable test.

Mini exercise, 20 minutes:

  1. Paste 500 words from a scene with dialogue.
  2. Run Tool A. Accept only fixes you would make by hand.
  3. Log numbers, time spent, and two lines on voice impact.
  4. Reset. Repeat with Tool B on the same text.
  5. Pick the cleaner result with less voice drift.

A few tells of real value:

Privacy and IP

Protect your pages before testing.

Look for:

Where to check:

Ask direct questions if anything feels fuzzy. Copy, paste, and send:

“Before trial, I need clarity on data handling. Do you store user text long term. Do employees read user content. Do you train models on user uploads. Is there a training opt-out tied to my account. Link me to the policy pages which confirm these answers.”

No reply, or a vague reply, means move on.

Pro tip for drafts under wraps:

Integration and UX

A tool needs to stay out of your way.

Test in your real setup:

Run a small stress test. Open your novel file. Run a grammar pass on a 2,500-word scene. Jump between three chapters. Add a comment. Accept ten fixes. Export to DOCX. Reopen the export. Check comments, styles, and line breaks. If anything breaks, that is a no.

Comfort matters too:

Cost and limits

Know your load before you pay.

Make a quick grid:

Pick the plan with enough headroom for crunch weeks.

Red flags

Walk away when you see:

Quality editing needs your judgment. Any tool selling shortcuts on taste or truth wastes your time.

Run a 2–3 chapter bake-off

Give each finalist the same tasks. Use the same text. Log everything.

Chapters: pick one heavy on dialogue, one with action, one with exposition.

Tasks and prompts:

  1. Grammar and consistency pass. “Flag spelling, punctuation, hyphenation, and obvious grammar errors. UK spelling. Do not change slang or dialect. Return fixes in a list with quotes.”
  2. Clarity rewrites for tough lines. Mark 5 sentences with [UNCLEAR]. Prompt: “Offer 3 rewrites per [UNCLEAR] line. Preserve tone and rhythm. No added information.”
  3. Summary for continuity. “Write a 120-word scene summary with goal, conflict, outcome, and time/place markers.”
  4. Style sheet draft. “Extract names, places, capitalization, hyphenation, and spelling choices into a Chicago-style sheet.”

Scoring sheet columns:

Signal to noise wins. A strong tool gives fewer, sharper suggestions you accept with confidence. A weak tool floods you with noise.

Two small rules during the bake-off:

Decision day script:

You will end up with a stack that helps, not hinders. The right tools respect your pages, speed up the grind, and keep your name on the line where it belongs.

Advanced Techniques for Power Users

Once you know the basics, these methods turn AI into a precise editing partner.

Style conditioning

Train your tools to recognize your voice, then let them police your drift.

Start with exemplars. Pick three pages from your best work. Pages where the voice sings, the rhythm flows, the word choices feel inevitable. Add your style guide if you have one. Feed this to your LLM with clear instructions:

"These three pages represent my target voice and style. My style guide is attached. I will paste new chapters for comparison. Flag any drift from these references. Focus on sentence rhythm, word choice patterns, dialogue tags, and metaphor density. Return specific quotes with explanations."

Test it with a chapter you know has problems. The model should catch:

Example prompt structure:

"Reference voice: [paste polished pages]
Style guide: [paste key rules]
Chapter to check: [paste new work]
Flag drift from reference voice. Quote specific problems. Suggest fixes that match the reference tone."

Keep your exemplars current. Update them every few months as your voice evolves. The model learns from what you feed it.

Retrieval-augmented prompts

Stop the guessing. Make your AI work from facts you control.

Build a knowledge base for your project:

Store these as separate documents. When you prompt, attach the relevant files and require citations:

"Attached documents: [world bible, character sheet for Sarah, timeline]
Chapter text: [paste scene]
Check this scene against attached documents only. Flag continuity errors. Quote the source document for each issue. Do not add information not found in the attached files."

This stops hallucinations cold. The model works from your facts, not its training data.

Sample fact-checking prompt:

"Documents attached: [police procedure manual, forensics notes]
Scene: [detective examining crime scene]
Verify technical accuracy against attached documents only. Flag errors. Quote source material. Mark any details not covered in the documents as 'verify externally.'"

For series work, this approach saves hours of manual cross-referencing. Upload book one's character arcs and world rules. Let the AI catch inconsistencies in book two before they compound.

Prompt templates

Stop retyping instructions. Build reusable templates that work every time.

The five-part structure:

  1. Role: "You are a copyeditor with 15 years in literary fiction."
  2. Constraints: "UK spelling. Preserve dialect. No changes to invented terms."
  3. Passage: [paste text]
  4. Request: "Flag comma splices and misplaced modifiers."
  5. Acceptance criteria: "Return max 10 suggestions. Include page references. Explain each fix."

Template examples:

Dialogue polish:

"Role: You are a dialogue editor specializing in contemporary fiction.
Constraints: Preserve character voice. Keep contractions. Maintain subtext.
Passage: [dialogue scene]
Request: Flag unnatural speech, talking heads, and attribution issues.
Criteria: Return 3-5 specific suggestions. Quote problems. Suggest natural alternatives."

Pacing check:

"Role: You are a developmental editor focused on scene pacing.
Constraints: This is chapter 12 of a thriller. Target pace is fast.
Passage: [action scene]
Request: Flag slow spots, weak tension, and momentum breaks.
Criteria: Quote problem sentences. Suggest cuts or tightening. Max 7 issues."

Clarity pass:

"Role: You are a line editor focused on sentence clarity.
Constraints: Preserve author voice. Keep intentional fragments. UK spelling.
Passage: [dense expository scene]
Request: Flag unclear sentences, buried subjects, and tangled syntax.
Criteria: Return 5 rewrites maximum. Preserve meaning and tone."

Save templates as text snippets. Copy, paste, add your passage, send. Consistency improves results.

Sensitivity and bias checks

Use AI as a first screen, not a final word. Follow up with human readers.

Run targeted passes on specific issues:

Representation audit:

"Role: You are a sensitivity editor focused on representation in fiction.
Constraints: This is young adult contemporary fiction set in London.
Passage: [character introduction scene]
Request: Flag stereotypes, tokenism, and problematic descriptions related to race, disability, and class.
Criteria: Quote specific problems. Explain why each flagged element is concerning. Suggest alternatives."

Body and ability language:

"Role: You are an editor focused on inclusive language around bodies and abilities.
Passage: [hospital scene]
Request: Flag ableist language, medical stereotypes, and problematic metaphors.
Criteria: Quote problems. Explain issues. Suggest neutral alternatives."

The AI catches obvious problems: outdated terms, harmful metaphors, stereotype patterns. But it misses nuance, context, and lived experience.

After the AI pass, send the same scenes to human sensitivity readers from the relevant communities. Pay them. Ask specific questions based on the AI findings.

Combined approach script:

  1. Run AI sensitivity check, flag 8-10 potential issues
  2. Research flagged terms and metaphors independently
  3. Hire sensitivity readers, share AI findings, ask for deeper feedback
  4. Revise based on human guidance, not AI suggestions alone

Collaboration with editors

Turn AI critiques into efficient discussion tools.

Export summaries for your professional editor:

"AI Review Summary - Chapter 7
Tools used: Claude for developmental feedback, Grammarly for mechanics
Acceptance rate: 12 of 18 suggestions (67%)

Accepted changes:
- Cut 3 weak transitions (lines 45, 78, 134)
- Tightened 2 wordy sentences (lines 23, 91)
- Fixed dialogue attribution (lines 56-58)

Declined changes:
- Kept repetitive 'he said' tags - matches character's flat affect
- Left fragment at line 102 - matches POV character's thoughts
- Retained technical jargon (lines 67-70) - character expertise

Discussion points:
- AI flagged pacing in middle section - agrees or disagrees?
- Suggested cutting backstory paragraph (lines 89-95) - your thoughts?
- Unclear if dialect spelling consistent - please review lines 34, 49, 81"

Frequently Asked Questions

Which AI tools should I use at each editing stage?

Match the tool to the job: use generative LLMs (ChatGPT, Claude, Gemini) for brainstorming and diagnostic prompts during developmental editing; grammar/style checkers (Grammarly, ProWritingAid) for copyediting; readability tools (Hemingway) for final sentence-level polish; and dictation/transcription tools for fast drafting. Build a simple stack—draft in Word/Docs/Scrivener, use an LLM for spot edits, a grammar tool for mechanical cleanup, and a readability pass before human proofing.

How can I preserve my authorial voice when using AI?

Adopt a disciplined two-pass method: a mechanical pass for grammar and punctuation, then a voice pass where you accept only changes that preserve tone, subtext and character diction. Use a do-not-change list, turn off dialect flags in tools, read suggestions aloud and reject anything that flattens rhythm or personality.

How do I prevent hallucinations and verify facts from AI outputs?

Use retrieval-augmented prompts and attach your own source documents so the model checks against facts you control, and always cross-reference anything that matters to plot or reader trust. For historical, legal or medical details, verify dates, quotes and procedures against primary sources or consult subject experts rather than relying on the model alone.

Are my unpublished manuscripts safe to upload to AI tools?

Not always. Check terms of service for training opt-outs, data retention and ownership clauses before uploading full manuscripts. Safer options include local/desktop processing, redacting unique names or lore, uploading single scenes instead of whole drafts, and choosing vendors with explicit no-training promises.

Can I use AI to write whole chapters or the entire novel?

It’s possible but not recommended: full-chapter generation risks generic prose and loss of your distinctive voice. Use AI for targeted jobs—brainstorming beats, offering three sentence rewrites, or proposing plot complications—and always shape AI drafts heavily so the final manuscript remains unmistakably yours.

How should I evaluate and choose an AI writing tool?

Run a 2–3 chapter bake-off: use the same text and tasks across finalists, log time spent, total and accepted suggestions, readability delta and false positives on voice. Prioritise acceptance rate, privacy posture, export reliability and UX integration with Word/Docs/Scrivener over marketing claims or price alone.

What acceptance rate and workflow should I aim for when using AI suggestions?

Aim to accept roughly 60–80% of AI suggestions on mechanical fixes and a lower share on voice-sensitive changes; track this with a simple count on a 1,000-word sample. Use version control and a changelog, paste only the scene you’re working on, and review AI-suggested changes against your style sheet before applying them.

Writing Manual Cover

Download FREE ebook

Claim your free eBook today and join over 25,000 writers who have read and benefited from this ebook.

'It is probably one of the best books on writing I've read so far.' Miz Bent
Get free book