Redlining with AI: The New Playbook for Contract Review

Learn how small firm lawyers are using AI to redline contracts faster and more accurately, without giving up control. This practical guide covers legal AI tools, real-world prompts, and workflows for corporate and real estate transactions using Gavel Exec.

By the team at Gavel

Published:

May 5, 2025

| Last updated:

May 22, 2026

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Redlining Contracts: A Late-Night Revelation

I'll never forget one particular night early in my legal career as a summer associate. It was past midnight, and I was hunched over a hefty contract, manually comparing it to an earlier term sheet. The office was silent except for the rustling of paper and my muttering every time I spotted a subtle change. I wanted to be a litigator, but here I was negotiating a settlement agreement line by line, eyes burning from toggling between documents. I remember thinking: there has to be a better way. Years later, as the CEO of Gavel, I often hear similar stories from small firm lawyers.

What if an AI could handle the busywork, and hand you a nearly-finished markup by the time you finish your coffee? In this whitepaper, I'll share how that's not just wishful thinking, but an everyday reality with tools like Gavel Exec. I'll walk through the basics of legal AI in plain English, give you ten ready-to-use prompts for contract review, and even recount a realistic deal scenario showing how an AI "associate" works in practice. The goal is to help you redline contracts faster and more effectively – with less risk and zero loss of control. Let's dive into the new AI-assisted playbook for contract review.

Primer: Legal AI Terms You Should Actually Know

Before we get to the fun stuff, let's cover a few key terms and concepts. This isn't a theoretical tech lecture – it's a human-centered primer on how AI actually fits into our contract review workflow:

• LLMs (Large Language Models): These are the engines behind tools like ChatGPT and Gavel Exec. They generate text based on patterns in legal language—great at drafting, summarizing, and editing when given clear instructions.
• Prompting: This is how you tell the AI what to do. Precise prompts get better output—think "Redline this clause from the tenant's perspective" instead of "Fix this."
• Hallucinations: When AI makes things up. It might invent a clause or misstate a rule if it doesn't have enough context. Always double-check critical sections.
• Context Injection: Giving the AI more info—like an LOI or prior contract—to improve accuracy. Gavel Exec lets you upload docs so the AI isn't guessing.
• Playbooks: Your firm's rules—like standard fallbacks or deal breakers—turned into AI-checkable logic. Gavel Exec can flag anything outside your playbook in seconds.
• Token Limits: AI models can only "read" so much at once. Most tools handle 10–15 pages fine; long agreements may need to be broken into sections.
• RAG (Retrieval-Augmented Generation): This combines AI with real data from your documents. Instead of relying just on what the model was trained on, it pulls in relevant info (like your playbook or deal terms) live. That's what powers Gavel Exec's accuracy when comparing docs or enforcing standards.

That's it – the ABCs of AI for contract review: LLMs that generate text, prompts that you control, the risk of hallucinations (managed by careful context injection and verification), playbooks to encode your expert knowledge, and token limits to keep in mind for document size. Now, let's get practical and look at how you can put this to use today.

10 Gavel Exec Prompts You Can Use Right Now

One of the best ways to "level up" your AI use in day-to-day work is to start with a library of proven prompts. Below are ten real examples tailored to corporate and real estate contract redlining. I've focused on scenarios that small firm lawyers encounter regularly – and each prompt is written in plain language as you might input it into Gavel Exec's chat sidebar in Word:

1. Compare a Draft to an Original (Lease vs. LOI)
   • Prompt: "Compare the following lease to the attached Letter of Intent. Highlight any terms in the lease that deviate from the LOI and suggest appropriate redlines."
2. Rewrite an Indemnity Clause (Make it Balanced):
   • Prompt: "The current indemnification clause is one-sided. Rewrite this clause in a more mutual way that protects both parties."
3. Simplify an Assignment Provision:
   • Prompt: "Rewrite the assignment clause in simpler, plain language, without changing its legal effect."
4. Apply an Internal Playbook Check:
   • Prompt: "Review this contract based on [Your Firm's Name] playbook and mark any non-compliant clauses or missing provisions."
5. Summarize Key Obligations for a Client:
   • Prompt: "Summarize the key obligations and deadlines in Sections 3-5 in plain English bullet points. Assume the reader is a client, not a lawyer."
6. Identify Deviations from Market Standards:
   • Prompt: "Review this purchase agreement and let me know which provisions are unusual compared to market standards for similar deals."
7. Generate a Missing Clause (from Examples):
   • Prompt: "Insert a standard 'Limitation of Liability' clause here, based on typical tech service contracts, capping liability at 1x fees and excluding indirect damages."
8. Make an Aggressive/Conservative Redline Pass:
   • Prompt: "Redline this agreement to be extremely [buyer-friendly]."
9. Spot Inconsistencies or Undefined Terms:
   • Prompt: "Check the document for any defined terms that are never used, or terms that are used but not defined, and list them."
10. Add Explanatory Comments for Client/Opposing Counsel:
    • Prompt: "For each major change in the redlined document, add a brief comment explaining the reason for the change in plain language."

Each of these prompts is like a power tool in your toolbox. They're not pie-in-the-sky ideas; they're things you can literally copy-paste into Gavel Exec (or a similar LLM-powered assistant) and get results today. The more you practice crafting prompts, the more you'll develop your own playbook of go-to AI moves. Remember, you can always refine the prompt and run it again if the output isn't spot on. It's an iterative conversation. Next, let's see how this actually plays out in a real-life scenario – from receiving a contract to sending out a revised draft – with AI as part of the team.

A Day in the Life: Using Gavel Exec on a Real Estate Deal

To illustrate the workflow, let's follow a small firm lawyer, "Alice," through a realistic transaction. Alice represents a startup tenant, and they're negotiating a commercial office lease. They signed a Letter of Intent a few weeks ago, and now the landlord's attorney has sent over a 40-page lease draft. Alice could manually redline it, but instead she fires up Gavel Exec in Word to help. Here's how the process unfolds:

1. Opening the Document with AI at Hand:
Alice opens the landlord's lease in Microsoft Word. She has the Gavel Exec add-in installed (it lives in Word's sidebar). With one click, she pulls up the Gavel Exec panel next to her document. She's essentially got a smart co-pilot ready to go on the same screen. The interface looks like a chat window where she can ask questions or give instructions, and a menu for running her playbooks.

2. Context Injection – Uploading the LOI:
Before asking the AI anything, Alice provides context. She uses the "Reference Document" feature to upload the signed LOI that outlined the key deal terms. In the chat, it now shows that an LOI.pdf is attached as context. By doing this, Alice ensures the AI knows the "deal" and can catch any discrepancies.

3. "Find What's Missing" – Prompting a Comparison:
Alice types: "Redline this lease based on the attached LOI. List any terms that don't match the LOI or are missing, and suggest edits." She hits send. Under the hood, Gavel Exec's AI quickly reads both the LOI and the lease. Within about 30 seconds, the chat populates with a response. It's a rundown of differences, essentially an issues list: - "Rent: LOI stated $5,000/month, but lease has $5,500/month – suggest changing rent to $5,000." - "Security Deposit: LOI said two months' rent ($10k) but lease lists $15k – consider revising deposit to $10k." - "Lease Term: LOI: 3 years; Lease: 5 years – possibly an error, flagging for review." - "Option to Renew: LOI included one 3-year renewal option; lease draft has no renewal clause – suggest adding a renewal clause per LOI."

Alice is impressed – in one go, the AI spotted four or five substantive inconsistencies. It also suggested language for adding the missing renewal option, pulling phrasing from usual practice. Alice clicks "Apply All," and Gavel Exec inserts those changes into the Word document (with Track Changes on). Just like that, major LOI alignment issues are handled. Alice, of course, double-checks each against the LOI – and they all align perfectly. She's still in control, but saved a ton of time.

4. Running a Built-In Market Playbook:
Next, Alice wants to ensure the lease is reasonable by market standards, not just matching the LOI. She switches to the Playbook tab in the Gavel Exec sidebar. There, she selects the "Tenant-Favorable Commercial Lease" playbook – one of the built-in options Gavel provides, developed with experienced real estate attorneys. She clicks "Run Playbook."

In moments, the AI produces a set of redlines and comments throughout the lease, all following the playbook's rules. For example: - It inserted a cap on CAM (Common Area Maintenance) charges at 5% annual increase, with a comment: "Added cap on CAM per tenant playbook (protects tenant from large year-over-year increases)."
- It flagged the assignment clause with a comment: "Playbook: allow assignment to affiliates without consent. Suggest adding that exception."
- It struck a sentence in the indemnity clause that made the tenant indemnify the landlord for the landlord's own negligence (a big no-no). The playbook automatically removed that and added a note: "Removed Landlord negligence from Tenant's indemnity (not standard for tenant to cover Landlord's negligence)."

Alice reviews these playbook-driven changes in the redline. It's like having a senior real estate lawyer whispering in her ear about what to fix. She doesn't accept all of them blindly – for instance, she knows this particular landlord never agrees to a CAM cap above 3%, so she tweaks the AI's inserted 5% to 3%. But the heavy lifting is done. In a few minutes, Alice has advanced the lease to a much more tenant-friendly state and documented the rationale behind each change with comments.

5. Clause-by-Clause Refinement via Chat:
With the broad strokes done, Alice now zeroes in on a few tricky clauses for fine-tuning. One is the "Default and Remedies" section, which is three pages long and full of legalese. Alice highlights a particularly dense paragraph (about five default scenarios) and in the Gavel Exec chat types: "Summarize this default clause in plain English, and suggest if any part of it poses unusual risks to the tenant." The AI quickly outputs a summary: "If the tenant fails to do X, landlord can do Y... etc." and notes that one provision is a bit harsh (the landlord can accelerate the entire rent for minor breaches, which is not common). This jibes with Alice's own impression. She asks a follow-up in chat: "What changes would make it more tenant-favorable without likely rejection?" The AI suggests a softer remedy (no acceleration for non-monetary defaults until 30 days opportunity to cure, for example). Alice likes that and manually incorporates a version of it into her redline, using the AI's suggestion as a template.

6. Quality Check and AI Double-Check:
Now the lease is heavily marked up with changes (in Track Changes) and sprinkled with comments explaining them. Before sending it out, Alice does a final review. She uses one more AI prompt as a safety net: "Scan the document and list any places where the tenant might still be over-exposed or any clause that a tenant-side attorney would typically push back on that we haven't addressed." Essentially, "did I miss anything?" Even after all that, the AI flags one item: "The guarantee clause makes the startup founder personally liable. Tenant attorneys often try to limit or remove personal guarantees. Consider if this aligns with your client's risk tolerance." Alice had indeed overlooked the personal guarantee section because she was focusing on the main lease. Now, she discusses with her client and they decide to propose a limited guarantee (maybe just for the first year's rent). She adds that to her markups as well. It's a prime example of how the AI, with its wide lens, can act as a backstop so nothing important is missed. The AI essentially acted like a diligent associate doing a second review of her work.

7. Delivering the Marked Draft – With Confidence:
Within a couple of hours, Alice has taken a landlord-friendly lease to a balanced document ready to send back. She's used the AI to compare against the deal memo, enforce her client's playbook preferences, translate and refine complex clauses, and ensure consistency. All the while, she has exercised her own judgment on which suggestions to keep. The final product is her work product – just accelerated and augmented by AI. When she emails it out, she includes a note to the opposing counsel highlighting a couple of major changes (the AI even helped draft those explanations).

From the outside, what the landlord's lawyer sees is a thorough, well-reasoned redline that looks like Alice spent days crafting. In reality, it was one afternoon, and Alice was able to make a soccer game with her kids that evening instead of pulling another late night.

Checklist: How to Review AI Outputs (Without Losing Control)

Using AI to draft and redline is powerful, but don't let the novelty distract you from the fundamentals of good lawyering. Here's a practical checklist to make sure you, the lawyer, remain in the driver's seat:

• 🔍 Always Verify Critical Edits: Treat AI suggestions as you would a junior associate's work – trust, but verify. If the AI redrafted an indemnity clause or added a new section, read it closely. Make sure it accurately reflects the deal and doesn't introduce legal issues.
• 🎯 Check for Accuracy (No Hallucinations): If the AI output references laws, definitions, or facts, double-check them. Ensure that any clause it "pulled in" actually exists in the context (or is standard in the jurisdiction) and isn't something made-up.
• ⚖️ Make Judgment Calls on Strategy: AI doesn't know your client's business priorities or what's a "throwaway" vs. a "dealbreaker." So review the AI's redlines in light of the client's goals.
• ✂️ Edit the Tone and Wording: Sometimes AI-drafted text, while technically sound, may need a tweak in tone. Perhaps the suggestion came off a bit too harsh, or not firm enough.
• 🔑 Protect Confidentiality & Sensitive Info: Make sure you're using AI in a secure way. Gavel Exec and similar legal-specific tools are designed with confidentiality in mind.
• 💾 Keep a Human-Readable Trail: After using AI, document the key alterations. This isn't because the AI might vanish – it's to ensure you internalize and remember the rationale.
• 🗑️ Know When to Toss and Try Again: Not every AI attempt will be gold. If you ask for a summary and it's too verbose, you can re-prompt it.

By following this checklist, you ensure that AI remains a tool, not an actor, in your practice. You maintain control over the substance and quality of the work.

Scale Yourself, Don't Replace Yourself

When I talk to fellow attorneys about AI, I often get asked, "Is this thing going to replace lawyers?" Let me be clear: No. What it's going to do – and is already doing – is replace certain tedious aspects of lawyering. And thank goodness for that!

AI automates those tasks, so you can focus on the higher-value work: advising clients, negotiating business points, crafting deal strategy, exercising judgment.

At the end of the day, "Redlining with AI" means you have a new playbook – one where man and machine collaborate. It's not sci-fi; it's here now, and it's remarkably easy to slot into your existing practice. If you've dabbled with ChatGPT, consider Gavel Exec your upgraded, lawyerly version of that experience – one that understands our documents and sits right inside Word, where you already work.