Key Takeaways:
- Use the Oreo Cookie method: Developed by Nada Alnajafi, this workflow keeps humans at the beginning and end of the contract review process to strike the right balance between expertise and automation.
- Humanize contract comments: Nate Kostelnik advises using psychological tactics like asking for a small favor because it “gets them on your side… and it helps build some trust.”
- Schedule live calls sooner: If an agreement stalls after one email exchange, pivot to a live call to help drive decision-making and build rapport.
Many lawyers and contracts professionals have noticed a dramatic shift in how deals are reviewed. For decades, sharpening contract review skills was straightforward: you read more agreements, negotiated more deals, and gradually refined your internal playbooks. Today, AI tools can instantaneously scan documents, spot issues, and generate thousands of lines of markups with a single click.
But this sudden technological explosion brings a profound paradox to the negotiation table. If everyone has immediate access to automated redlining capabilities, do negotiations actually move faster? Do we sign better deals? Or are we simply generating more redlines?
In a recent webinar I hosted for Contract Nerds📄🤓, on “Contract Redlining Skills for In-House Counsel in the Age of AI: More Human, Less redlines, Faster Deals,” legal experts Nada Alnajafi and Nate Kostelnik addressed these exact challenges. Our webinar provided a masterclass on how to naturally integrate AI into a secure contract management process without abandoning the human connection required to finalize high-stakes business deals.
Missed the live webinar? I recommend watching the full webinar recording on YouTube and accessing the presentation and bonus materials to dive deeper into this topic.
1. The Redlining Paradox: Why Faster Markups Don’t Necessarily Mean Faster Deals
The introduction of generative AI into commercial legal tech promises unprecedented speed, yet legal professionals are discovering that artificial speed can easily morph into operational friction. When legal teams blindly delegate their oversight to automated platforms, the quality of communication with opposing counsel rapidly breaks down. This slows deals down.
“AI is faster at redlining some contracts than I am, and I’m pretty fast,” noted Nada Alnajafi, Sr. Corporate Counsel & Legal Ops Lead for Franklin Templeton and author of Contract Redlining Etiquette. “But generating redlines faster was never the goal. The goal was, and still is, to close deals faster.”
When automated systems are utilized without rigorous oversight, teams fall victim to what the speakers termed the “AI ping-pong trap.” In this scenario, one side dumps hundreds of algorithmically generated redlines onto the other, only for opposing counsel to run those edits through their automated tool, bouncing back a defensive, equally dense markup. The transactional velocity grinds to a halt because neither human has actually read the underlying clauses or assessed the true commercial risks.
To break this cycle, lawyers must remember that contracting is a relational exercise, not an algorithmic one. AI excels at processing volumes of text, but it completely lacks the capacity to cultivate trust or establish a professional rapport.
2. The Oreo Cookie Method: Structuring an AI-Assisted Contract Workflow
To safely utilize artificial intelligence without violating professional standards or causing negotiation fatigue, legal departments need a structured, step-by-step workflow. Alnajafi developed a simple, highly effective framework known as the Oreo Cookie Method to govern how attorneys should interact with automated legal tech for contract reviews.
This structural methodology mandates that a qualified human professional always serves as the beginning and the end of the contract lifecycle, while the technology is confined strictly to the middle layer.
Fun Fact: During the webinar, Contract Nerds gave away three free copies of Contract Redlining Etiquette to live attendees. Alnajafi promised to send Oreo cookies to satisfy their craving. Cookies and contracts seem to be a winning combination for these nerds!
Here are the five steps of the Oreo Cookie Method:
Step 1: The Initial Human Review (The Top Cookie)
Before any automated software touches a document, the attorney must review the basic transactional framework. You must understand the core business goals, identify which party holds the commercial leverage, establish the timeline, and define what a successful outcome looks like for your internal business stakeholders. AI can flag missing words, but it cannot tell you what matters most to your executive team.
Step 2: The Automated Processing Layer (The Cream Filling)
Once the attorney understands the strategic context, the contract is fed into the AI redlining tool. At this stage, the software handles the tedious, mechanical components of the review—cross-checking definitions, comparing language against pre-approved playbooks, and performing initial risk-spotting.
Step 3: The Final Human Verification (The Bottom Cookie)
The final step is entirely non-negotiable. The contract expert must meticulously read through every automated markup and edit. As Alnajafi firmly cautions legal teams: “The attorney, the contract expert, the contract manager, or whoever is responsible for that agreement has to review it at the end. And I don’t mean skim it. I mean actually read it.”
This strict human verification step ensures full compliance with ethical rules regarding professional competence. Because technology vendors explicitly disclaim 100% accuracy for automated outputs, the legal professional remains completely accountable for every single clause that moves to execution.
3. Designing Collaborative Playbooks to Combat Bottlenecks
Many in-house legal departments struggle to scale because highly specialized resources become bogged down by a massive influx of routine agreements. Implementing a generic, out-of-the-box AI model rarely solves this issue because standard algorithms cannot replicate your organization’s specific risk tolerance. The solution lies in dedicating internal subject matter expertise to building custom, hyper-targeted digital redlining playbooks.
“The time invested up front is what saves the time later,” Alnajafi explained when describing how her team successfully automated their high-volume Data Processing Addendums (DPAs). By uniting a privacy expert, an in-house counsel, and a vendor legal engineer for an intense 36-hour sprint, they built a customized playbook that reduced individual attorney review times by an astonishing 50% in some cases.
Custom contract playbook creation transforms AI from an untrusted black box into an authorized extension of your legal team’s collective brain. When your internal lawyers participate directly in defining the fallback positions and conditioning the model’s behavioral prompts, user adoption rates skyrocket.
Furthermore, an optimized contract playbook enables a safe transition toward business self-service models. Armed with pre-approved fallback guardrails embedded directly into the software, procurement or sales operations teams can autonomously clear standard redlines, completely removing legal as an operational bottleneck.
Strategic Takeaway: Don’t rely on generic, default AI settings. Target your company’s primary operational bottleneck (e.g., NDAs, SaaS terms, or DPAs) and invest the upfront hours required to train the platform to think like your most experienced counsel.
4. Injecting the Human Touch Into Digital Explanatory Comments
A frequent mistake legal professionals make when utilizing automated tools is accepting dry, robotic explanatory comments in the margins of their documents. A standard algorithm might correctly note: “This clause has been revised to alter the limitation of liability cap.” However, a sterile statement like that does absolutely nothing to persuade opposing counsel to accept your redline.
Kostelnik strongly emphasizes that contract negotiation is rooted in human psychology. To maximize your closing velocity, your digital comments must actively build trust, transparency, and collaboration. One technique is the Ben Franklin Technique. Kostelnik shared, “Ask your counterparty for a small favor to get them on your side, because you’re asking them for a small favor that they can comply with and do, and it helps build some trust.”
For example, placing a friendly comment at the very top of a document asking opposing counsel to double-check formatting or section numbering immediately breaks the ice. This signals that a cooperative human being is driving the draft, rather than an adversarial machine.
Kostelnik also advocates for utilizing unexpected psychological tools, such as the unsolicited compliment. Explicitly acknowledging and praising a well-drafted, reasonable position taken by the other party in an initial draft costs your client nothing, yet it creates a massive amount of behavioral rapport that can be leveraged when resolving more contentious clauses later in the text.
Turns out 61% of the live webinar audience was already using this technique and perhaps unknowingly using a tried and tested negotiation technique to build trust.
5. Transitioning Safely From Emails to Live Negotiation Calls
While asynchronous redlining via email is highly efficient for initial drafts, almost every complex commercial transaction eventually hits a structural wall. Issues become overly nuanced, email response times lag, and long-form comments turn combative.
Rule #3 of Contract Redlining Etiquette guides legal professionals to exchange redlines via email once, and then move to a live negotiation call. Of course, there are exceptions to this rule, but this is a general rule of thumb.
“Email is a fantastic tool,” Alnajafi observed. “But every communication method has its strengths and limitations… If the other party is not cooperating… then that’s probably a good signal that you should switch to a live negotiation call.”
As the mechanical work becomes automated, Alnajafi predicts that the differentiator will be the legal professionals who can step out from behind their inboxes and close deals in real time.
Learn More: How to Master Contract Redlining Calls for Faster Closings and Better Terms by Nada Alnajafi
Overcoming the Live Negotiation Anxiety
Despite the clear efficiency of jumping on a call, many junior attorneys avoid live negotiations because they dread real-time pushback. During the webinar, we polled the audience to find out exactly what holds them back:
With nearly half of poll participants citing a fear of not knowing how to respond on the spot, it’s clear that live negotiation anxiety is incredibly common. To mitigate this anxiety and build your confidence, legal professionals can implement three disciplined call preparation steps:
- Block Preparation Time: Protect 30 to 60 minutes on your calendar immediately preceding the live negotiation call to review the redlines, align with your internal business stakeholders, and map out your formal fallback positions.
- Establish Internal Communication Channels: Maintain a back-channel chat (such as Microsoft Teams) with your business sponsors during the live call so you can seamlessly align on commercial concessions without exposing internal strategic debates to opposing counsel.
- Engage in Live Co-Drafting: Share your screen during a Zoom or Teams meeting and edit the Word document live. Typing collaborative, middle-ground language in real time builds an immense amount of shared momentum and frequently shatters weeks of gridlock in a matter of minutes.
Audience Q&A
How can we manage our AI tool usage if our organization enforces a strict token limit or usage restriction policy?
Nada Alnajafi: Do your contract reviews in layers. The larger and more complex the prompt you give to an LLM, the less accurate its output tends to be. You do not need to use AI for every single sentence or routine paragraph. Confine your tool usage strictly to the high-value use cases where automation significantly drives efficiency, such as advanced risk-spotting or complex playbook comparisons. If you find yourself caught in an exhausting loop of constant re-prompting and fighting with the tool, turn it off and default entirely to your personal human legal expertise.
How do we safely manage liability when utilizing an AI tool that is built as a wrapper over a third-party LLM?
Nate Kostelnik: This comes down to a rigorous vendor selection process. You must deeply understand the technical architecture of your vendor’s platform. What models are they using under the hood? How do they handle data privacy? You want to partner with a legal technology vendor whose platform naturally evolves and improves alongside foundational model updates, while ensuring that your inputs are completely isolated and never utilized to train public algorithmic models.
Who legally owns the intellectual property and work product generated by AI redlining tools?
Nada Alnajafi: Your SaaS vendor agreement must explicitly state that all generated output is owned exclusively by you. The output should be legally defined as anything created by the software based directly on your proprietary input data and custom playbooks.
Nate Kostelnik: I completely agree. Protecting your inputs—including your highly confidential corporate playbooks—is vital. Ensuring your business maintains absolute ownership of both your inputs and outputs was a core theme during our recent live contract negotiation rumbles, and it must remain a non-negotiable point in your technology vendor agreements.
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This webinar was made possible by Docusign, Intelligent Agreement Management.
