Marshall Deutz, who works in Product & Solutions at SpotDraft, moderated this webinar with Aprajita Tyagi, Senior Corporate Counsel at Miro, and Anna Pototschnig, Senior Legal Counsel at Calix. Aprajita has supported tech companies on commercial transactions for nearly a decade and leads global partnership transactions at Miro, where she also builds AI tools and agents for her team. Anna focuses on negotiating technology agreements at Calix, including AI and data privacy matters, alongside a broad range of commercial work. Both negotiate technology deals every day, so we heard how playbooks hold up when the counterparty pushes back and the business needs the deal signed today.
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The conversation started with where playbooks break down and what makes one genuinely useful instead of merely comprehensive. Aprajita and Anna then covered how prescriptive to be, what to do when a negotiation falls outside the playbook, and who should approve exceptions. They closed with where a playbook should live, how to keep it current, what data shows whether it's working, and audience questions on AI edge cases and separate playbooks for business teams.
Here are our top ten takeaways from the speakers' comments during the webinar:
Build your playbook to help people decide. Aprajita described a good playbook as a decision-making tool and not a textbook. It doesn't need to cover everything. It needs to help the reviewer make a quick call in a live negotiation or while working through redlines. Rank what you won't cross, what you can negotiate, and what you can accept, and explain why each item sits where it does.
Sort your positions into tiers your team can read at a glance. Aprajita's teams used traffic signals. Red light items are walls that go to leadership when the counterparty pushes back. Yellow light items, like the scope of an indemnity or a warranty, call for a pause to check the exclusions before moving ahead. Green light items can be accepted as is.
Match your guidance to the actual transaction. Anna pointed out that an AI vendor agreement carries very different risks than a sponsorship agreement. Even within one contract type, a SaaS vendor that receives sensitive data deserves a different look at limitation of liability than one that receives no data at all. Give reviewers enough context on the underlying deal to pick the right position.
Explain the protection you want along with the words. Anna separated the protection you need from the wording that delivers it. When the counterparty's language gives you that protection, don't nitpick it just because it isn't your wording. Spell out the objective behind each position so reviewers can recognize an acceptable alternative. A workable third option shouldn't die just because it's missing from your examples.
Get very specific where the wording carries the risk. Aprajita wanted precise language and explanations for high-risk items like training models on customer data, indemnities, data usage, and the scope of a license. Every word matters there, especially for a junior attorney. For everything else, give principles and the reasons behind them and trust the reviewer's judgment. Name the exact approver for any deviation on the high-risk items.
Give approvers a short risk summary when you go off script. When a negotiation fell outside the playbook, Anna first asked why the playbook didn't cover it and then found the right decision maker, which might be finance or security instead of another lawyer. Her approvers got a short summary of the transaction, what the parties had agreed, and what she was trying to achieve. They shouldn't have to reconstruct the negotiation. Record any approval conditions so the decision stays informed.
Match the approver to the risk and the subject matter. Aprajita tied approval authority to the size of the risk, the revenue, and the strategic value of the deal. Routine exceptions can sit with the reviewing attorney, and nuanced items get a second set of eyes from a senior attorney. Uncapped damages or an expanded indemnity go to leadership. Exceptions that touch privacy, data localization, or security bring in those experts.
Treat repeated exceptions as a reason to take another look. Anna looked at both the pattern and the reason behind each exception. One concession to a counterparty with leverage tells you little. The same ask across comparable deals may signal a market shift or a preferred position that doesn't address the real risk. Even then, any new standard should be a deliberate decision by someone with the authority to make it.
Put the playbook where your team already works. Anna wanted the playbook inside the reviewer's workflow, whether that's a Word add-in or the CLM, and not in a stale PDF. Keep one authoritative version owned by legal, with changes going through a defined approval process. Control access to sensitive fallbacks too. Anna had seen a colleague tell a counterparty "we've agreed to that before" and give away leverage on a deal with very different risks.
Collect your negotiation history and act on it. Aprajita called every redline data. Her team used to log new fallbacks as parked items and review them quarterly. Now an AI skill flags each deviation and approved exception and sends it to a shared board the team reviews every few weeks. The log only helps when the team actually meets and decides what belongs in the playbook.
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