The setting
develops an AI answer engine that searches the web and replies with cited sources. is the version for large organizations, including regulated industries, with administrator controls over access and use.
The signature deadline collides with commitments that must survive real agent use.
The customer wants certainty around Computer, while Security must avoid promising controls it cannot verify.
Who you’d be doing this for
“My security committee wants the signed terms today, and they keep asking what Computer can actually do with our data.”
Mikel Blanco · IT Administrator · a character in this brief
Leads identity, permissions, and compliance readiness for a healthcare organization preparing to provision Enterprise Max and Computer.
What is at stake
A healthcare IT administrator cannot enable Computer until the BAA commitments are settled. You must choose which agent commitments belong in the signed terms and which cannot be promised yet.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- signature momentum vs supportable commitments
- customer certainty vs unverified control claims
- Computer access vs narrower initial scope
- reusable precedent vs deal-specific concessions
Why Perplexity
Enterprise Max and Computer place contractual promises directly against the permissions and policy controls administrators rely on.
Written with these in mind
Not your kind of problem? 44 more at Perplexity, or browse every organization.
Where the organization context comes fromThe postings this brief was written from, and the reporting read before it.
The organization context comes from public information. The situation and characters are written for the brief.
Job postings it was written from
Public descriptions of the work at Perplexity. They are listed as sources, not as openings. The lines under a posting are its own words, where it meets this brief.
- Legal Response Specialist (opens in a new tab)
- Senior Commercial Counsel, Enterprise (opens in a new tab)
- Advise on AI-specific contract terms for enterprise deployments, including bespoke data postures; negotiate output ownership and liability, agentic-feature risk allocation and translate product operations into enterprise contract commitments.
- Serve as a trusted legal partner to Enterprise Sales, Partnerships, Deal Desk, and Customer Success, providing fast, practical, business-aligned counsel that accelerates deal velocity, protects the terms that matter, and scales as the Sales organization grows.
- Commercial Counsel/Senior Counsel (opens in a new tab)
- Advise on AI-specific legal considerations in commercial agreements, including acceptable use, data retention and training restrictions, output liability, and evolving regulatory requirements (e.g., EU AI Act, CCPA/CPRA, GDPR).
- Provide strategic counsel on legal risks across AI infrastructure, compute, partnerships, and enterprise deployments as the company scales.
This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.
Where similar work appears
Other live briefs connected to this one, and what connects them.
Similar problems at other organizations
Like this one, each of these is about betting growth on an outside partner or launch.
A selected financial-services prospect could lose its forecast transformation budget within 14 days.
You must weigh a fast commercial commitment against terms that security, procurement, and regional sales leaders can all stand behind.
Security wants proof that access controls hold in every region, and procurement wants a simple contract with little flexibility.
You have to decide what you can promise before deployment and still get signed inside the window.
The buyer ranks you first on quality, but two redlines are open and the incumbent offers a bundled guarantee.
You have to protect the commercial model without promising what you cannot verify yet.
Other problems with a similar purpose
In each of these, as in this one, the aim is to make an ambitious commitment financially and operationally sound enough to hold up under later scrutiny.
Two weeks before the committed control date, 14% of export events in scope cannot be classified either way.
You have to weigh broken analytics against the promise you made to a regulator and a customer.
A signed contract exposes up to $4.8M in annual service credits, and the reserve is due before the customer goes live.
You weigh machine-generated evidence against a wider scenario range, and the terms hold for the year.
Fourteen of 180 reviewed benefit-change contacts did not match the current eligibility record.
You have to weigh a four-week go-live against an architecture that cannot cheaply be reversed.
