The setting
builds an AI answer engine that pairs web search with generative AI. The lets developers use its search and agent technology in their own software, to build answer engines based on real-time search.
A finished research demonstration has set expectations that the customer's search application does not meet.
Friday's adoption checkpoint needs real task completion, while the application must remain unchanged this week.
Who you’d be doing this for
“I searched for my client this morning, then messaged the developer because I didn't know which source to use.”
Kiran Mishra · Research Associate · a character in this brief
One of the four intended users who has not yet completed a task in the customer's application.
What is at stake
Four of six researchers still need a developer to finish their first task. You must weigh tailored guidance for Friday against a reusable walkthrough that reaches future users.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- tailored guidance vs reusable enablement
- demonstration expectations vs application capabilities
- attendance counts vs observed first value
- developer availability vs researcher independence
Why Perplexity
The move from a demonstration in Perplexity Computer to an application using the Search API changes what customers must do to reach first value.
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.
- AI Strategist, Legal (opens in a new tab)
- Assess whether we have the right research, contract, docket, and document-management integrations to serve each legal segment—and drive the roadmap where we do not
- As an AI Strategist on our Applied AI team focused on the legal vertical, you are the subject matter expert who makes this real for legal professionals.
- Customer Success Lead (opens in a new tab)
- As Customer Success Lead at Perplexity, you’ll lead the team responsible for helping enterprises adopt Perplexity Computer and our API products, turning adoption into measurable business value.
- Engage executive sponsors at our largest accounts and step in personally on strategic adoption efforts, high-stakes renewals, and escalations while building the team’s ability to own day-to-day execution
- Technical Customer Success Manager, API (opens in a new tab)
- Perplexity's API Platform brings our work in AI, search, and agent orchestration to developers.
- Technical fluency: comfortable reading API documentation, making API requests, interpreting responses and errors, and discussing integration questions with developers.
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 people starting something and never quite finishing it.
Only six of eighteen designer-developer pairs finished an asset handoff independently.
You must weigh keeping the intended workflow against giving everyone enough time to practice a narrower one.
Three finance departments still run reports manually after completing dbt training.
You weigh customer ownership through a workshop against specialist configuration in the only available session.
Four departments still request manual extracts despite having working reports.
You must weigh departmental ownership against a centralized service that needs less customer preparation.
The same setting, from another role
Each is set around Perplexity’s Perplexity API Platform, written for a different role. They’re separate briefs, not the same scenario.
Connector failures are taking about 90 minutes to diagnose because engineers reconstruct agent traces by hand.
You have to decide how far the AI's failure narrative and replay inputs travel before an engineer must confirm them against the connector events and choose what enters an incident or evaluation.
Deep research calls can produce useful answers before developers discover the cost was outside their budget.
You must weigh a firm spend boundary against the retrieval depth that makes the answer useful.
Two developers received project names from another organization after credential refreshes.
You must weigh a hard credential cutover against disruption to active agent workflows.
Other problems with a similar purpose
In each of these, as in this one, the aim is to turn a customer's incomplete or stalled adoption into a credible story of real operational value.
One hundred twenty Professional Hosts are keeping peak weekends closed after receiving pricing recommendations.
You have to weigh faster availability gains against the trust hosts need to keep managing their own rates.
Several enterprise customers are being asked to reduce telemetry spend without agreement on what protects SEV1 investigation.
You have to weigh a repeatable FinOps programme against the risk of oversimplifying each customer’s incident workflow.
Test purchases complete, yet recovered revenue never appears on the shopper profile.
You must weigh a fast staging fix against an event mapping the customer can trust in production.
