The setting
offers , a cloud platform that gives sales teams insights, forecasts and coaching, and runs AI agents that carry out tasks and automate workflows.
Managers want to try proposed CRM changes without turning rehearsal into live execution.
Customer-specific approval rules protect the forecast, while manual checking consumes the time agentic workflows promise to save.
Who you’d be doing this for
“I spent forty minutes checking five suggested changes; I just want to try them somewhere safe.”
Duangjai Ngo · Sales Manager · a character in this brief
She evaluates proposed opportunity updates before the weekly pipeline review.
What is at stake
Sales managers spend 40 minutes checking proposed CRM changes in each evaluation. You must choose what to prototype and prove customers can operate it themselves.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- richer rehearsal vs. simpler approvals
- customer-specific rules vs. reusable deployment
- prototype speed vs. faithful evaluation
- demonstration appeal vs. repeat use
Why Gong
MCP and Gong APIs provide the integration boundary for testing agent-proposed actions alongside customer-owned Salesforce controls.
Written with these in mind
Not your kind of problem? 21 more at Gong, 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 Gong. They are listed as sources, not as openings. The lines under a posting are its own words, where it meets this brief.
- AI Enterprise Architect (opens in a new tab)
- You will help customers understand how Gong's AI capabilities, APIs, MCP, Gong Assistant, Deep Research, integrations, and broader platform fit into their enterprise AI strategy, technology ecosystem, and revenue workflows.
- Architect how Gong can be used within and alongside a customer's AI ecosystem, including through Gong APIs, MCP, Gong Assistant, Deep Research, integrations, and workflow automation.
- Talent Engineer (opens in a new tab)
- Real experience building solutions that integrate with external systems — APIs, OAuth, webhooks, rate limits, error handling in production, not just in a tutorial.
- Lead Solutions Engineer (opens in a new tab)
- Solution complex business and technical requirements and explain them in simple terms.
- Help eliminate bottlenecks by working cross-functionally (Sales, Customer Success, Support, Product Management, Engineering) in order to get deals across the line.
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 turns on easing someone in at the cost of understanding.
CSMs checked multiple records for 18 of 30 onboarding replies about next steps.
You decide when AI may draft a next step from Salesforce notes and when the CSM must settle whether a proposal became an agreement.
Applicants are repeating their application history while agents spend about 11 minutes finding a usable next step.
You decide whether the generated brief only recaps application activity and prior outreach, or also suggests what the agent says next.
The same setting, from another role
Each is set around Gong’s Gong Revenue AI OS, written for a different role. They’re separate briefs, not the same scenario.
RevOps leaders are appearing in two active corporate campaigns.
You must decide whether AI proposes segments only, or also recommends which active campaign yields.
Mid-market buyers question another revenue platform while cheaper AI tools promise deal-risk signals.
You must decide which consolidation concern earns a meeting and what proof belongs in the first message.
Enterprise CIOs are pausing technical validation over incompatible claims about revenue context.
You must choose a proof-backed story that can survive security review and still create qualified pipeline.
Other problems with a similar purpose
In each of these, as in this one, the aim is to turn a person's earliest brush with a product into a habit they keep coming back to.
Sixty-two percent of newly activated workspaces do not return for a second production session within 21 days.
You must weigh a scalable configuration-and-enablement path against a simpler setup change that uses the same capacity.
New enterprise accounts are starting tables but not returning to run a second workflow.
You have to weigh a fast activation path against a promise that still feels safe for RevOps.
New desktop users are skipping iOS setup and staying in a single-device inbox habit.
You need to decide how prominently mobile setup belongs before users reach their first inbox.
