How to Build an AI RevOps Team with Perplexity

TL;DR

The video demonstrates how a single RevOps lead uses Perplexity Computer to run an entire AI-powered RevOps workflow. It covers model council for planning, end-to-end CRM to outreach automation, and a trust framework to control agent autonomy, turning complex processes into scheduled autonomous tasks. This enables faster testing and execution.

Transcript

If 2025 was a year of AI agents, 2026 is the year of fully autonomous [music] agents. We have Nate Folen from Perplexity who has built an entire RevOps team using autonomous agents built with Perplexity computer. These are some of the most powerful fully autonomous workflows on the web for how you can scale your go to market. All of that and more o... Read More

Key Insights

• AI agents can scale RevOps by acting as a one-person team supported by a larger agent network.
• Model Council uses multi-model agreement to reduce risk and improve decision quality.
• CRM data is the backbone for locating target accounts and planning events or outreach.
• End-to-end workflows can be scheduled as recurring jobs to maintain ongoing operations.
• Apollo and CRM integrations enable seamless generation of outreach sequences and contact targeting.
• A trust framework governs how autonomous the agents can be, balancing speed with oversight.
• Skills and cron jobs enable proactive, self-running workflows without constant human input.
• Sharing best-in-class skills across teams helps standardize AI-driven RevOps practices.
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Questions & Answers

Q: How can AI power a RevOps team with Perplexity Computer

AI can power a RevOps team by acting as a single operator supported by autonomous agents, allowing end-to-end workflows from data ingestion to outbound outreach. The approach uses model councils to compare outputs, then automates campaign setup and delivery via integrated tools like Apollo, CRM, and outreach platforms.

Q: What is model council in Perplexity Computer

Model council is a workflow that prompts multiple AI models to produce outputs on a topic, then compares their results to find areas of agreement, disagreement, and unique insights. This reduces reliance on a single model and increases robustness when planning complex tasks like executive dinners.

Q: How does Perplexity Computer handle CRM data for campaigns

Perplexity Computer ingests CRM data to identify open opportunities and the best audience for outreach. It supports end-to-end processes by mapping data to campaign actions, including creating Apollo sequences and adding relevant contacts with appropriate senders, enabling seamless execution from data to outreach.

Q: What is the trust framework for agent autonomy

The trust framework defines how autonomous the agents can be, starting with guided tasks and gradually expanding to fully automated workflows. It involves monitoring outputs, adding human check-ins when needed, and designing recurring jobs that can operate with minimal human intervention while retaining oversight.

Q: Can this system run on a schedule

Yes, the system can run as scheduled cron jobs or weekly end-to-end skills that select a dinner location, draft a campaign, and queue it for execution. This enables continuous improvement and routine operations with minimal manual intervention.

Q: What is meant by the RevOps super PAC of skills

The RevOps super PAC of skills refers to a curated set of reusable capabilities that orchestrate agents, data, and tools to perform complex workflows. By sharing these skills, teams can quickly replicate best practices across different parts of the organization.

Q: How does the system plan events using CRM data

The system analyzes CRM opportunities to suggest suitable events, identifies target audiences, and uses model outputs to craft messages. It then deploys outreach through integrated channels, ensuring that invitations and follow-ups align with deal stages and relationship context.

Q: What role do autonomous CRM backfills play

Autonomous CRM backfills continuously monitor data, fill gaps, and adjust workflows without manual input. This capability keeps CRM data fresh, ensures consistency across campaigns, and supports ongoing experimentation and optimization of RevOps activities.

Summary & Key Takeaways

• A single operator leverages Perplexity Computer to automate a full RevOps workflow, effectively replacing a typical 10-15 person ops team.

• The process includes model council for cross-model agreement, then translates insights into actionable outbound campaigns via Apollo and CRM data.

• The program emphasizes governance, cron jobs, and proactive skills as core to sustaining autonomous operations.