SaaStr runs 30 AI agents: harder than managing 12 humans
SaaStr has been running AI agents in production for 10 months. What started as experiments turned into 30 agents handling outbound, inbound qualification, and internal ops. The top problem: context switching. Amelia, their operator, manages four separate dashboards daily: Artisan, Qualified, Salesforce AgentForce, and Monaco. None talk to each other. When they ran a ticket promotion, she manually updated five agents with identical context. No product exists today that unifies these tools into a single management layer. Second issue: the blackout period. Every new agent costs two weeks minimum to onboard. During Monaco's setup, existing agents sat idle because no one fed them new contact lists. Monaco shipped results (6 meetings from 64 contacts in week one), but other agents degraded. The math: one to 1.5 new agents per month maximum, or you cannot keep up. Third problem: succession planning. All knowledge about agent segmentation (which contacts go where, which agents handle what) lives in one person's brain. If that person leaves, the entire operation breaks. The implication for sales teams: AI agents are not set-it-and-forget-it. They require daily one-on-ones. Wait a week and the output goes stale. Most agents idle waiting for human input. You are paying for capacity you are not using. SaaStr runs agents on Claude, Replit, and multiple vendor platforms. They have an internal AI VP of Marketing called 10K that assigns daily tasks. It works, but the overhead is real. For sales leaders evaluating AI agent deployment: budget the human time. One operator can manage roughly 30 agents with daily check-ins. Plan two-week blackouts per new agent. Document everything because vendor platforms do not integrate and the knowledge will not transfer automatically. The promised orchestration layer does not exist yet. What sales ops teams actually need is unification: a single interface where humans meet with AIs. Until that ships, expect manual work across multiple dashboards and genuine operational complexity.