We Have 30 AI Agents in Production. Here Are the Top 5 Issues No One Talks About

We Have 30 AI Agents in Production. Here Are the Top 5 Issues No One Talks About by Jason Lemkin | Artificial Intelligence (AI), Blog Posts, SaaStr.Ai We’ve been running AI agents in production at SaaStr for about 10 months now. What started as a couple of experiments has turned into almost 30 agents and vibe-coded apps running across our GTM stack — from outbound sales to inbound qualification to internal operations. And managing 30 agents is harder than managing the 12 humans we had at peak headcount. Not harder in every way. But harder in ways I didn’t expect. Here are the top 5 issues we’ve hit — plus a bonus one that might be the most uncomfortable of all. #1: The Context Switching Tax Is Brutal Here’s the thing nobody tells you about running 20+ agents: they don’t all speak the same language. Some push data back to Salesforce. Some don’t. Some … sort of do. Some run on Claude. Some don’t. They all ingest context similarly but differently enough that switching between them takes real mental overhead. Think about it this way: we don’t think of them as 20 agents anymore. Not entirely. We think of them as 20 different AI employees, each with a different personality, different needs, and a different interface I have to log into every single day. Amelia’s morning routine right now looks like this: she starts with a deep dive with 10K, our internal AI VP of Marketing that runs on Claude and Replit. It literally tells us what to do each day — tickets, sponsors, outreach, cam...