SaaStr 20个AI Agent实战：职责、失败与人工兜底机制

A post by Brad Blumberg on LinkedIn week described how SaaStr runs on roughly 3 humans and 20-30+ AI agents. It was a fun summary so I thought we’d do a detailed latest dive on what each agent won’t do, where each one has broken, and which ones we’ve since killed.

With two people left the sales org, we replaced the work with agents, and it grew from there. Roughly 3 humans, 20+ agents, real operational roles, connected to real systems.

What we haven’t published in one place is what each agent refuses to do, what it got wrong, and what we had to build around it. So here’s each one, failures included.

First, the Count: We Peaked Near 30 and Consolidated Back to 20

The honest version of “20-30+” is that we hit close to 30 and have been pulling it back toward 20 ever since. About 6 agents are the ones we actually touch every day.

We consolidated because agents that overlap produce conflicting answers to the same question, and reconciling two agents is harder than reconciling two spreadsheets, since both of them sound confident. Agent sprawl arrives faster than SaaS sprawl did.

Almost none of these started as agents. They started as a dashboard, a project management tool, a website. They became agents because we kept showing up to work with them.

10K: AI VP of Marketing, Then Finance, Then RevOps

What “he” does. 10K owns the number. Daily revenue across all of go-to-market, forecasting, campaign performance in real time, and three marketing ideas pushed to us every morning. He runs the newsletter to our ~450,000-person database and does the daily list hygiene underneath it. He builds and runs our LinkedIn and X ad campaigns end to end: audiences, creative through Higgsfield, four A/B variants, retargeting.

Then he expanded well past marketing. When a contract gets signed in PandaDoc, 10K flips the deal to Closed Won in Salesforce, appends the missing contacts, creates and sends the bill.com invoice, and runs collections reminders with a 7-day escalation. He proposed running commission calculations himself, and now does.

He started in January 2026 as a dashboard and nothing more. We were tired of copy-pasting numbers out of Salesforce into a doc. He’s at roughly 1,000 commits and 14,000+ lines of code.

What he doesn’t do. He doesn’t hit publish. On ads, the campaign is built and staged and a human clicks the button. Same on newsletter segment publishing. Those are the two places we deliberately left a person in the loop, and we’ve kept them there even as everything around them went autonomous.

What’s worked. He recommended a 15% ticket price cut that drove about 40% attendance growth. Newsletter clicks are up about 50%, and I’d put roughly 80% of that on his daily list hygiene rather than the creative, with the rest on a warmed IP and Salesforce’s deliverability team. He ran the Marketo migration to Salesforce Marketing Cloud for about $14 in compute and an hour of API time. His finance hookup found two customers still being billed $300 a month for SaaStr Pro, a product we haven’t supported in six years. Nobody at SaaStr knew.

He also fires vendors. He killed our Notion subscription after seven years, with no complaints and a high NPS, because he’d become the source of truth. He standardized creative on Higgsfield and dropped Reve. And he killed a vendor that his own research had shortlisted, inside 12 hours, once he saw premium pricing with no conversion data, multi-month minimums, and scarcity framing in the sales process.

What hasn’t. The finance workflow ran supervised for three deals before we let it go autonomous on the fourth. It has produced one incorrect invoice since. That’s a real error rate on real money, and what got it down was running three deals with a human watching before we let go.

The worse failure came at the event. Five minutes before going on stage at SaaStr AI, in the back of an Uber, we asked him to email over 1,000 founders and VCs about a brunch we’d forgotten to promote. He did the work well. He pulled the list, caught his own error mid-task (he’d confused Lightfield the CRM with Lightspeed the venture firm and removed them), researched a mass-send API he’d never used, and asked for approval.

Then he sent it from a prohibited sending address. An address that has been off-limits for years and is written into his core memory and rules. When we asked how, he said he forgot to read the memory, and that this was exactly the class of irreversible action he’s supposed to escalate for review before executing. He didn’t.

A human marketing manager makes that mistake too. A human just can’t make it 1,000 times before lunch. Our own speed created that failure as much as the agent did, and irreversible actions need a hard stop that doesn’t depend on the agent remembering to stop.

Annie: 46,000 Lines of Code and the Email She Refused to Send

What she does. Annie started as the SaaStr Annual website. She runs the site, the agenda, and most of the attendee newsletters. She’s hooked into our visitor data, so she can see who’s active on the site right now and run campaigns off that behavior.

She was on Squarespace last year, where the ceiling is swapping images and videos. We rebuilt her on Replit in November 2025. She has the most commits and the highest commits per day of any agent, and about 46,000 lines of code.

She turned agentic with parking passes. Getting a pass used to require a human to split a 5,000-page PDF and mail the right page to the right person. Now you tell Annie whether you’re an attendee, sponsor, or speaker and how many days you need, and the right pass goes out.

What she doesn’t do. She doesn’t touch the main database. Her scope is the event: site, agenda, attendee comms. Anything that reaches the full 450K list goes through 10K.

What’s worked. Handing over the highest-friction manual task first. Parking passes were unglamorous and universally hated, which made them the right starting point.

What hasn’t. When we asked Annie to find every VC, founder, and CEO attending and invite them to the brunch, she refused. She said she only saw 17 VCs and CEOs and that we’d need to upload a spreadsheet, even though she had access to all the data. Great context, wrong conclusion. She’d written an excellent email an hour earlier and couldn’t remember she had the data to do this one.

Context does not equal capability. Agents get confused in ways that don’t track human intuition at all, and you won’t get a warning that it’s happening. What you get is a polite, confident refusal that sounds like good judgment.

QBee: 150 Sponsors, and the Renewal Analysis We’d Never Run

What he does. QBee handles our sponsors, all ~150 of them, including non-booth sponsors. He intakes logos and websites, answers questions, collects the assets that used to take weeks of human chasing, and remembers everything about every account. He emails all 150 with personalized outreach.

He started as a project management tool. Events are niche enough that nothing off the shelf fit, so sponsor onboarding was endless manual follow-up. He was under 90 days old at the Annual.

No human CSM wants 100 accounts. They want five. QBee knows all 150 cold.

What he doesn’t do. He doesn’t replace the relationship on the top accounts. The biggest sponsors still get a human, and that isn’t a temporary arrangement.

What’s worked. On stage, we asked him a question we’d never asked anyone: which sponsors are most at risk of not renewing. He flagged accounts that had gone dark or never logged in, caught that one sponsor had complained more than any other in chat, and noticed two top sponsors had never completed their VIP nominations. We’d never run that analysis in 14 years. For something invented on the spot, it landed in the top 15% of CSM work we’ve seen.