8:42 AM - Inbox and overnight triage
I pour coffee and open the admin dashboard before I've even sat down. The laptop is still cold. On Tuesday mornings, this is my ritual: check what MSP AI flagged while I slept.
There are 47 new incoming tickets across our 23 active customers. The system automatically sorted them by urgency and assigned potential SLA impacts. I scroll through the summary: five tickets are marked "escalation needed" because they arrived outside coverage windows or because the AI detected language suggesting the customer is frustrated. I click into one.
Carol Reyes at Reyes Family Practice submitted a ticket at 11:47 PM last night complaining that her entire network went down. The AI did the right thing flagging this as critical. I read the draft response it wrote:
"We understand network outages are disruptive. Our team is available 24/7 for critical issues. Can you confirm which systems are currently offline and whether you have a backup connectivity option?"
It's fine. Generic, safe, but fine. I approve it and mentally note to check on this ticket around 3 PM to see if Reyes Family Practice's technician has replied. The AI won't send the follow-up automatically - I need to review it - but it'll draft one and flag it for me.
I tab over to Slack. Three notifications. One is a customer workflow automation flag: a Slack alert telling me that TechVision Solutions' ticket volume spiked 340% in the last six hours. That's unusual enough to surface. The other two are routine: payment confirmations and a digest of new feature requests the AI collected from customer emails.
9:15 AM - Dashboard walkthrough
I pull up the main metrics page in our product. It's my second month running this, and I'm still getting used to seeing these numbers refresh in real time.
Today's revenue: $687 so far. That's from 11 subscription renewals that hit Stripe this morning. I click the Stripe dashboard in a new tab to verify the reconciliation is clean - it is. No failed charges, no chargebacks. Last Tuesday we had $612, so we're up 12 percent week-over-week. Annualized, if this holds, we're looking at $36,000 ARR by month three. That's not the $168,000 mid-year number from the pitch deck, but it's real revenue from real companies paying us on the first and fifteenth.
New signups overnight: three. That's below our rolling average of five per day, but the cold email campaign is still pulling. One signup came from a cold email I sent on Friday to a 15-person MSP in Phoenix. Another came directly through r/msp where we've been building credibility. The third one I don't recognize - I'll need to check the referral source in the CRM, which the AI should have logged. I make a note to do that.
Week-to-date pipeline: 14 prospects in active conversations. That's low. By Friday last week, we were at 18. I've lost at least four prospects to either churn or stagnation. I need to figure out why. Probably some of them got nervous about pricing, or got distracted by competing tools.
10:50 AM - A customer escalation
My phone buzzes. A Slack DM from Marcus Washington at Sterling IT, one of our earliest and largest customers (four technicians, $1,200 MRR). He's asking to jump on a call in the next hour.
I check the draft the AI prepared overnight for his account. It's flagged a billing anomaly: Sterling IT was charged twice for their monthly renewal yesterday. That's a mistake on our end - a double-submission to Stripe. It happens when a payment fails and retries, and I didn't catch it during yesterday's review. It's my job to catch these before the customer sees them.
I spend 15 minutes manually creating a credit in Stripe for the duplicate charge ($1,200), and I write Marcus a direct email:
"Marcus, I caught a billing error on our side. You were charged twice yesterday for your renewal. I've issued you a credit for $1,200 effective immediately. I apologize for the mistake. Sterling IT shouldn't have any out-of-pocket cost. Let's skip the call unless you have other concerns. Thanks for catching this quickly."
I hit send. I don't wait for the AI to draft this one. Some things need the owner's voice.
12:30 PM - Lunch and the hard conversation
I grab leftover pasta and open Gmail. Among the routine customer support threads, I find an email from Deborah Lin at Advanced Network Solutions. The subject is "We're canceling on Friday."
My stomach tightens. Advanced Network Solutions was one of my first beta customers. Eight technicians, $1,800 MRR. They came on three weeks ago with real enthusiasm. I read her email:
"The product is solid, but we're reallocating budget for a new hire instead. Your tool would save us time, but the time it saves isn't worth $1,800 a month when we need a technician more. Nothing wrong with MSP AI. Just not the right timing for us."
That one stings. I've been expecting some churn - you can't build something without losing customers to budget constraints or changing priorities. But losing $1,800 MRR also drops our week-to-date revenue significantly. I write her back:
"Deborah, I appreciate the honest feedback. If your situation changes or if you want to revisit this in Q4 when hiring is done, reach out. We'll be here. Genuinely rooting for Advanced Network Solutions."
I don't offer a discount. The AI suggested that in its draft response, but I overrode it. Discounting doesn't solve her actual problem - she needs a technician, not cheaper software.
I close the laptop for ten minutes and eat the pasta.
2:45 PM - A tricky edge case
Back at the desk, I'm reviewing SLA reports the AI compiled for our trial customers. There's one that bothers me. Universal Dental Group has a trial that expires in nine days. They've been using the system for two weeks, and the AI has accurately logged all their incoming tickets and drafted responses. But I notice the AI has been drafting responses in a much more clinical tone than some of the other customers prefer.
I click into their ticket history. Ah, I see it. Universal Dental Group has a lot of urgent tickets about patient data access issues. The AI detected the clinical domain and shifted its tone accordingly. That's actually correct behavior, but it's making the trial feel robotic compared to what the customer is probably expecting from a communication helper.
I don't have a one-line fix for this. It's a feature request: allow customers to set communication tone profiles. I log it in Linear, our task tracking tool, and flag it as low priority. For now, I draft a manual email to the trial contact:
"We noticed your team is handling a lot of patient data access requests. We can tune our response drafts to match your team's usual tone. Would you prefer warmer, more personal responses, or is the current format working?"
4:15 PM - Revenue check and a small win
I'm checking Stripe again because I like to see the daily numbers update in real time. We've hit $1,247 in revenue today, which is above average for a Tuesday. A customer payment came through that I wasn't expecting - ClientFirst IT paid early for their August renewal. That's a signal they're happy.
I also see that one of our free trial customers (a 7-person MSP in Colorado called Peak Systems) has converted to a paid subscription. Their 30-day trial expired yesterday, and they upgraded to our $400 MRR tier this morning. That's a clean conversion, no discount offered, no negotiation needed. I feel actually good about that one.
I spend 20 minutes writing an onboarding email to Peak Systems' owner, Adrian Torres:
"Adrian, thanks for choosing MSP AI. You're going to see your team's documentation time drop by 20-30% in the first month. That's what we're hearing consistently. A few tips for your first week: configure your Slack integration today so you get real-time escalation alerts. Then set up your SLA thresholds for each client. Let me know if you hit any snags."
5:50 PM - Pipeline and the rest of the week
I pull up our CRM. The 14 prospects in active pipeline are spread across three stages. Five are in discovery (we've had one conversation). Six are in trial (they're using the product for free). Three are waiting on quote and are probably ready to close within a week.
One of those three is interesting: TechCare Plus (12 technicians) requested a quote five days ago, and the AI sent them one automatically based on their team size and feature selection. But they haven't engaged since. The AI flagged them as stalled. I could send a follow-up email, but I want to think about what to say first. Sometimes a forced follow-up just feels pushy.
I decide to wait until Thursday and then check in with a specific question: "Quick question - did our pricing land where you expected, or is there something about the tier we quoted that doesn't fit your team?"
6:15 PM - Closing the laptop
I shut down the laptop and put it in the bag.
Today felt like real work, not automation. The AI handled the routine triage beautifully - I approved 43 responses without changes, which means the system is doing its job. But I spent two hours on decisions and conversations that only I could make: the billing error, the churn email, the tone tuning, the pipeline follow-ups. I sent two meaningful customer emails by hand. I logged a feature request. I overrode the AI's discount suggestion because the AI doesn't understand intent.
Week-to-date, we've brought in about $7,200 in revenue. We lost $1,800 to churn. We gained one solid conversion and probably lost four to pipeline decay. The metrics are real. The work is real. The business is building, slowly.
Tomorrow I need to check on Reyes Family Practice's network issue, nudge three stalled prospects, and figure out why our cold email reply rate dropped last week. The AI will prepare drafts for all of it. I'll review, approve, and occasionally rewrite.
That's what running MSP AI actually feels like after two months.