It's 8 AM on a Sunday and Four AI Agents Are Running My Companies

It's 8 AM on a Sunday in May. Swati is asleep in the next room. The pour-over is gone. I forgot to turn on the AC, so I'm a little sweaty, which is just gross. I've been talking into a chatbot for two hours about my own life, for a writing project that's supposed to end with five essays on what I think I've figured out about AI and work.

In the other tabs of this browser, three things are happening without me.

In one tab, an AI agent is running a deep security audit on SmartCue, a B2B SaaS company I founded in 2020 and still run on the side. In another tab, a different agent is doing competitive analysis on MarkIT, my family's Tally Partner business in Mumbai, and rewriting parts of its site in real time. In a third tab, a third agent is setting up the day's Meta ads campaign for Gramms, a B2C mobile app I also run on the side. I haven't touched any of those tabs this morning. I gave each agent its budget and its context yesterday. They are working.

Harvard Business School published a case study on the AI program I run at my day job at OneDigital. It came out in April. It's called Building a Digital Workforce. The lead author is Shikhar Ghosh, a professor at HBS and a principal investigator at their AI institute, a person Fortune once called "Master of the Internet Universe." There is a setup case before it covering the strategic decision that led to the program. He chose to write both. My CEO and CPO co-wrote a book about the program for Wiley; it ships this summer. I am quoted in it five times. Harvard, MIT, and UCLA invited me to co-author an academic paper on the same topic; that one comes out later this year.

I went to a small private liberal arts college in Oregon, Willamette, on a full scholarship. My Dad could have paid. He didn't want to bet on a mediocre student. So I had to earn the bet by scoring well enough to get the scholarship myself. That worked. I graduated in 2010 into the worst job market in a generation, took an H-1B at a healthcare startup called hCentive that built the insurance exchanges for the Affordable Care Act in Colorado, Kentucky, and a few other states. I lived in DC, then Denver, then in 2018 moved back to India to be closer to family. I founded SmartCue in October 2020. In November 2024 I joined OneDigital as the person who runs their AI program. That is 18 months ago, in elapsed time. It still feels like I just started.

I am 40. I am not, by any traditional measure, the kind of person Harvard professors choose to write case studies on, or invite to co-author papers with. Or rather, I wasn't. I am still trying to figure out what changed.

What I think might have changed

Here is the thing I keep noticing. AI is good at doing the work I tell it to do, very precisely. It is bad at deciding what work to do. It is a tireless executor and a useless visionary. And the bottleneck for most knowledge work used to be the executor. There were a lot more people with ideas than people who could ship them. Calling someone an "ideas guy" was a quiet insult.

I am, by traditional measures, an ideas guy. I am fluent in business strategy because I read a lot, I think about it a lot, and I have shipped enough in the last fifteen years to recognize when I am seeing the same shapes again. I am much less fluent in the granular execution work, the SQL queries, the React components, the YouTube ad-copy variants, the SEO grunt work. That is the work other people used to have to do for me, or that I had to learn just-enough-to-be-dangerous to do badly myself.

That gap is what AI inverted. The execution layer got cheap. The articulation layer, knowing what to ask for, in what order, with what context, against what fitness function, got disproportionately more valuable.

I am not claiming this as an insight. The people who actually study workforce transformation already know it; that is the thesis of the book my CPO co-wrote. The reason it bears repeating is that the practical implications are still being missed by smart people I know. AI didn't make smart people obsolete; it changed what "smart" buys you. If you can articulate clearly, AI gives you a ten-person team. If you can't, AI gives you a slightly faster autocomplete and a lot of slop.

What changed for me, specifically, is that the articulation work became my entire job. At OneDigital, my team and I don't write the AI Coworkers' code; we write their job descriptions, their training programs, their performance reviews. We hire them, supervise them, fire them when they don't perform. (I have fired a lot of Coworkers, mostly versions of the same Coworker that didn't quite work and got replaced. There is a joke in the book that when AI becomes sentient I'll be first in its firing line.) On the side, the same articulation work runs my eight properties. The browser tabs open right now are the proof.

The receipts

Three weeks ago, in one of these biographer sessions, I told the chatbot the consistent gap across my eight properties is GTM. I can build with AI. I have never been great at selling, distributing, marketing. That was true three weeks ago. Today my Meta ads campaign for Gramms is running daily, on a budget I set, executed by Claude without me touching it. I literally just give it the budget. It knows the context that it needs for setting up the campaigns. It is, in the most boring possible sense, off to the races. I am also orchestrating an influencer campaign for the same property, also via AI. The gap isn't gone. It is narrower than it was three weeks ago. The same lever that closed the build gap is closing the distribution gap.

A different property, MarkIT, is my family's Tally reseller and consulting business in Mumbai. Mom started it on her own in 1999, ran it for 18 months solo, then convinced Dad to join. Dad ran it for the next two decades. My brother Kshitij runs it now. I rebuilt its website using AI on weekends, mostly over about ten hours of focused work spread across a few weeks, and traffic went from roughly 3,000 monthly visitors to roughly 16,000. Most of the work was AI iterating on SEO basics and content. No agency. No external consultant. The hosting bill stayed about the same. The SEO bill went to zero.

SmartCue, the B2B SaaS I founded in October 2020, has been running solo for the past year. Zero developers. The AI handles the engineering work I would have needed three or four engineers for at our previous size. Customers still call. Revenue still comes in. I have not had to hire to keep it alive.

At OneDigital, the AI Coworker program has been live for about 12 months. In that 12 months, adoption has reached 52% of the workforce. That number matters not because of the percentage in isolation, but because of the time. Adoption usually decays back toward zero once the launch champagne wears off. Reaching 52% sustained adoption inside a 6,000-person traditional consultancy in 12 months is not normal. The thing that makes it possible isn't the AI; it is the boring discipline behind it. Three-phase coworker lifecycle. Five-tier human fluency model. Mandatory training. Supervisors running bi-weekly 1:1s with their AI Coworkers like they would with humans. None of this is futuristic. None of it is hard to explain. It is, on the inside, deeply unsexy.

The weirdness of being studied

I keep waiting for someone to tell me they got the wrong person.

The book chapter that quotes me four times has me as the deployment expert. The HBS case study has the program I run as the subject. The joint paper has me as a co-author, sitting in working sessions with researchers from three universities, contributing to something that will be peer-reviewed and cited by other researchers. None of that was something I aimed at. I joined OneDigital because the work seemed interesting and the boss seemed like someone I could learn from. Eighteen months later there is a Wiley book about what we did.

When this kind of recognition started showing up earlier this year, my honest first reaction was bewilderment. I know people who went to Harvard MBA who are smarter than me; they are not getting case studies written about their work. I know operators in my Twitter feed who shipped more than I did; they are not getting quoted in Wiley books. I consider myself, in the most operational sense of the word, mediocre. I read the business books most operators read. I have the kinds of opinions most operators have. I have not had a single insight in my life that I could honestly call original. What I have done, repeatedly, is keep showing up to bets that other people made on me. Tarun and Manoj at hCentive in 2010, Vinay at OneDigital in 2024. And I have tried not to let any of them down. That is it. That is the entire operating principle.

Maybe what changed is that the kind of mediocrity I have, the kind that is good at articulating, good at showing up, good at not letting people down, turns out to be the kind of mediocrity AI multiplies. Maybe the kind that doesn't get multiplied is the kind that needed perfect technical execution to defend its ideas, and AI ate that defense. That would be embarrassing for the people who built their identity on it. I don't know if that is what is happening. I am an operator inside one company, watching one program work; I am not an economist with a dataset.

What I can say honestly is this: the people who study how AI changes work are looking at the work I do. So whatever I am doing is real enough to study. I just don't think the smart people in my Twitter feed have the right model of what they are looking for. They are looking for the brilliant builder with the perfect AI workflow. They are missing the mediocre articulator with the boring change-management program.

What I'm not telling you

I am not telling you ideas guys can ship now. I am one. I am still not sure I have shipped enough to say that. Three of my eight properties are basically dead. Two are toys. Two pay their hosting bills and a little extra. SmartCue is the only one that is a real business, and its biggest growth windows happened before AI; the current AI-augmented era at SmartCue is more about running it lean than about growing it fast. The body of work is real. It is also small. The honest version of my résumé is: 40 years old, two businesses that mattered, 18 months of running an AI program at a 6,000-person company, mostly because I happened to be the right person for the right job at the right time.

I am also not telling you to be like me. I think the through-line in my career has been "why not, what is the worst that could happen", a borrowed line from my mother and one I keep using because it is accurate. That posture compounded in an era where the cost of starting things kept falling. It would not have compounded in a different era. I happen to be middle-aged at a moment when the leverage on "why not" got obscene. That is lucky. That is not strategy.

What I am doing here, on this site, is writing down what I think I see while I still see it. Mostly for myself. So that if any of this changes, if AI plateaus, if the program at OneDigital falls apart, if the receipts stop arriving, I can come back and read what I thought was happening before any of it shifted. The first thing I am writing down is the case Harvard published. The next ones will be the rest of the eight properties, each of them an experiment in something AI now makes possible. I will be wrong about some of them. The point isn't to be right. The point is to have a record. A notebook, not a manifesto.

Closing

It is 8 AM on a Sunday in May. The pour-over is still empty. Swati is still asleep in the next room. I am still a little sweaty, because I still have not turned on the AC. In the three other tabs of this browser, SmartCue's security audit is still running, MarkIT's competitive analysis is still going, and Gramms' Meta ads campaign is mostly set up. I will review what each of them produced later this afternoon. The work happens regardless.

I am not telling you I figured something out. I am telling you the people who study this stuff are looking at the work I am doing. I am still trying to figure out what to call it. I really hope it stays that way.