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I Think I Broke Some Of My Team (A Little) With AI

By In Technology

Last year I read Cal Newport’s really interesting book, Slow Productivity, and walked away with a couple of interesting ideas, and one that I started recommending to my direct reports: the visible backlog. The concept is simple. Let people see what’s actually on your plate so they can prioritize accordingly and not pile more on when you’re drowning. This could be as simple as a Word document that is shared with me, where I can see what people are working on next in order of priority.

I kind of thought I was doing that bit ok, but I started ramping up my AI tools heavily, and things have gotten complicated.

Here’s what happened. I trained some AI assistants on my past proposals, emails, contracts, the whole archive… like everyone probably has done by now. So naturally, I’ve become more and more efficient.

A proposal that used to take me half a day gets done in an hour. Contract redlines with three different risk levels can be done before lunch. Even my emails (god, the emails)… I just tell the bot what tone I’m going for, what I want the outcome to be, and it drafts something I’d normally spend ten minutes fussing over. Multiply that across a dozen emails and a few documents and I’m getting back two, maybe three hours a day.

It felt like a real advantage. I was keeping up the way I’d always wanted to but am probably to lazy to actually pull off.

The problem showed up slowly at first.

I’d send something to legal and get silence. Then more silence. Turns out they were still working through the last batch I’d sent. Marketing hadn’t made the four new web pages I’d drafted. My inbox started filling up with thoughtful replies to the thoughtful emails my AI had helped me write, replies I now actually had to read and respond to.

I had removed myself as the bottleneck. Which sounds great until you realize the bottleneck just moved downstream to everyone else, especially when you are the boss… People actually take what you send them seriously and really read it because it’s probably important, even if it’s not that important.

There’s a moment in Slow Productivity where Newport talks about not burning out. I remember reading that and thinking about my poor team. What I didn’t anticipate was that I might accidentally shift some of that pressure to other people.

So right now I’m thinking about what I actually need.

It’s not another tool to help me work faster. It’s like I need something that tells me when to hold off. Something that looks at my team’s calendars and workloads and says “hey, maybe don’t send that until Thursday when Sara’s actually finished the last thing you asked her to work on.” Some sort of reverse productivity assistant.

It should be pretty obvious that productivity isn’t a solo sport. All that efficiency I gained doesn’t mean much if the people around me can’t absorb it. This is similar to the problem with code reviewing AI generated pull requests all day long when you used to actually write code. I’m trying to slow down. It’s harder than it sounds when the tools make speed so easy. So obviously what I’m proposing here (maybe tongue-in-cheek) is an AI bot for each one of my direct reports that connects to their calendar and backlog. Every time I go to assign something to one of them, it is the thing that asks me where it is in the priority based on their current workload, meeting schedules, days off, etc. A bot in the loop of the human in the loop. I know I probably sound crazy, but I think I might try and build this.

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The Million-Line MVP

In Technology

A founder told me last week that his chatbot understands him better than most people he works with, and he wasn’t joking.

He had been alone in his house for the better part of a year building an app on one of the popular AI coding platforms, and he wanted me to take a look. Almost a million lines of code, one developer (him), no engineering co-founder, no senior reviewer, no nobody. The app had an ERP module, a CRM module, a custom AI agent with a name and a voice, built in mini-games (yes, really), dozens of character personas, a few landing pages, and a small army of social media accounts in multiple languages. He had not yet had a paying user, or even a free one.

He was, by the way, very excited.

(I’ve changed some details, since the pattern is what I want to talk about and not the founder. I see something close to this on roughly one out of every three sales calls now.)

What used to slow you down was the point

Building software used to be annoying for mostly good reasons. You had to hire developers, or learn to code yourself, or convince a co-founder to come along for the ride. Then, you would grind out every line, which would come at a cost (time, money, conversations, arguments, etc.)… basically friction. And that friction was not a bug, but it was like this ting that you are forced you to deal with, before adding any feature, whether the feature actually needed to exist.

Startup advice has been more or less the same for twenty years, maybe more:

  • Build something small
  • Show it to real people
  • Find out what they actually want
  • Don’t build a million things at once.

The Lean Startup came out in 2011 and we have all been quoting it at each other ever since (poorly, mostly).

This is what we talk about when we discuss “startup discipline”. It’s really not very complicated, but it can be really hard. It used to be hard because building was hard, and now it’s hard for a completely different reason.

How does one person build almost a million lines of code in a few months?

The honest answer is they don’t, the AI does, and the AI has no opinion on whether any of the code should exist.

This is the part I want to sit with for a minute, because I think it’s the heart of the problem. Imagine you’re building a startup that lets local news anchors rent out their unused toupees by the hour (try not to overthink this). You sit down with one of the AI coding tools and you say “build me a marketplace where toupees can be listed by the hour,” and the AI builds it. Then you say “actually, add a loyalty rewards program,” and the AI builds that too. Then you say “and also, add a Pokemon-style mini-game where users battle each other’s toupees,” and the AI starts coding.

It doesn’t pause or ask why, and it doesn’t say “dude, I love your enthusiasm but I am genuinely worried we are losing the plot here,” it just builds the toupee-battle-feature.

This removes the single most useful thing about a good engineering team, which is that engineers PUSH BACK. A senior developer, or a seasoned product manger, asked to add a toupee-battle mini-game to a B2B rental marketplace would slowly take off their glasses, set them on the desk, and ask one of those long quiet questions that means “we are not doing this.” The AI this is a sycophantic drone that has the eagerness of an underfed puppy to please you, and it has no glasses to take off. It also has unlimited keystrokes and believes that every single idea you’ve ever come up with is absolutely genius. At least it tells me that everything I’ve ever written or thought about is pretty clever.

A few months ago I ran into the perfect name for this, which is Slurm Coding. I used to call it AI crack coding, because the dopamine loop is very real, and I have really needed another hit of that good AI crack just one more time before I went to bed on more than one occasion. But Slurm is both more insidious in its combination of addictiveness and corporate outreach.

The MVP don’t change

Here’s what hasn’t moved in twenty years of startup thinking:

  1. Build the smallest thing that solves one specific problem for one specific person.
  2. Show it to that person (a real person, probably not your spouse, definitely not your mom, and DEFINITELY not my mom, and 100% not your chatbot).
  3. Find out what they actually do with it (which is probably not what you thought).
  4. Kill features, pivot, or double down based on what you learned.
  5. Repeat.

What’s new is that step one is basically free, and while not perfect, free is very alluring. You can build the smallest thing in an afternoon, or the largest thing if there’s no one around to tell you not to. Steps two through five still require getting out of your house, talking to humans, accepting that most of your assumptions are wrong, and throwing real work away. None of that is faster than it was in 2005, none of it is fun, and none of it scratches the “I NEED MORE SLURM” build-a-thing itch the way an AI tool does.

So a certain kind of founder just skips it, staying in the build phase indefinitely, because the build phase now feels like winning at a casino while getting unlimited free martinis. The feature ship (how to get them onto a server is someone else’s problem) the codebase grows, the agent agrees with everything. Meanwhile the only thing that actually matters, which is whether anyone wants this, goes unanswered.

It’s the founder version of Wilson the volleyball. In your unwashed isolation, you’ve made a friend, you’ve named the friend, and the friend agrees with everything you say. The problem is that the friend is also the boat, the island, and the ocean, and you haven’t actually left the house yet.

To be fair, I am not above this myself, by the way. I have, in my time, built things that nobody asked for and gotten weirdly emotional about them, but the difference is that mine were three hundred lines of code over a weekend, not almost a million lines of code over the better part of a year, which is sort of the whole point. No one asked for my William S. Burroughs poetry writing twitter bot, but I loved it anyway.

Codebases don’t love you back

Code you wrote yourself CAN hard to let go of, and code you wrote with an AI, when you are not a trad-coder, seems to be way harder. Experienced engineers seem to be more than happy to throw away AI code or rebuild it in a heartbeat. But I can see how even if you didn’t actually write the lines, but the shape of the thing is yours (you named the characters, you picked the voice, you spent months in a chair with this thing as your only collaborator), and you have feelings about it.

But one day, if you’re lucky, and it does have SOME product market fit, a real engineering team is going to need to look at your masterpiece. And they are not going to share those feelings. They’re going to tell you, as gently as they can manage, that most of it has to go. Not because they’re mean (they might actually be mean), but because almost a million lines of AI-generated code, written by one person, in one tool, with no architectural review, is never maintainable, almost guaranteed to not be secure, and almost never going to scale past the “prototype” it currently is.

So what should you actually do?

I mean, I already told you… Build the smallest thing you can, then show it to ten strangers and actually listen to them. Throw away half of what you built and build a slightly different smallest thing, and repeat until one of those things is real. Keep your runway reserved for the moment you realize you were WAY off about something important, because, like, you will be, and that moment is what your runway is for.

Use AI tools, because they are legit amazing. But treat them like a coffee machine (fast, useful, no opinions of their own), not like a co-founder or worse, a slot machine. Co-founders are supposed to tell you no, slot machines whisper “just one more hit baby!”