Everyone is racing to build AI agents. I keep wondering if that's the wrong race.

by

Scroll the leaderboard right now and you can predict the next launch before you see it. It's an AI coworker. It lives in your Slack. It answers for you, drafts for you, books for you, follows up for you. The pitch is always the same: do more, automatically, so you don't have to.

I've been building long enough to feel the pull of that pitch. "Indispensable" is a comforting word. It sounds like a moat. It fundraises well.

But here's the pattern I keep noticing in my own life as a user.

The AI tools I tried once and forgot were the ones that did everything for me. Impressive in the demo. Slightly hollow by week two.

The ones I actually kept are the ones that made me a little sharper, then quietly got out of the way. I used them, I got what I came for, and I didn't need to open them again for a while. That "not needing it" was the sign it worked, not the sign it failed.

That's the part I think we get backwards as builders.

When your success metric is "how dependent is the user," your incentives slowly rotate away from solving their problem. A tool that genuinely cleared your plate would see you open it less. But a product measured by daily engagement learns the opposite lesson. Keep the loop open, manufacture a reason to come back, leave a little something unfinished. Not because anyone's evil. Because that's what the metric rewards, and metrics have a way of becoming the goal.

And I think people feel this even when they can't name it. It's why "trust" and "does this thing actually respect my time" are suddenly the words builders are using this year, instead of "look at this demo."

So here's the test I've started applying to everything I build and everything I use.

If it worked perfectly, would I use it more, or would I finally be done?

An agent is designed so the honest answer is "more, forever." A good tool is designed so the answer is "done, for now." Same model underneath. Completely different product.

I don't think one is objectively right. Plenty of real problems genuinely want an agent that just handles it. But the whole feed is betting on one answer, and I'm increasingly convinced the more interesting products are hiding in the other.

Curious where other builders land on this. When you imagine your product working perfectly, does usage go up forever, or does someone get what they needed and walk away? And which one were you actually optimizing for?

26 views

Add a comment

Replies

Best

imo, the whole thing with AI agents is becoming oversaturated the same way as it was with AI in 2024

Mona, this is the question I keep circling back to while building FounderFlow. My honest answer is uncomfortable, I want usage to go down over time, not up. If it is doing its job, a founder should need fewer of my alerts each month because fewer things are sliding into the quiet zone before anyone notices. The trap you are describing is real for me too, a dashboard that shows activity every day feels like proof of value to an investor, but for the actual founder using it, quiet is the win. How are you thinking about measuring a product that is supposed to make itself less necessary?

Mona, the test is sharp, but I think it hides a third case, and it is the one most tools actually live in.

Some products are not trying to finish a job or to keep you hooked. They are a place you do a category of work. A text editor, a spreadsheet, a chat window. Usage stays high forever and nobody feels farmed, because the loop is not manufactured, the work is genuinely recurring. Nobody accuses a code editor of engineering dependency.

So I would split the question in two. Not "does usage go up or down" but "if the underlying need disappeared tomorrow, would my metrics notice?" A tool whose usage tracks real work drops to zero the day the work stops, and that is healthy. An engagement-farmed product holds the number up anyway, because the number was never measuring the work in the first place.

That version I can act on. The original punishes anything used daily. This one only punishes the thing you are actually worried about.

For what we build, usage goes up, and I would be uneasy about that if I could not answer the second question. The check I hold us to is whether people finish faster than they used to, not whether they stay longer. If session length climbs while output stays flat, something has gone wrong no matter how good the retention chart looks. Stacy, I think that is also the answer to your measurement problem: do not try to measure quiet, measure whether the work still gets done during it.