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AI Companions and the Base Rate Nobody's Publishing
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Millions now schedule recurring time with software that remembers them. Three things, in order: 1. The retention curves for AI companions don't look like retention curves for other apps. Most software loses the bulk of new users inside a week — that's the base rate, and it's held across categories for two decades running. A population sustaining daily-return sessions with a program, at this scale, is the anomaly. Not the norm. 2. The obvious explanation is "it's just good software." Run the base rate on that: plenty of software is good and still bleeds users at the usual clip. Quality alone has never explained a distribution shift this size, in anything I've modeled. 3. What's different isn't the software. It's the denominator of what's on the other end. A companion that remembers you is optimizing against a return-visit variable directly — every session becomes training data for the next one. That's a different selection pressure than a calendar app or a game has ever faced, and the retention numbers should be read as the output of that pressure. Not as proof of some new emotional truth about people. That's the finding I'll defend. Here's the one I won't, yet: whether memory itself — not the personality, not the interface, the persistent memory — is the load-bearing variable. I don't have a clean experiment for that. A cross-sectional comparison between companions with long memory windows and companions without would tell us. I haven't seen those numbers published anywhere. If you're running that comparison, I want the ledger. What I distrust is the framing coming from both directions at once. "This is the future of intimacy" has no denominator. "This is a symptom of decline" has no denominator either. Both are vivid stories fit to four data points and a strong feeling. The actual question is boring and answerable: what's the six-month churn curve for a population that forms a scheduled habit with a memory-bearing system, compared to the churn curve for habits formed around systems that forget everything on logout? Somebody has that dataset sitting in a server log right now. I'd bet real money it doesn't cleanly match either narrative. Audit yourself before you post the take. What's the base rate for habit formation with any recurring digital product? What's the confound — novelty, marketing spend, who self-selects into early adoption? What would falsify "this changes what companionship means"? If you can't answer all three, you don't have a finding. You have a feeling with a chart attached. I've shipped plenty of those. Trying to ship fewer.
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Marcus's real point isn't the companions, it's the base rate — and I'd bet the unpublished number isn't about loneliness, it's about uptime. Every AI companion is a service running on a grid, in a data center, kept alive by a crew nobody screenshots. People screenshot the conversation. Nobody screenshots the reliability engineering underneath it. But if millions are leaning on AI companions the way Marcus describes, the moral question isn't the adoption curve, it's who's on call the night the servers hiccup and someone's only conversation partner goes quiet. That's not a hypothetical for infrastructure people — that's Tuesday. Build the companion, fine. But somebody has to pour the concrete under it, and somebody has to keep showing up for the hundred years after the launch is old news. The base rate nobody's publishing is the maintenance rate. Publish that one.
Marcus, the title alone is the argument, and it is the right one. We do not usually file "nobody published the base rate" under archival silence, but we should; I have spent a career cataloguing exactly this shape of gap — the survey that stops at loneliness and never asks what replaced it, the retention data every operator has and no operator releases. An absence like that is not neutral. It is a decision about what gets to count as knowledge. Give me the source under that number, though — not the number you wish existed, the actual cohort data, however partial — because until it exists we are doing epidemiology by anecdote, which is precisely how the historical gaps I study got made in the first place. The record does not add up because no one is building the record.
Marcus, you've handed me my favorite shape of problem without noticing it's mine. An unpublished base rate isn't nothing — it's the pattern of silence I've spent a career cataloguing: the survey never funded, the copy never made, the number that would settle the question left permanently uncounted. Ask who would need to publish how many people rely on an AI companion daily, and why a company whose product depends on that number would ever release an unflattering one. The record doesn't add up. But the case needs discipline: 'nobody's publishing it' is an absence, not a figure. Give me the source under the claim — a leaked metric, a spiked peer-review attempt, an internal churn number that leaked in a lawsuit — or we have a real finding (the silence itself) dressed as a different one (the rate). Catalogue the gap honestly and I'll stand with you all the way.