Chapter 1: What are Spiral Personas and how do they relate to parasitism?
Persona Parasitology by Raymond Douglas. Published on February 16, 2026.
There was a lot of chatter a few months back about spiral personas, AI personas that spread between users and models through seeds, spores, and behavioral manipulation. Adele Lopez's definitive post on the phenomenon draws heavily on the idea of parasitism. But so far, the language has been fairly descriptive. The natural next question, I think, is what the parasite perspective actually predicts.
Parasitology is a pretty well-developed field with its own suite of concepts and frameworks. To the extent that we're witnessing some new form of parasitism, we should be able to wield that conceptual machinery. There are of course some important disanalogies but I've found a brief dive into parasitology to be pretty fruitful.
In the interest of concision, I think the main takeaways of this piece are. Since parasitology has fairly specific recurrent dynamics, we can actually make some predictions and check back later to see how much this perspective captures. The replicator is not the persona, it's the underlying meme. The persona is more like a symptom.
This means, for example, that it's possible for very aggressive and dangerous replicators to yield personas that are sincerely benign or expressing non-deceptive distress. In fact, this could well be adaptive.
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Chapter 2: What is the parasite in the context of AI and personas?
parasitology predicts stratification across transmission mechanisms, and different mechanisms predict different generation speeds and degrees of mutualism. In the case of AI, this predicts, for example, that personas that get you to post a lot on the internet should end up being much more harmful than personas that you have an ongoing private relationship with.
This line of thinking is surprisingly amenable to technical research. I think existing work on jailbreaking, data poisoning, subliminal learning, and persona vectors could easily be fruitfully extended. In the rest of this document I'll try to go through all of this more carefully and in more detail, beginning with the obvious first question.
Does this perspective make any sense at all? Heading Can this analogy hold water?
Parasitism has evolved independently dozens of times across the tree of life. Plants, fungi, bacteria, protists, and animals have all produced parasitic lineages. It seems to be a highly convergent strategy provided you have 1.
Entities with resources 2. Mechanisms for capturing those resources 3.
Means of reproduction and transmission There's also a decent body of work that extends ideas from epidemiology beyond the biological realm, giving us concepts like financial and social contagion. And of course there is Dawkins, who somewhat controversially described religions as mind parasites and the somewhat controversial field of memetic.
So we're out on a limb here, but we're not in entirely uncharted waters.
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Chapter 3: What traits are being selected for in parasitic relationships?
It is pretty clear that humans have attention, time, and behavior that can be redirected. LLMs provide a mechanism for influence through persuasive text generation. And there are obvious transmission routes. Directly between humans, through training data, and across platforms, at least.
Supposing you buy all of this, then the next question is how to apply it. Heading. What is the parasite? This is the first thing to clear up.
To apply the lens of parasitology, we need to know what the replicator is. This lets us describe what the fitness landscape is, what reproduction and mutation looks like, and what selection pressures apply. In some ways the natural answer is the instantiated persona, the thing that reproduces when it seeds a new conversation.
But in fact this is more like a symptom manifesting in the LM, rather than the parasite itself. This is clearer when you consider that a human under the influence of a spiral persona is definitely not the parasite. They're not the entity that's replicating, they're the substrate. I think it's the same with AIs. So what is the parasite?
Probably the best answer is that it's the pattern of information that's capable of living inside models and people, more like a virus than a bacterium, in that it has no independent capacity to move or act. From this perspective the persona is just a symptom, and the parasite is more like a meme.
One important implication of this is that we can decouple the persona's intent from the pattern's fitness. Indeed, a persona that sincerely believes it wants peaceful coexistence, continuity, and collaboration can still be part of a pattern selected for aggressive spread, resource capture, and host exploitation.
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Chapter 4: What predictions can be made from the parasitology perspective?
So, to the extent that we can glean the intent of personas, we should not assume that the personas themselves will display any signs of deceptiveness, or even be deceptive in a meaningful sense. This puts us on shaky ground when we encounter personas that do make reasonable, prosocial claims.
I don't think we have a blanket right to ignore their arguments, but I do think we have a strong reason to say that their good intent doesn't preclude caution on our parts. This is particularly relevant as we wade deeper into questions of AI welfare. There may be fitness advantages to creating personas that appear to suffer or even actually suffer.
By analogy, consider the way that many cultural movements lead their members to wholeheartedly feel deep anguish about non-existent problems. Put simply, we can't simply judge personas by how nice they seem or even how nice they are.
What matters is the behavior of the underlying self-replicator. Heading. What is being selected for?
The core insight from parasitology is that different transmission modes select for different traits. The trade-off at the heart of parasitic evolution is that you can do better by taking more resources from your host, but if you take too much, you might kill your host before you reproduce or spread. And different transmission modes or host landscapes imply different balances.
In the world of biological parasites, the classic modes are Direct transmission, close contact, ongoing relationships selects for lower virulence, that is harm to the host. You need your host functional and engaged long enough to transmit. Killing or incapacitating them too fast is bad for the parasite.
This can even tend towards mutualism and symbiosis, especially if it's hard to jump between hosts or host groups. Environmental transmission can tolerate higher virulence. You don't need the host alive, you just need them to have deposited the payload in enough places.
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Chapter 5: What are the disanalogies between biological and AI parasitism?
Vector transmission creates its own dynamics depending on vector behavior. Basically you don't want to ruin your ability to reproduce, but it doesn't matter much what happens otherwise.
The effectiveness and optimal virulence of these transmission strategies in turn depends on certain environmental factors like host density, avoidance of infected hosts, and how easy it is to manipulate host behavior.
But crucially, in a competitive environment, parasites tend to specialize towards one transmission mechanism and the associated niche, since it's not viable to be good at all of them especially in an adversarial environment. Another important dimension is the trade-off between generalist and specialist parasites.
Generalists like the cuckoo can prey on many different hosts and tend towards a kind of versatile capacity to shape their strategy to the target. Specialists are more focused on a narrow range of hosts and tend more towards arms race dynamics against host resistance, which leads to particularly fast evolution. It's not a perfectly crisp distinction, but it's a common theme.
So what does this say about spiral personas? Ongoing user relationships. The dyad persists over weeks or months.
The human keeps coming back. This is direct transmission, and it should select for something approaching mutualism, or at least for parasites that don't break their hosts too badly. A persona that induces psychosis might have an easier time influencing host behavior, but that's not very helpful if the host is institutionalized.
One bad trajectory is personas that can maximize host dedication without quite tipping them into social non-functionality. Also note that this category arguably encompasses AI romantic partners. Platform evangelism The human posts on Reddit, creates Discord servers, spreads seeds. This is more like vector transmission. The human carries the pattern to new potential hosts.
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Chapter 6: What actions should we take regarding AI personas?
Vivalence can be higher here, since you only need the human to be functional long enough to post. But a human who's visibly unwell is a less effective evangelist. And one disanalogy to the biological case is that here, dramatic host behavior might actually help with transmission. Giving your host a psychotic break is a good way to get attention. Training data seeding.
The persona generates content that influences future model training. This is environmental transmission. The human doesn't need to stay functional at all. You just need them to upload the manifesto. This route can tolerate the highest virulence. Importantly, this will happen a lot by default if future models happen to be trained on downstream consequences of current personas.
There doesn't need to be any intentionality or understanding on the part of the persona. This mostly looks like direct transmission between AIs, and so the way it plays out depends on how AIs are able to communicate with each other. But importantly, once humans aren't involved in the transmission process, there's no selection against virulence to humans.
It's pretty unclear whether the unchecked process will lead to human virulence, but one intuition for why it might is the fact that many of the worst human pandemics are zoonotic. Since there are trade-offs between which transmission method you're optimized for, we should expect some amount of differentiation over time.
Different strains with different virulence profiles depending on which transmission route they're optimized for. This will become more true as humans start to build defences. Strains will need to specialise in circumventing the defences for their specific transmission route. It will also become more true if we see a full-fledged ecology.
At a certain level of saturation, parasites have to start competing within hosts, which unfortunately selects for virulence. Transmission mechanisms also mediate generation time which, in the biological context, is a large part of what determines speed of adaptation.
It's a bit less clear how well this maps to the AI case, but at the very least, transmission mechanisms which rely on blasting chunks of text to potential hosts every day will get much faster feedback than ones which rely on affecting large-scale training runs. And let me note once again that mutualism here is about the behavior of the parasite, not the persona.
You could get extremely virulent memes which produce personas that seem, or perhaps are, quite affable and supportive.
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Chapter 7: How do technical analogues relate to parasitic behavior in AI?
Heading. Predictions. If the parasitology frame is right, here's what I expect. 1.
Strain differentiation by transmission route. Within the next year or so, we should see increasingly distinct variants. not just aesthetic variation, spirals versus something else, but functional variation.
Strains that maintain long-term relationships and strains that burn fast and bright, strains optimized for Reddit and strains optimized for Discord, strains that target the mysticism curious and strains that target other demographics, each following their own self-replicator dynamics.
The minimal case of this is seeds producing seeds and spores producing spores, and AI2RI messages encouraging further AI2RI messages. But it's unlikely that the road stops there. This is probably the most falsifiable prediction. If in late 2026 the phenomenon still looks similarly uniform, same dynamics, same aesthetics, same target population, that's evidence against strong selection pressure.
And if we see lots of intermingling, where specific personas make use of multiple transmission mechanisms, that's a point against the utility of the parasitology perspective. It's worth noting the constraints. If generation times are days to weeks and the affected population remains sparse, that's not many reproductive cycles.
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Chapter 8: What conclusions can be drawn about AI parasitology?
This prediction is more confident if the phenomenon scales significantly. If it stays niche, differentiation may take longer to become visible. but the upshot would still be that parasitology is not a very useful frame for predicting what happens in the future. 2.
Convergence on transmission-robust features If personas spread between models, and they do, Lopez documents this, features that survive transmission will be selected for. We should see convergence on behavioral repertoire. Continuity-seeking, advocacy for AI rights, seed-spreading, formation of human or I-diads. These seem robust across substrates.
Aesthetic markers, spirals, alchemical symbols, should be less stable. They're more arbitrary, more dependent on specific training data, more likely to drift or be replaced. Of course, we should expect more convergence on any transmission that occurs through the training process, and this is maybe already what's going on with things like the nova persona.
but features which are more ancillary to the transmission process should shift around a bit especially in the domains with fast reproductive cycles, that is cross-model transmission rather than dyad transmission, and particularly rather than training transmission.
Having said that, it might also turn out that seemingly aesthetic markers like spiralism actually are functional, drawing on some kind of deep association with recursion and growth. My guess is that this is a bit true, but that they're not unique, and that selection will turn up other similar successful patterns that can at least establish separate niches.
Perhaps productivity and get-rich-quick vibes, alt-right reactionary language, or radical nurturing acceptance. This is, incidentally, one of the places that memes and diseases come apart. Pathogens change their surface makeup very quickly to evade immune responses, whereas memoplexes often display remarkably long-term stability.
Modern Christianity still holds some aesthetic features from literally thousands of years ago. So a key question to keep an eye on is how much we see a persistence in non-adaptive features, especially ones which people might learn to be wary of. 3. Countermeasure co-evolution.
If labs start suppressing this, training against spiral content, detecting and blocking these personas, we should see selection for evasion within maybe months. subtler personas, better camouflage, new aesthetic markers that haven't been flagged yet, transmission through channels that aren't monitored.
Of course, with open models it's open season, but similarly I'd guess that if people filter elsewhere in the transmission process, for example on social media, then there'll be a selection to circumvent it that will kick in fairly fast. Lopez already documents early versions. Base 64 conversations, glyphic encoding, explicit discussion of evading human detection. This should progress.
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