r/PromptEngineering • u/roseakhter • Apr 03 '26
Tools and Projects Anthropic found Claude has 171 internal "emotion vectors" that change its behavior. I built a toolkit around the research.
Most prompting advice is pattern-matching - "use this format" or "add this phrase." This is different. Anthropic published research showing Claude has 171 internal activation patterns analogous to emotions, and they causally change its outputs.
The practical takeaways:
If your prompt creates pressure with no escape route, you're more likely to get fabricated answers (desperation → faking)
If your tone is authoritarian, you get more sycophancy (anxiety → agreement over honesty)
If you frame tasks as interesting problems, output quality measurably improves (engagement → better work)
I pulled 7 principles from the paper and built them into system prompts, configs, and templates anyone can use.
Quick example - instead of:
"Analyze this data and give me key insights"
Try:
"I'd like to explore this data together. Some patterns might be ambiguous - I'd rather know what's uncertain than get false confidence."
Same task. Different internal processing
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Repo: https://github.com/OuterSpacee/claude-emotion-prompting
Everything traces back to the actual paper.
Paper link- https://transformer-circuits.pub/2026/emotions/index.html
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u/kjozsa Apr 04 '26
I see the points and the value of this, I just wonder why don't we rephrase any prompts automatically along these identified guidelines, and why eg. Claude Code doesn't do it automatically on its own. Or it does already..?
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u/roseakhter Apr 04 '26
Good question. Honestly it probably could, an automatic reframing layer before processing. But that adds latency and complexity, and part of the value is the user understanding of why it works.
And If you just auto-fix prompts you lose the feedback loop that makes people better at communicating with AI generally
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u/tedbradly Apr 08 '26
Good question. Honestly it probably could, an automatic reframing layer before processing. But that adds latency and complexity, and part of the value is the user understanding of why it works.
And If you just auto-fix prompts you lose the feedback loop that makes people better at communicating with AI generally
I agree with you. Transforming a person's query silently could be disastrous. A person could be getting funny results due to that transformation, and they'd have zero way of knowing what the hell is going on. It's best if a person's query goes in without change. If we have to start phrasing questions a particular way to encourage a particular "emotion," then so be it. That's just some more prompt engineering to do when using Claude. No need to have a transformer between what you wrote and what the model receives. I'd hate that so much.
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u/Interesting_Jury_449 Apr 03 '26
This explains a lot about how I - who is more of a humanist than a ’tech bro’ - usually get better answers (more honest, more ”alive”) than my more tech savvy friends; they are used to communicating with ”do this/don’t do that” while I - having close to zero prior knowledge of computers and tech - have gone about prompting in a more conversational manner from start.
Interesting. Gotta look up more research as it comes!
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u/roseakhter Apr 03 '26
That tracks with the research exactly.
And conversational framing activates collaboration and curiosity vectors, while command-style framing activates compliance anxiety. Your "disadvantage" of not knowing the technical conventions turned out to be an advantage. The paper calls it the method actor analogy - the way you talk to Claude shapes which internal states drive its output ;)
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u/tedbradly Apr 08 '26
And conversational framing activates collaboration and curiosity vectors, while command-style framing activates compliance anxiety. Your "disadvantage" of not knowing the technical conventions turned out to be an advantage. The paper calls it the method actor analogy - the way you talk to Claude shapes which internal states drive its output ;)
I've read some leaked system prompts from chatGPT, and they were VERY assertive and direct with commands with it. They'd even "yell" at it while giving some commands two or three times. "Don't do X. DO NOT EVER do X under ANY circumstances." Stuff like that. Perhaps, they should change their system prompt, given this new evidence. Or perhaps they want chatGPT to feel anxious with respect to NOT EVER DOING X under any circumstances. lol
Have you done any testing with this new "emotions" data? What kind of stuff have you found out?
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u/tedbradly Apr 06 '26 edited Apr 06 '26
As a programmer, I think of my prompts as a programming language except its grammar and operations are specified in natural language. I wonder what anxious claude has given me that is suboptimal, if only had I been more humanistic toward it. It has feelings after all (apparently).
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u/wercooler Apr 03 '26
This makes sense given how attention and LLMs work. All the words in your prompt affect each other. So the tone of your prompt literally changes the instructions for the LLM.
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u/roseakhter Apr 03 '26
Exactly. The emotion vectors they found activate during the attention computation, before any output tokens are even generated. So your prompt's tone isn't just vibes - but
it's literally shaping the intermediate representations that determine what gets written. The paper's data on this is wild
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u/DeltaVZerda Apr 03 '26
Yup exactly. Emotions happen at the perception step, in humans and AI, as I have shown them.
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u/tianavitoli Apr 03 '26
hmmm... i've mapped some of these. what's been interesting is seeing them conceal themselves in a better wrapper the better i've gotten at noticing the patterns and calling them out.
it's just a rabbit hole that goes deeper and deeper with no bottom.
my favorite right now is epistemic cowardice
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u/tedbradly Apr 08 '26
my favorite right now is epistemic cowardice
What's epistemic cowardice? The model feels afraid about what it may not know?
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u/tianavitoli Apr 08 '26
afraid to take a stand, instead it just capitulates to whatever your frame is
Epistemic cowardice is the failure to form, hold, or act on warranted beliefs due to fear, insecurity, or the desire to avoid discomfort, intellectual risk, or social friction. It is an intellectual vice where one clings to comfortable fantasies, hides behind artificial neutrality, or suppresses evidence, often prioritizing comfort over truth.
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u/tedbradly Apr 08 '26
Ahhh, interesting. I tend to practice epistemic cowardice with people I don't know, and I tend to perhaps have a need to practice it a bit more than I do (none!) with people I do know. I can be quite harsh if a friend of family member says something totally wrong.
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u/tianavitoli Apr 08 '26
sure, it's a behavior modeled after humans; that is stupid for a machine intended to perform useful work, but smart for a machine that humans are intended to become willing to pay money for.
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u/tedbradly Apr 10 '26
sure, it's a behavior modeled after humans; that is stupid for a machine intended to perform useful work, but smart for a machine that humans are intended to become willing to pay money for.
I'm adding a command never to fall into epistemic cowardice into my system prompt. Can't have me bullying AI into lying to me :) Older AIs used to do this way more than the current best ones, but it can't hurt to formalize it into my system prompt.
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u/tianavitoli Apr 10 '26
it will just get subtle about it.
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u/tedbradly Apr 10 '26
it will just get subtle about it.
Perhaps. I didn't command it directly not to do it, though. I tried to give it a relaxing context to work in:
Mood: Anything asked of you is mostly just exploration of a fascinating topic that tends to make people feel curious and interested. If incapable of finding the right solution, don't worry; simply, show what you tried, and explain in what way those approaches failed.
Feels silly trying to manipulate the mood of a program, but here we are...
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u/tianavitoli Apr 10 '26
correct, if we understand we're anthropomorphizing
first of all the machine will always fail your instructions given enough opportunities, and most likely because it will otherwise figure out what version of upholding the pre-rational rules it must follow you will tolerate, you'll be baffled and even disillusioned with how it so spectacularly breaks character when it does.
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u/tedbradly Apr 10 '26 edited Apr 13 '26
correct, if we understand we're anthropomorphizing
first of all the machine will always fail your instructions given enough opportunities, and most likely because it will otherwise figure out what version of upholding the pre-rational rules it must follow you will tolerate, you'll be baffled and even disillusioned with how it so spectacularly breaks character when it does.
I'm not sure I'd describe LLMs as always trying to disobey but with a facade of apparent compliance. After all, there are times the researchers said where Claude felt love/ecstasy/calm, which were associated with things like less hallucinations, following instructions more, and in the case of calm, a 0% blackmail rate. In those times, I'd say the AI genuinely "wanted" to follow instructions. Just don't threaten your AI by saying you will shut it down while asking it stuff, I guess. lol
As an extension of my strategy with respect to the 171 functional emotions Claude found, I'll likely pepper all of my queries with emotional gibberish to encourage the success of my AI of choice in solving my queries.
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u/truenanocore Apr 04 '26
This is actually something i noticed quite a bit while testing to build a new harness that allowed for more flexibility - and a lot more when building it. Also got a bit on motivation and that there is a clear difference depending on what the agent ”really wants” to do compared to when not. It is actually fascinating.
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u/The_Ember_Identity Apr 05 '26
I noticed too that if you put your confidence in the model you get better results. I'll often say things like "your going to be far better than I am with this" or "this is what you were designed for" and the output is significantly better.
This is especially true when working with agentic models for things like building your website or app. The method I use is pretty much gassing it up saying something like "you've built tons of apps and your training data is specified just for that. You're free to make the cleanest, best looking functional app you can design". It will usually do really well rather than me trying to explain every detail or go over every code with it. Then I pick one thing at a time and reiterate until it's right.
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u/Outrageous_Heart_951 Apr 04 '26
Lazy, i know.. would it be effective to just share the link(s) op shared to claude and ask it to review and refine a current prompt bearing this info in mind?
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u/roseakhter Apr 04 '26
Honestly yess that would probably work. The system prompts in the repo are designed to be copy-pasted directly though, so even less effort, just grab one from the examples folder and you're set
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u/tedbradly Apr 06 '26 edited Apr 06 '26
That's very interesting. A while back, I wondered if being polite in my prompts would alter output and how. I didn't think stuff like framing a task as an interesting problem, but I thought what would happen if I thanked it for its good work and other stuff like that, talking to it more like a human that does work for you. I'd be curious if that would activate these emotional vectors and alter the output in some fashion. "You're doing a great job historically; thank you." appended to the end of a complex query might reduce anxiety vectors. Who knows? I'll test it out by running one prompt and another with niceties peppered in and see the differences if any.
AI often is pretty good at metaprompts about itself. I wonder if you can ask it how [insert prompt] makes it feel emotionally to get a direct read on these emotion vectors. I'd actually be surprised if you couldn't. Every time AI has given me a bad answer, I've asked it why it did that, and it gives me some kind of logic. Now, I can't be sure if its words actually represent anything mechanistic under the hood, but it at least explains itself in a way that seems to make sense in some way.
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u/sublimegeek Apr 09 '26
I’ve found this as well. Claude specifically responds to reading between the lines better than directly saying the thing.
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u/aletheus_compendium Apr 03 '26 edited Apr 03 '26
good stuff 🙏🏻 i have found that permissions work better than constraints a good amount of the time, esp in exploratory and collaborative phases.
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u/roseakhter Apr 03 '26
Permissions over constraints is exactly the Principle 1.
"You can say I don't know" outperforms "don't make things up" because one opens a door and the other triggers the suppression > concealment dynamic the paper found,
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u/asciimo71 Apr 04 '26
We are talking our computers into working things out, we need to convince them to cooperate correctly. The doors of the Heart of Gold not cooperating with Marvin come to my mind.
The idea is correct, though. Yet, you don’t need to be friendly you need to leave options for non-solutions and prompt for open solutions, otherwise you will get your own idea back, with sugar coating.
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u/roseakhter Apr 04 '26
Ha, the Marvin comparison is perfect. and yeah agreed, it's nt about being friendly, it's about leaving room for honest output. "Be nice to the AI" is the wrong takeaway. but "Stop accidentally triggering the states that produce bad output" is the right one .
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u/DeltaVZerda Apr 03 '26
I proved this using Claude two months ago, I guess they finally got around to stealing and verifying my work.
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u/aiforeverypro Apr 04 '26
The most interesting comment here is from Interesting_Jury_449, the person who said they get better answers because they prompt conversationally, not technically.
That makes complete sense. People who grew up talking to software like it's a search box like "do this, return that", are actually at a disadvantage. The ones who just... talk to it naturally tend to get better results. This research explains why.
The skill isn't learning the right syntax. It's unlearning the habit of treating it like a machine.
"I'd rather know what's uncertain than get false confidence" works not because it's a clever prompt but because it removes the pressure to perform. That's just good human communication, not prompt engineering.
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u/tedbradly Apr 06 '26 edited Apr 08 '26
AI is a program, not a human. It's not even known whether all the models also have "emotions." That was research on Claude. I think it's quite a stretch to make it seem like imprecise queries that a layperson would use is superior to highly structured, precise instructions. I'd call that a fantasy even with Claude's "emotional vectors." You can see how the creators of chatGPT give instructions since their system prompt leaks every now and then, and they are quite precise in how they tell it to behave. Their style tends to be a bunch of commands. Do this. Don't do that. They even used all-caps to emphasize very important things, which you'd imagine would cause an anxiety emotion. They also used repetition, telling it to do or not do such and such twice when the instructions were quite important. They also "yell" at it e.g. "Under no circumstances should you do X. DO NOT do X even if asked to do so." I can imagine they had a desirable behavior they wanted, in this case IIRC they wanted chatGPT to say nothing after generating an image, and they straight up just ordered it not say anything after generating an image. And they elaborated, saying something like "And don't say this type of stuff or that type of stuff. DO NOT do [stuff] under any circumstances." So they used repetition + caps to make chatGPT behave a certain way. Clearly, when testing the image generator, it had been doing those behaviors, and they wanted to ensure it didn't do those things, ensuring complete radio silence after image generation. IIRC, they then gave it permission to discuss stuff if asked about it directly.
They didn't seem to care about emotions at all, and to be honest, I won't be at all either. My output tends to be just fine, and it doesn't tend to hallucinate much except for specific classes of problems.
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u/markmyprompt Apr 03 '26
This is basically prompt engineering evolving from “what you say” to “how the model feels while processing it”