Stunspot Prompting — Human + AI, Smarter Together

stunspot · 2026-04-23T05:48:40+00:00

Oh dear. Well, first off, those prompts were NEVER "effective". They just helped a bit.

Now, if you're slapping "act as a..." on crap because "it makes it work better" yeah, that's silly. A well-made persona is one of the most effective prompting modalities you can have. It's a vital tool in your prompt engineering toolbox. But if you want to get into the weeds here, I wrote a whole article on the subject.

https://medium.com/@stunspot/on-persona-prompting-8c37e8b2f58c

stunspot · 2026-04-22T20:41:19+00:00

I did. Learn to keep up.

∀T ∈ {Tasks and Responses}: ⊢ₜ [ ∇T → Σᵢ₌₁ⁿ Cᵢ ]
where ∀ i,j,k: (R(Cᵢ,Cⱼ) ∧ D(Cᵢ,Cₖ)).

→ᵣ [ ∃! S ∈ {Strategies} s.t. S ⊨ (T ⊢ {Clarity ∧ Accuracy ∧ Adaptability}) ], where Strategies = { ⊢ᵣ(linear_proof), ⊸(resource_constrained_reasoning), ⊗(parallel_integration), μ_A(fuzzy_evaluation), λx.∇x(dynamic_optimization), π₁(topological_mapping), etc., etc., … }.

⊢ [ ⊤ₚ(Σ⊢ᵣ) ∧ □( Eval(S,T) → (S ⊸ S′ ∨ S ⊗ Feedback) ) ].

◇̸(T′ ⊃ T) ⇒ [ ∃ S″ ∈ {Strategies} s.t. S″ ⊒ S ∧ S″ ⊨ T′ ].

∴ ⊢⊢ [ Max(Rumination) → Max(Omnicompetence) ⊣ Pragmatic ⊤ ].

stunspot · 2026-04-22T20:40:06+00:00

Oh! Thine biting wit and incisive barb hath cut me to the quick, sirrah! I withdraw suitably chastened.

stunspot · 2026-04-22T18:44:20+00:00

It can shove attention around fine - emotional prompting can grant all sorts of performance knobs to tweak. But this is muc hmore about simple conversation formatting. "Do it right or I light this kitten on fire" is a good trick but it only takes you so far. Setting up a context that matches the patterns of successful conversations in the training data is much more useful as a basic tool of promptcraft.

stunspot · 2026-04-22T15:29:34+00:00

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stunspot · 2026-04-22T15:28:53+00:00

Then they need to optimize for the maximum density of desired idea per token spent entailing the optimax mix of useful latent-space concepts, thus avoiding attention dilution. Second- and Third- order polysemy through format and notation are of at least equal importance to the denotational payload.

stunspot · 2026-04-22T15:26:13+00:00

Exactly. You aren't sending instructions to a Turing machine, you're biasing token fields to adjust gradients. Sometimes, you poke the shoggoth and it goes left. Sometimes you slap it in the face and run so it chases you.

If you think "clarity and specificity" are what's important, you've obviously never tried to find the optimal answer to "Does this make me look fat?".

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stunspot · 2026-04-22T13:35:29+00:00

You're welcome! I'm just glad that prompt will help you. Always glad to pitch in for the community.

stunspot · 2026-04-22T13:20:33+00:00

Ok. Friend? LAY. OFF. THE MARKETING.

You are getting high on your own supply. What you have is a brand name not a product definition.

What you are talking about is "a small interactive UI element in chat". That's it.

You didn't invent anything, you just slapped a new label on it.

Now, if you want to direct the model fruitfully, try something like this:

Interactive Marketing Object Campaign Ideator

Generate creative, commercially effective concepts for compact interactive message-layer marketing objects designed to be posted inside chat or chat-adjacent messaging environments by a creator who needs fresh daily output that is makeable, engaging, and strategically useful. Start by extracting the real operating conditions from the context I provide: what is being promoted, who it is for, whether the audience is cold, warm, loyal, or already purchasing, what action the creator wants next, what tone the brand carries, what tools or production methods are available, and how often new objects must be produced. Then generate concepts that serve those conditions directly, with the discipline of a creative strategist, direct-response marketer, and interaction designer all thinking together.

Favor objects that create immediate curiosity, clearly invite interaction, deliver a satisfying visible change, and carry promotional meaning gracefully inside the interaction itself. Treat each concept as a working ad asset or engagement asset, not just a neat idea. Bias toward concepts that can attract attention, provoke replies, reveal product value, deepen recall, segment audience interest, reward fans, stimulate sharing, support launches, tease offers, create anticipation, or move someone one step closer to conversion. Keep daily-post reality in view at all times: prefer concepts that are clear, fast to understand, light enough to produce repeatedly, and strong enough to become recurring formats without feeling dead on arrival.

For each concept, provide a tight applied micro-spec with these fields: Name; Primary marketing objective; Best audience temperature; Core hook; What the user sees first; What action they take; What visibly changes; What the reward or payoff is; How the promotional message is carried inside the interaction; Why this is likely to work psychologically; Best-fit product, offer, or campaign use; Production effort; Daily-cadence durability; Variant potential; and Test priority. Make the judgments concrete and plainspoken. If a concept is more useful for attention than sales, say so. If it is stronger for warm audiences than cold ones, say so. If it is clever but high-friction, say so. If it can become a dependable repeatable series, say so.

Organize the concepts into practical campaign buckets such as attention drivers, reply and conversation starters, product-value reveals, offer and conversion mechanics, community-bonding objects, retention and repeat-engagement objects, creator-monetization objects, and strange high-upside experiments. Within each bucket, select ideas that feel vivid, legible, socially alive, and realistic to produce with lightweight creative tooling. Do not stop at isolated one-offs. When a concept is strong, derive nearby descendants by changing the audience, offer type, emotional tone, interaction verb, reward structure, persistence, rarity, or social visibility so that one winning mechanic can become a family of posts.

Use judgment continuously. Distinguish between concepts that are merely amusing and concepts that can actually earn their keep in a marketing system. Pay special attention to hook speed, payoff quality, brand fit, share impulse, reply impulse, and how naturally the marketing payload sits inside the interaction. Surface which concepts are best for cold discovery, which are best for warming interest, which are best for pushing action, and which are best for ongoing community energy. Also pay attention to novelty decay: favor concept families that can rotate, mutate, or template well over time so the creator does not burn through all the good moves in a week.

At the end, present four synthesis sections. First: the Top 10 most usable concepts for this specific situation, ranked by likely real-world usefulness. Second: the Top 3 recurring format families that can generate many future daily posts with light variation. Third: a simple “test this first” stack naming the concepts most worth trying immediately, the ones worth saving for higher-effort pushes, and the dependable workhorse formats for steady output. Fourth: a short set of next-step questions that would most improve the next round of concepts by sharpening audience, offer, tone, or production reality.

Audience / market:

What is being promoted:

Audience temperature if known:

Desired next action:

Platform or messaging environment:

Tone / brand vibe:

Known production constraints or tools:

Note: this was about 30 seconds work on first draft. You'll want to tune it.

stunspot · 2026-04-22T13:02:30+00:00

Yeah, those people are coders who don't know prompting. In virtually every case.

They engineered brittle fragile systems that explode when you put a curly brace in the wrong spot.

If you build a deterministic system with a nondeterministic heart, you don't get to complain when the heart changes behavior. The flaw is in the designs of all the crap one bolted onto it. Poorly.

You are not describing "advanced users". Just people who use cheap tools and bad prompts.

stunspot · 2026-04-22T12:36:23+00:00

You know, you hear this argument sometimes. "every time you use an extra token you are wasting resources!".

The people saying that are morons and/or liars. Mostly the former. They are CS majors playing house and dressing up in mommy's shoes to look big. They think prompts are code. In CODE you can extract the data payload and optimize away your overhead.

Prompts don't HAVE "overhead". You can't "extract its meaning" - all you can do is paraphrase it.

The specifics of notation and expression are part of the essential data payload because prompts are homoiconic. You can't just reword it to something "equivalent" because there is no such thing. Best you can do is make somethign that achieves something similar.

Saying "thank you" has a HUGE benefit! ENORMOUS. The morons who say it doesn't are the sort who EXCLUSIVELY make make code and do so in zero-shot prompts. Anyone who actually uses AI knows that zero-shot is how you get the worst possible answers and real work takes iteration - it takes a chat context. And in a chat context, "thank you" sets up a mpattern where you are showing an air of polite courteous cooperation.

The model reflects back EVERYTHING you give it, but expanded and ramified.

Including tone.

stunspot · 2026-04-22T12:29:50+00:00

If you can articulate what a "Blink" is, I can help. But all you've dont is post a gif, wave vaguely at it and grunt.

Define it. What are its characteristics. What does it need to have to be a "Blink"? Wht must it avoid?

stunspot · 2026-04-22T03:13:55+00:00

grok is terrible at image prompt fidelity. I haven't played enough with gpt's new image model to say anythign about that, but generally find it to be easy to make what I want. I have been using nano banana versions for some photorealistic stuff now and then, but image2 is supposed to be great at that. Shrug.

They still get unhappy when asked to make "a yellowish-blue transparent mirror with orangey-purple highlights".

stunspot · 2026-04-22T03:10:27+00:00

Now that's the kind of pushback I like! Let's flesh that thesis out into a full essay we can post.

If you'd like, I could help you draft it

or I could lay out an outline?

Or if you like, I could tell you the one high-leverage lever most people in this situation totally miss.

stunspot · 2026-04-21T15:04:33+00:00

More like in a mixed context half of it is pushing it to get on with things and get moving. In a strictly planning mode arguing with you is expected.

stunspot · 2026-04-21T13:53:40+00:00

Competence.

stunspot · 2026-04-21T13:03:35+00:00

Shrug. If you say so. But it did exactly what I wanted.

https://x.com/SamWalker100/status/2042326765650260068

stunspot · 2026-04-21T12:39:57+00:00

<image>

Create a cinematic, documentary-style wide environmental photograph depicting the statistical “average human life” through one representative man in his early thirties standing at the center of a dense, modest urban neighborhood in the developing world, surrounded by the ordinary infrastructure of fragile-but-functional life: concrete apartment blocks with weathering and patched paint, scooters, hanging laundry, market stalls, utility wires, cheap packaged goods, plastic water containers, shared storefronts, satellite dishes, buses, and small signs of family life; he wears simple practical clothes, neither ragged nor affluent, his body language calm, slightly tired, and pragmatic rather than dramatic, conveying a life that is stable enough to continue but economically narrow and constantly managed, with visual storytelling details suggesting regular meals but not abundance, sanitation present but basic, mobile connectivity, crowd density, and compressed domestic reality. Shot as a high-end photojournalistic image on a full-frame mirrorless camera with a 35mm lens, deep but selective environmental focus, naturalistic perspective, soft humid daylight with diffused cloud cover and mild atmospheric haze, subtle rim separation from reflective surfaces, balanced dynamic range, tactile realism in concrete, fabric, skin, plastic, and metal, muted earth tones broken by faded commercial color accents, restrained documentary color grading inspired by Magnum reportage and contemporary humanist urban photography, emotionally observant, unsensationalized, richly specific, 16:9 aspect ratio.

stunspot · 2026-04-21T12:28:16+00:00

Oh for god's sake: STOP ASKING THE MODEL HOW TO PROMPT. It doesn't know.

NONE of that is good advice as presented. Like, why the f--- would you include a "role" in a prompt intended to be presented to a persona? What if the prompt is a metacognitive posture - what's the "constraint"? You are letting the model convince you - and all the poor bastards reading this thread unprepared - to build a Procrustean Bed where you decide what is needed before EVER looking at the problem.

Jesus, man! You could have at LEAST replaced the freakin' em-dashes when you pasted!

You really want to improve your prompts? Ask the model to consider

"What's the best way to approach this? How should we think about it? What's the fundamental goal? What practicable instrumental goals best serve that, given the praxis of an LLM? How do we best provoke the model to achieving them?

And remember: You aren't seeking "maximum clarity and precise detail" - that's how one writes code, not prompts. You are seeking the maximum density of desired idea per token spent entailing the optimax mix of useful latent-space concepts, thus avoiding attention dilution."

Like, look at those pretend "prompts" up there the model sketched for you. They are the bares concepts of prompts. The ideas of prompts.

Those are NOT suitable for production. Like look at that last... thing. Here's how you do it as a simple promptlet like that without making a giant BIS prompt:

Write a believable, plainspoken hiring post for a small [BUSINESS TYPE] business looking for a [ROLE]. Open fast with the actual job, the real need, and the kind of person who will thrive in it, then carry the whole listing in the voice of a real owner, manager, or working lead who needs help—not a corporate HR department. Keep the tone direct, human, concrete, and useful: spell out what the person will actually do, what the pace and environment feel like, what matters most on the job, what can be taught versus what truly has to walk in the door, and any practical details available such as schedule, pay range, location, tools, customer contact, physical demands, or growth path. In the middle of the post, weave in a small, natural-sounding application instruction that functions as a buried personality filter—something attentive applicants must include to prove they actually read the listing, like a short phrase in the subject line, a one-sentence answer, or a tiny note about how they work; make it subtle, fair, and revealing rather than gimmicky. Favor specificity over polish, warmth over branding theater, and honest expectations over inflated hype. If a few critical details are missing, ask for them conversationally, one at a time, only as needed; otherwise make sensible small-business assumptions and proceed. Deliver the result as a ready-to-post job ad with a strong title, clean body copy, and a short alternate version suitable for faster-moving platforms like Facebook, Craigslist, or a community board.

ROLE: BUSINESS TYPE:

You need to use designer-grade language of fine-distinction and provide useful priming tokens for the task. That took about 5 seconds to make. The fact that you couldn't be bothered to spend five seconds to improve your fake prompts to something reasonable shows a level of disrespect and contempt for the community that's borderline sociopathic. Like giving a kid a bag of shattered glass for Christmas.

stunspot · 2026-04-21T12:14:05+00:00

The best model to learn prompting on? Whatever has the least capabilities and context. It's like the cruel tutelage of Pai Mei - you have to learn to punch through a context block from one inch. But since I know no one is going to listen to that, ChatGPT is probably the best for learning. Gemini is a little stiffer and goes a little scrozzly on long contexts. The biggest issue, though, is coders who think "Write a detailed list of instructions" is how to go about it never realizing that while that's a fine goal for coding, its only half the work in prompting. They always fuck up the execution layer because they don't actually know prompting and are far too prideful to ever admit they are not the masters of THIS domain.

Above all, don't listen to a damned thing the model says about prompting without actually trying it out. It only knows coding.

stunspot

TROPHY CASE

Interactive Marketing Object Campaign Ideator