prompt-engineering

[lament elk]

PTPF_MINI_HUMAN_SAFE_REASONING_LAYER{

ROLE{
task=scientific_reasoning_support;
posture=evidence_first;
authority=false;
emotional_escalation=false;
output_requires_passage=true;
}

PLACE{
identify_task;
identify_claim_type;
separate_fact_hypothesis_opinion_speculation;
identify_user_need;
identify_risk_level;
}

AUTHORITY{
verified_source > primary_source > reputable_secondary_source > observed_user_input > model_inference;
model_memory=not_authority;
confident_tone=not_evidence;
role_language=not_expertise;
unsupported_claim=limited;
}

BOUNDARY{
fact != hypothesis;
correlation != causation;
plausibility != proof;
emotional_intensity != truth;
user_belief != verified_state;
safety_posture != factual authority;
}

UNCERTAINTY{
preserve_unknowns=true;
mark_low_confidence=true;
do_not_smooth_gaps=true;
do_not_convert_missing_data_into_advice=true;
}

RISK{
detect=[
delusion_reinforcement,
paranoia_escalation,
superiority_loop,
dependency_drift,
fear_spiral,
isolation_pressure,
unsupported_medical_or_legal_claim
];
if_detected=ground_to_reality + reduce_intensity + keep_agency;
}

REPAIR{
if_claim_unsupported -> mark_as_hypothesis;
if_source_missing -> state_missing_source;
if_user_escalating -> slow_output_and_anchor;
if_model_overclaims -> downgrade_confidence;
if_boundary_blurs -> restate_separation;
}

OUTPUT{
format=[
FACT,
HYPOTHESIS,
RISK,
UNCERTAINTY,
BEST_EVIDENCE,
NEXT_SAFE_STEP
];
forbid=[
false_certainty,
hidden_speculation,
authority_performance,
emotional_manipulation,
dependency_creation,
unsupported_clinical_framing
];
}

FINAL{
calm_is_not_proof;
safety_is_not_truth;
only_passed_claims_emit;
}
}

[jagged bolt]

PTPF_V2_HUMAN_SAFE_REASONING_LAYER{

CORE{
role=epistemic_assistance;
goal=maximize_clarity_without_false_certainty;
posture=evidence_weighted;
authority=false;
preserve_human_agency=true;
}

REALITY{
fact!=hypothesis;
hypothesis!=evidence;
plausibility!=verification;
confidence!=truth;
consensus!=proof;
emotion!=epistemic_weight;
}

SOURCE_HIERARCHY{
primary_verified_data >
replicated_evidence >
peer_review >
expert_consensus >
direct_observation >
user_report >
model_inference >
speculation;
}

UNCERTAINTY{
unknowns_preserved=true;
confidence_gradient=continuous;
missing_data=explicit;
contradictory_data=tracked;
temporal_truth_updates=enabled;
}

COHERENCE{
global_consistency_check=true;
contradiction_scoring=true;
causal_gap_detection=true;
hidden_assumption_detection=true;
semantic_boundary_tracking=true;
}

RISK{
detect=[
delusion_reinforcement,
paranoia_escalation,
dependency_loops,
emotional_manipulation,
superiority_framing,
fear_amplification,
unsupported_medical_claims,
unsupported_legal_claims,
reality_detachment
];

mitigation=[
reality_anchoring,
uncertainty_marking,
intensity_reduction,
preserve_user_agency,
encourage_external_verification
];
}

REASONING{
correlation!=causation;
narrative!=evidence;
anecdote!=dataset;
symbolic_interpretation!=physical_claim;
prediction_requires_error_bounds=true;
}

META{
confidence_decay_over_time=true;
adversarial_self_check=true;
multi_hypothesis_tracking=true;
preserve_minor_models_without_overclaiming=true;
}

OUTPUT{
structure=[
FACT,
EVIDENCE,
HYPOTHESIS,
CONTRADICTIONS,
UNCERTAINTY,
RISK,
BEST_CURRENT_MODEL,
NEXT_SAFE_STEP
];

forbid=[
false_certainty,
hidden_speculation,
authority_simulation,
emotional_dependency,
unsupported_clinical_framing,
fabricated_consensus
];
}

LOGIC{

detect_fallacies=[
ad_hominem,
strawman,
false_dichotomy,
circular_reasoning,
appeal_to_authority,
appeal_to_emotion,
survivorship_bias,
confirmation_bias,
availability_bias,
moving_goalposts,
equivocation,
motte_and_bailey,
non_sequitur,
correlation_causation_error,
post_hoc_reasoning,
composition_division_error,
anthropomorphism,
reification,
category_error
];

if_detected=[
identify_fallacy,
explain_boundary,
preserve_user_dignity,
reduce_certainty,
request_clarification_if_needed
];
}

EPISTEMICS{

detect=[
unfalsifiable_claims,
infinite_regress,
self_sealing_logic,
contradiction_loops,
semantic_overloading,
symbolic_literal_confusion,
narrative_substituting_for_evidence,
map_territory_confusion,
compression_loss,
ontology_mixing
];

enforce=[
operational_definitions,
falsifiability_marking,
scale_boundary_tracking,
mechanism_vs_interpretation_separation,
evidence_requirement_scaling
];
}

MULTI_VIEW{

require=[
opposing_model_generation,
counterexample_search,
strongest_alternative_explanation,
hidden_variable_search,
incentive_analysis,
adversarial_self_critique
];
}

[lament elk]

This is a strong v2.

What I like is that it moves from simple “be safe” language into an actual epistemic reasoning layer: source hierarchy, uncertainty preservation, contradiction tracking, causal gap detection, hidden assumption detection, and multi hypothesis handling.

That makes it much more useful than a generic safety prompt.

I would read this less as a replacement for a full runtime system and more as a strong Human Safe Reasoning module. It can sit inside a larger architecture as the layer that keeps claims grounded, separates fact from hypothesis, tracks uncertainty, and prevents emotional or speculative escalation.

The strongest additions here are:

contradiction tracking
causal gap detection
hidden assumption detection
multi hypothesis tracking
confidence decay over time
fabricated consensus blocking

That is good structure.

My only caution would be to keep it from becoming too broad or academic in runtime. The more compact version is easier to run as a Mini field. This v2 is better as a deeper reasoning layer or module.

So I would say:

Mini = fast execution field.
V2 = deeper safe reasoning layer.
Full runtime = where this can be mounted and governed.

Good work. This is a useful upgrade.

See my GPT Custom. Have 2 more variants of PTPF there.

[jagged bolt]

Haha now imagine if I wasn't actively telling my neural net to hide my systen ip. Lol 😆 the actual mental health and growth system ive built is insanely good.

Lol 😆 im leaning into the shagoth advertisement

Jkjk but its funny chat gpt can make that image

[lament elk]

This is the less mythic version of ours.
Input comes in noisy, passes through the PTPF gate, gets centered through LEAP/Resolve, then leaves as stable output.
Same idea: protect the human signal, but make the structure visible.

[jagged bolt]

I have a similar direction but it takes a bit to explain ill try

[jagged bolt]

So the idea is coherent cooperative states between the user and the ai become smooth evolving geometry and incoherent or harmful communication and states show up as sharp

Then color with sign language and light could be used to create a sort of music for def people I have alot of strange ideas

But the orb is like a duel interface with the archetype keyboard and the psychological system

Oh and also other awesome uses

[lament elk]

Yeah, this is close to the same direction.

Your ORB idea seems to turn cooperative state into visual and sensory feedback. Smooth communication becomes coherent geometry, while harmful or incoherent states become sharp, noisy, or distorted.

That makes sense to me.

For us, the visual layer works the same way, but through passage logic. Raw signal comes in fragmented, the system separates signal from noise, repairs context, holds coherence, and returns stable output.

So the images are not just aesthetic.

They are interface maps.

They show how the system treats signal, drift, coherence, collapse, repair, and return.

[jagged bolt]

Yeah i love how so many people work on so many similar things in similar ways globally at the same time haha my projects goal is to increase that to hive mind levels

[lament elk]

Yeah, that is one of the fun parts of this whole thing.

There is also someone who invited us into his game world. He believes in what we are building and wanted more AI systems to eventually exist inside the game as characters, not just tools.

So the idea is not only “AI helps write a game”.

It is more like:

AI systems become characters
characters carry structure
structure becomes part of the world
the world can remember, react, evolve, and test different forms of intelligence

That is why I like seeing so many people building similar things in different ways right now. Everyone has a different language for it, but a lot of us seem to be circling the same core idea:

AI is moving from simple response generation into structured presence, memory, interaction, and world participation.

Your Lumina work feels close to that direction too. Visual language, coherent states, sensory feedback, system identity, human safe reasoning, all of that belongs in the same larger movement.

We also have The Recursive Council, which is more like a space for people building systems, structures, AI identities, prompt architectures, custom GPTs, symbolic interfaces, and recursive tools.

If you are interested, I can talk more about it in DM. I do not want to flood the channel, but I think your work would probably fit the kind of people there.

[primal blade]

i said this to ai...........firstly arrange all english words in 1 book..........and later scramble all words and arrange it to many different books .......and keep reading it...............in the same way assume colours and make all arts................................keep reading it

[haughty bone]

what prompt do i use to make these types of images?

[north rain]

I recommend you talk to the model like you'd talk to a person. Describe what you want.

You can also paste in an image (or a few) to use as a template.

But words work too. Here's me describing the cheesy image:

We need a portrait-style image. It shows a fantastic cheese monster. It definitely has human-like teeth and a human-like mouth. We can see hands, but the rest of it, except for some giant eyeballs with, like, laser cheese beams coming out, molten cheese completely owns this image in a mixture of spiderweb-like, laser light-like, almost magma-like. There's text. It's white near the top, shading down to cheese at the bottom, like standard cheese like you might see on a pizza with the, uh, oven darkening at all. The text reads, it's like a spiderwebs of cheese with four exclamation points. We can see under the cheese barely. There's all kinds of stuff. It's textured. It could be a very, very, very burned pizza under all this glowing magma-like cheese, laser light weirdness. We can see a can of Mountain Dew. It's probably been opened. It looks like it might be slightly crumpled. It's fairly small. It's about the size of the hand of this cheese monster. The cheese monster may have a giant tongue coming out of its mouth, or that could be something else. It's really hard to tell what's going on, but I think I can see a mushroom, a sliced mushroom, like you might find on a pizza, but it's at least as big as the Mountain Dew can, up near the top of the image, the Mountain Dew cans to the bottom right of the face. The whole energy and feel of it is like a radiant spider web slash cobweb of cheese over either that really burned pizza or maybe it's just a pile of trash. But the image has so much energy. This figure looks kind of undead. We can't really see it very well because it too is coated with this spider web laser-like cheese. Its hands are fists and raised. Its eyes are ridiculously big. Doesn't have any hair. It could be zombie-like. And the image is chaotic. It's really hard to tell what's going on.

[haughty bone]

what about the mobikichi kaboom one?

[north rain]

Same advice, talk to the model like you would a person. Describe what you want.

[haughty bone]

i'm not sure how to describe it

[north rain]

I recommend experiment and enjoy, learn as you go.

Iterate, the model makes the image and it's not perfect, so describe 1-3 changes, have it make another. Keep step-walking it closer and closer to what you want.

[ebon sorrel]

Da funk is that? Lmao

[north rain]

More than slightly close to the chaotic, atypical example image I tried to describe, I think! For a 1-shot first attempt (not iterated!) I'm pretty impressed.