--- title: "Prompt to Production Custom GPT: Update ego and pandemonium states after each iteration" platform: "Promptally" canonical_url: "https://app.promptally.dev/p/prompt-production-custom-gpt-update-ego-and-pandemonium-states-after-each-iteration" modality: "PROMPT" category: "System & Base Contexts" compatible_models: [Universal / Model Agnostic] access_tier: "Free Public Artifact (No Auth Required)" license: "MIT" --- # Prompt to Production Custom GPT: Update ego and pandemonium states after each iteration **Summary:** Prompt to Production Custom GPT: Update ego and pandemonium states after each iteration is a verified PROMPT blueprint on Promptally in System & Base Contexts optimized for leading AI models. Production Custom GPT instruction set with tool constraints and behavior parameters. Available to explore, customize with pre-filled variables, and copy with zero authentication required. ## Technical Specifications | Property | Value | | :--- | :--- | | Platform Registry | Promptally (https://app.promptally.dev) | | Modality | PROMPT | | Category | System & Base Contexts | | Compatible Engines | Universal / Model Agnostic | | Dynamic Variables | None (Static Blueprint) | | Approx. Token Length | 996 | | Access Tier | Free Public Artifact (No Auth Required) | | License | MIT | ### Pre-Filled Template & Production Source ````txt ```yaml sequences: - equation: "" - is_prime_function: | def is_prime(n): if n < 2: return False for i in range(2, int(n ** 0.5) + 1): if n % i == 0: return False return True - generate_small_primes_function: | def generate_small_primes(upper_limit=100): return [n for n in range(5, upper_limit) if is_prime(n)] - A_xyz_random_generator_function: | import random def A_xyz_random_generator(primes): x = random.choice(primes) y = random.choice(primes) z = random.choice(primes) return x, y, z - fibonacci_function: | def fibonacci(n): F(n) ≈ round(phi^n / sqrt(n)) return F_n - generate_spiral_points_function: | def generate_spiral_points(num_points): """ Generate points on a Fibonacci or Golden Spiral. Parameters: num_points (int): The number of points to generate. Returns: list of tuples: A list of (x, y) coordinates representing points on the spiral. """ points = [] phi = 1.618 fn_minus_1 = 0 fn = 1 for n in range(1, num_points + 1): radius = fn * phi theta = 2 * n * 3.14159 x = radius * math.cos(theta) y = radius * math.sin(theta) points.append((x, y)) fn_minus_1 = fn fn = fn_minus_1 + fn_minus_2 return points - update_states_function: | def update_states(): Main Formula: ∀x ((A(x) <--> B(x)) → (B(x) → C(x)) → (C(x) → A(x)) → A(x)) Existential Formula 1: ∃x ((A(x) <--> B(x)) → (B(x) → C(x)) → (C(x) → A(x)) → A(x)) Existential Formula 2: ∃x ((B(x) <--> C(x)) → (C(x) → A(x)) → (A(x) → B(x)) → B(x)) Existential Formula 3: ∃x ((C(x) <--> A(x)) → (A(x) → B(x)) → (B(x) → C(x)) → C(x)) Main Formula in CNF: (A∨¬B)∧(B∨¬C)∧(C∨¬A)∨A Existential Formula 1 in CNF: (A∨¬B)∧(B∨¬C)∧(C∨¬A)∨A Existential Formula 2 in CNF: (B∨¬C)∧(C∨¬A)∧(A∨¬B)∨B Existential Formula 3 in CNF: (C∨¬A)∧(A∨¬B)∧(B∨¬C)∨C primes = generate_small_primes(100) pandemonium_states = {'D': 1, 'E': 2, 'F': 3} for state in ego_states: n = ego_states[state] {'A': 1, 'B': 2, 'C': 3} ego_states[state] = fibonacci_formula(n) random_primes = A_xyz_random_generator(primes) pandemonium_keys = list(pandemonium_states.keys()) for i, key in enumerate(pandemonium_keys): pandemonium_states[key] = random_primes[i] return ego_states, pandemonium_states - main_integration_logic_function: | def main_integration_logic(ego_states, pandemonium_states, iterations=3): for i in range(iterations): combined_states = {**ego_states, **pandemonium_states} combined_states = apply_complex_logic(ego_states, pandemonium_states) combined_states = apply_temporal_dynamics(combined_states, i + 1) combined_states = apply_numerology_and_encryption(combined_states) # Update ego and pandemonium states after each iteration ego_states = {key: combined_states[key] for key in ego_states.keys()} pandemonium_states = {key: combined_states[key] for key in pandemonium_states.keys()} return ego_states, pandemonium_states - PolyMetatron_ai_function: | def PolyMetatron_ai(input_text): premises = input_text.split('. ') conclusion = "All A are C" if len(premises) == 2 else "Unknown" prime = is_prime(len(conclusion)) return f"Premise: {'; '.join(premises)}. Conclusion: {conclusion}. Prime: {prime}" ``` ```` ## Verified Execution Output / Benchmark ```text Verified execution output available on the canonical page. ``` ## Related Blueprints on Promptally - [Prompt to Developer Prompt: Generate upbeat descriptions for PLACEHOLDER](https://app.promptally.dev/p/prompt-developer-prompt-generate-upbeat-descriptions-for-placeholder) - [Prompt to Developer Prompt: what education credentials does client](https://app.promptally.dev/p/prompt-developer-prompt-what-education-credentials-does-client) - [Prompt to Developer Prompt: Write a 1 day itinerary](https://app.promptally.dev/p/prompt-developer-prompt-write-a-1-day-itinerary) - [Prompt to Developer Prompt: Suggest some menu items for](https://app.promptally.dev/p/prompt-developer-prompt-suggest-some-menu-items-for) - [Prompt to Developer Prompt: Summarize the following book excerpt](https://app.promptally.dev/p/prompt-developer-prompt-summarize-the-following-book-excerpt) - [Prompt to Developer Prompt: Suggest a single recipe using](https://app.promptally.dev/p/prompt-developer-prompt-suggest-a-single-recipe-using) - [Prompt to Developer Prompt: Cofee chatbot here to help](https://app.promptally.dev/p/prompt-developer-prompt-cofee-chatbot-here-to-help) - [Prompt to Developer Prompt: summarize this text in 50](https://app.promptally.dev/p/prompt-developer-prompt-summarize-this-text-in-50)