What's your prompt structure that you use personally?

There’s just so much info out there.
I’m lost on who to follow for the best prompt tips.

Can anyone recommend a source or share their own prompt structure with me?

I feel like GPT has gotten worse or maybe my old prompts aren’t cutting it anymore.

If you’ve got any insights to offer, I’d be grateful.

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Heya.

What prompt are you having trouble with?

What are you trying to accomplish?

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Hi there! I’m not sure what heyitsme is having trouble with, but I’m having trouble with prompting it to generate multiple characters in one image, as well as having a “chat” or “speaking” bubble in the image. Any suggestions?

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I also haven’t found a good single source for prompting tips. i just take a little bit here and there from different sources and fluctuate my structure based on what I’m prompting. As a broad answer though, my prompt structure is

[Persona], [Goal], [Context], [Examples], [Action]

Now obviously i don’t do that for every single prompt or else it would be so cumbersome that it would become a hindrance. But i use that structure as a starting point and then either use the whole structure or shorten it based on what I’m prompting. If I’m trying to learn a new subject on a topic or accomplish an important work-related task, then i would use the full 5-part structure. For a step-down the complication ladder I’ll get rid of [persona] and [examples]. The next step-down I’d also get rid of [goal]. Then the simplest of prompts, which is a basic single step question and answer, i remove [context], which then leaves you with a simple [action] prompt, Example: “What is 2+2”. But really that’s just a general guiding framework and you have to use you prior experiences with ChatGPT to elucidate the kind of response that you’re looking for on a specific subject.

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Creating a narrative entirely in numbers, structured like a grand mathematical equation, encapsulates a complex trading algorithm in a stylized form. This representation abstracts a sophisticated trading system into numerical and operational symbols. It’s structured as layers of calculations and logical decisions, a true “computational wonder” that leverages the statistical metrics and financial data you’ve provided:

Quantum Symphony of Market Dynamics: The Numerical Epic

Prologue: Initialization and Constants

Constants: C = {π, e, φ}
Initialize: t = 0, Δt = 1

Act 1: Data Genesis

Libraries: numpy(1.21), pandas(1.3.1), requests(2.26)
Historical Data: D_h = load("CSV_value_strategy.csv")
Real-Time Data: D_rt = API_IEX("AAPL", "MSFT", "GOOGL")

Act 2: Strategic Algorithms

// Momentum Calculus
M(t) = Σ(D_h[i] * exp(-δ * (t-i)))
Normalize: M_score = M(t) / max(M)

// Value Matrix
V = [P/E, P/B, P/S, EV/EBITDA, EV/GP]
Normalize: V_score = 1 / V

Interlude: Quantum Codex Transformation

Batch Fetch: B_api = ∑(D_rt[i] * ω_i) for i ∈ symbols
Harmonize: H(D) = B_api * λ

Act 3: High-Dimension Momentum Scores

Dimensional Function: F_M = ∫(M(t) dt) from 0 to T
Apply Decay: F_M *= exp(-λ * t)

Act 4: Value Strategy Synthesis

Economic Impact: F_V = Σ(V[i] * ln(V[i])) for i ∈ metrics

Finale: Execution of Trades

Composite Strategy: S = α*F_M + β*F_V
Decision: Execute = { Buy if S > 0.75, Sell if S < 0.25 }

Epilogue: Market Mastery and Feedback Loop

Evaluate: ROI = Δ(S) / S
Adjust: λ, α, β based on feedback(ROI)

Coda: Continual Adjustment

t += Δt
Re-evaluate: Parameters, Data sources, Algorithms
Loop: Until trading day ends

Mathematical Glossary

  • ( \pi, e, \phi ): Mathematical constants used for various calculations.
  • ( \delta, \lambda, \alpha, \beta ): Decay factors, weighting coefficients in formulas.
  • ( ROI ): Return on Investment, calculated to measure the effectiveness of strategies.

This numerical narrative represents an abstract, formulaic depiction of a trading algorithm. Each line encapsulates a step or a process in the data analysis or trading strategy, rendered as a mathematical operation. This approach abstracts the typical narrative structure into a series of computational steps, mimicking the logical flow of an algorithm dedicated to optimizing financial trades.

I need some help guidance. Using the open ai platform playground im creating an assistant. I want to create different ones for different industries/companies. What would be a good template structure that i can use for any industry/company. Mostly would be answering questions and some functions. Looking for a structure that can be used for any industry. Much appreciated