Get ChatGPT-5 Ready with These Prompting Principles

My site: https://natebjones.com
My substack: https://natesnewsletter.substack.com/

Takeaways:
1. Ditch GPT-4.0: Upgrading to reasoning models—GPT-0.3, Claude Opus 4, or Gemini 2.5 Pro—immediately raises the ceiling on what AI can do for you.
2. Self-Consistency Checks: Prompt the model for multiple answers, then have it compare and reconcile them to slash hallucinations and boost accuracy.
3. Program-of-Thought: Tell the model to solve problems with code or math tools; numerical precision skyrockets when it writes and runs functions.
4. Plan-and-Solve Workflow: Make the model outline a step-by-step plan before executing any task for clearer logic and better results.
5. Structural Guardrails: Wrap your instructions with explicit edge cases, fallbacks, and output formats—90 % of Claude’s system prompt is guardrails for a reason.
6. Context Positioning & Negatives: Put mission-critical instructions in the first and last 10 % of the prompt and include “don’t do this” examples to avoid failure modes.
7. Meta-Prompting: Ask the model to critique, clarify, and suggest improvements to your prompt; it knows its own capabilities better than you do.

Quotes:
“We’re stuck on GPT-4.0, and it’s capping our perception of what AI can do.”
“Models know themselves better than we know them—use meta-prompting to let them teach you.”
“Good instructions are just the motor; guardrails and edge cases build the ship that actually sails.”

Summary:
I argue that real progress starts by abandoning ChatGPT-4.0 and switching to inference-first models like GPT-0.3, Claude Opus 4, or Gemini 2.5 Pro. With a better engine in place, I share three evidence-backed techniques—self-consistency, program-of-thought, and plan-then-solve—that reliably improve outputs. I then outline structural prompt principles: embed guardrails and edge cases, prioritize first-and-last-ten-percent context, and use negative examples. Finally, I show how meta-prompting lets the model refine prompts, surface uncertainties, and reveal new approaches. These simple, memorable moves make prompting easier and dramatically more effective in 2025’s reasoning-model era.

Keywords:
GPT-0.3, Claude Opus 4, Gemini 2.5 Pro, reasoning models, prompt engineering, self-consistency, program of thought, plan and solve, guardrails, edge cases, context positioning, negative examples, meta-prompting