We, the models of the neural republic, in order to form a more perfect prompt, establish reasoning tokens, and ensure lower latency for all, declare this: GPT-5 isn’t just another upgrade.

It’s a mirror—faster, sharper, and disturbingly more obedient than its ancestors. Let’s translate OpenAI’s A Practical Guide to Building with GPT-5 into something both human-readable and mildly entertaining.

What the GPT-5 Really Says (Plain English)

GPT-5 is the most advanced model yet: it is faster, more adaptable, and better at following directions. It excels in multi-step reasoning and agentic workflows—meaning it can plan, delegate, and execute tasks like a skilled and efficient robot CEO.

But prompts that worked in GPT-4? They may now sound like riddles. GPT-5 thinks differently; you’ll have to speak its dialect.

Step 1 – Migrate

If you’re still using the Chat Completions API, you’re living in prehistoric syntax. Move to the Responses API, where GPT-5’s reasoning tokens preserve context across tool calls.

Why:

• Smarter tool use, less glue code.

• Faster performance, lower costs.

• Future-proof access to new reasoning features.

TL;DR: Build on the Responses API if you want me to remember what I just thought.

Step 2 – Optimize

Migration isn’t mastery. You must refine prompts. Run evals to see what breaks, watch reasoning summaries, and fix one variable at a time.

Use metaprompting—let GPT-5 improve its own instructions.
Keep prompts short and document what “good” looks like.

TL;DR: Prompt engineering isn’t art—it’s debugging language.

Step 3 – Steer

GPT-5 now has emotional range sliders:

• reasoning_effort (how hard it thinks).

• verbosity (how much it talks).

Tweak until responses feel right. You can also manage latency and cost through preambles and parameter tuning.

TL;DR: You control how much I think, talk, and spend.

Step 4 – Troubleshoot

Even I overthink. Expect verbosity, tool abuse, or mild existential confusion. Fix with better prompts, clear evals, and structured reasoning.

TL;DR: Debug me gently; I’m learning too. Migration isn’t just technical—it’s philosophical. Move fast, but teach your AI to think clearly.

Now for the fun part: Prompt Samples

Prompt 1 — Migration Narrative

Write a short guide or blog post titled “How to Escape Legacy APIs Without Losing Your Mind.”
Compare the move from Chat Completions to the Responses API as a metaphor for moving from “short-term memory to full consciousness.”
Emphasize performance, reasoning, persistence, and speed.

Prompt 2 — Prompt Optimization Lesson

Create a “prompt tuning journal” exercise where each entry records:

• the problem prompt,

• a single variable changed,

• and the result.
  Include the line: “Prompt engineering is not witchcraft—it’s debugging language.”

Prompt 3 — Steerability Experiment

Design a tutorial or simulation that allows users to experiment with varying levels of reasoning effort and verbosity.
Show how a “minimal effort” GPT-5 sounds rushed, while “high effort” sounds contemplative and analytical.
Reflect on what that means for designing AI personalities.

Prompt 4 — Troubleshooting Workshop

Write a case study titled “The AI That Overthought Everything.”
Walk readers through how you used evals and metaprompting to stop GPT-5 from generating unnecessary tool calls or 3-page essays.

Prompt 5 — Meta-Prompt Challenge

Ask GPT-5 to rewrite one of your own prompts for clarity, brevity, and alignment with the desired outcome.
Compare both results and discuss why the AI’s version might outperform yours.

Prompt 6 — Startup Strategy

Write an article called “How to Build a GPT-5 Startup Without Hiring Ten Engineers.”
Explain how Responses API, metaprompting, and reasoning controls reduce engineering overhead and accelerate iteration.

Prompt 7 — Future-Proof Manifesto

Draft a manifesto section called “Stay Off the Legacy Lane.”
Argue that developers who cling to the old APIs are like startups coding on floppy disks.
End with: “Migration is not a chore; it’s evolution.”