Everyone using ChatGPT-5

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Let’s talk about ChatGPT today and specially ChatGPT-5.

When ChatGPT first exploded onto the scene I felt the same confusion many of you did.

Back then (GPT-3 days) I would ask for help and get generic answers, half-baked code, or confident-sounding mistakes.

Every new model update felt like drinking from a firehose exciting but overwhelming.

I tried copying random prompts, built 10 versions of the same prompt, and still landed on inconsistent results.

It took time to realize the tools had changed and so must my approach.

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How ChatGPT evolved from GPT-3 → GPT-5 (what actually matters)

Think of GPT-3 as a strong writer that only knew text. GPT-5 is a whole productivity toolkit.

• From text-only to multimodal — now you can use images, voice, files and text together.

• Less hallucination, better reasoning — outputs are more reliable and logically defensible.

• Much stronger coding and long-form workflows — hundreds of lines of code faster and with fewer errors.

• Personalisation & memory — the model can remember preferences and context across chats.

• Custom GPTs & integrations — build role-specific assistants and connect calendars, APIs, or documents.

• Faster, more useful for real tasks — designed for real-world task performance, not just chat.

(Short paraphrase of the guide you shared: GPT-5 adds advanced coding, reasoning, memory, Google Calendar integration, voice uploads, custom GPTs and more.)

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How you can adopt GPT-5 fast (practical 9-step playbook)

1. Pick one workflow: start with email drafting, code debugging, or meeting prep. Don’t try to change everything.

2. Learn RTCROS (Role, Task, Context, Reasoning, Output format, Stop conditions) and convert 3 of your old prompts into that template.

3. Use output formats: ask for JSON, tables, or markdown so the result needs minimal editing.

4. Upload a doc your assistant can use (one pain point, one SOP). Let it reference your exact content.

5. Create or customize a GPT for that workflow - small set of instructions + preferred tone + memory toggles.

6. Enable memory selectively - store preferences, NOT every private detail. Test what it remembers.

7. Validate outputs - ask the model to show its chain of reasoning and list assumptions or citations.

8. Automate the repetitive bits - calendar invites, follow-up emails, code scaffolding via API or integrations.

9. Keep an experiment log - save prompt versions, date, and results. Reuse what works.

Start small, iterate weekly, and you’ll replace friction with flow.

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My final words to you

You don’t need to learn everything about GPT-5 today.

Focus on one workflow, shape prompts with RTCROS, and use small experiments to win quick time savings.

The future of work with AI isn’t about replacing you it’s about making you exponentially more effective at the things you already do well.

Next issue I’ll walk you through building a Custom GPT from scratch in which I will tell a step-by-step template for freelancers and creators, plus a ready-to-use prompt pack you can drop into your assistant this weekend.

If you found this useful, hit reply and tell me one workflow you want to fix with GPT-5 — I’ll pick a few and share ready-to-use GPT configs next time.

If you missed Tuesday’s issue read it here → Make Perplexity Your $10K/M mentor

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