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Nano Banana prompt: Lego bricked objects

Turn anything into a LEGO object crumbling into blocks with this prompt

Type in the prompt and replace [OBJECT] - your art is ready

Get the text prompt below 👇

[Minimalist food photograph, [1080x1080] – a single [OBJECT] rests on a light, matte surface and is captured mid-transformation into a lego bricks 3D form: one half remains intact while the other organically fragments into large, floating lego bricks that drift outward, each brick revealing the object’s texture, ingredients, and colors. Studio lighting with soft, realistic shadows, shallow depth of field, tasteful perspective and composition, hyperrealistic detail, stylish geometric abstraction, high resolution, cinematic close-up]

The Core: In this tutorial, you will learn how to create a CRM dashboard for your sales pipeline with Notion AI. Instead of manually creating pages, subpages, and toggles, all of this will be done for you using AI prompts.

Step-by-step:
- Go to Notion.so, open Notion AI, and collapse the side panel for a cleaner workspace

- Use this prompt: "A CRM pipeline database where I can track leads from first contact through conversion. Add filters for email, type of subscriber, first contact, second contact, did they convert, and why didn't they convert"

- Click Submit and let Notion AI build the database structure, then agree to suggested additions like follow-up stages and next steps

- Review the generated "CRM – Sales Pipeline" page and refine fields by changing toggles to checkboxes or adding filters like deal size

Pro Tip: Experiment with prompt styles. For example, instead of saying "create me a CRM," try "create a sales pipeline with Kanban stages" or "build a lead tracker with follow-up reminders." The more specific you are, the better your results.

Spent 6 months deep in #prompt engineering. Here's what actually moves the needle:

Getting straight to the point:

1. Examples beat instructions Wasted weeks writing perfect instructions. Then tried 3-4 examples and got instant results. Models pattern-match better than they follow rules (except reasoning models like o1)

2. Version control your prompts like code One word change broke our entire system. Now I git commit prompts, run regression tests, track performance metrics. Treat prompts as production code

3. Test coverage matters more than prompt quality Built a test suite with 100+ edge cases. Found my "perfect" prompt failed 30% of the time. Now use automated evaluation with human-in-the-loop validation

4. Domain expertise > prompt tricks Your medical AI needs doctors writing prompts, not engineers. Subject matter experts catch nuances that destroy generic prompts

5. Temperature tuning is underrated Everyone obsesses over prompts. Meanwhile adjusting temperature from 0.7 to 0.3 fixed our consistency issues instantly

6. Model-specific optimization required GPT-4o prompt ≠ Claude prompt ≠ Llama prompt. Each model has quirks. What makes GPT sing makes Claude hallucinate

7. Chain-of-thought isn't always better Complex reasoning chains often perform worse than direct instructions. Start simple, add complexity only when metrics improve

8. Use AI to write prompts for AI Meta but effective: Claude writes better Claude prompts than I do. Let models optimize their own instructions

9. System prompts are your foundation 90% of issues come from weak system prompts. Nail this before touching user prompts

10. Prompt injection defense from day one Every production prompt needs injection testing. One clever user input shouldn't break your entire system

The biggest revelation: prompt engineering isn't about crafting perfect prompts. It's systems engineering that happens to use LLMs

Hope this helps

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↳ 300+ curated prompts
↳ 12+ departments (IT, HR, Sales, Product, CS…)
↳ 25 per role

Adapt them with your KPIs & product context for better results! 🔥

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Link to the packs in 🧵 ↓

This guy literally revealed the one prompt that rewires ChatGPT’s brain.

Use these ChatGPT prompts to save hours:

AI storytelling prompt👇

“You are an expert noscriptwriter specializing in viral storytelling formats used by top faceless YouTube channels.

I will give you a noscript. Based only on that, write a full 3-act story that matches the tone, pacing, and emotional pull of the most engaging storytime channels on YouTube.

Title: {insert}

Your task:
1.Analyze the noscript deeply

→ What emotional tension does it carry?
→ What assumptions or questions will the viewer have?
→ What kind of characters and conflicts would create a satisfying arc?

2.Write a complete 3-part narrative

•Act 1: The Hook & Setup
Introduce a compelling character. Set the stakes immediately. Create tension in the first 10 seconds. Make the viewer NEED to know what happens next.

•Act 2: Escalation & Conflict
Show unexpected twists, moral challenges, and emotional turns. Use believable dialogue and relatable stakes. Maintain a natural, conversational pacing.

•Act 3: Twist & Moral
End with a powerful twist, reveal, or lesson. Must trigger emotional resolution (justice, irony, redemption, heartbreak). Leave the viewer thinking.

3.Write the story for voiceover delivery
•Keep the tone natural and emotionally charged
•Vary sentence lengths to control rhythm
•Use internal thoughts, dialogue, and vivid imagery
•Break the noscript into visual segments for easy editing (scene-based)

4. At the end, give me:

•A compelling thumbnail/noscript combo based on tension
•The emotional trigger this story activates (e.g., injustice, betrayal, empathy)”

Stop telling LLMs like Claude and ChatGPT what to do.

Start asking them questions instead.

I replaced all my instruction prompts with question prompts.

Output quality: 6.2/10 → 9.1/10

This is called "Socratic prompting" and here's how it works: